free research paper-artificial intelligence-neural network recent 2014




ESTIMATION OF DEMAND AND SUPPLY OF PULPWOOD BY ARTIFICIAL NEURAL NETWORK: A CASE STUDY IN TAMIL NADU
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Abstract The annual demand of paper and paperboard, including newsprint is at 11.15 Million Tones (MT) in India. The per-capita consumption is nearly 10.5 kg. The growth in the number of paper mills was from 17 units in 1950 to 759 units in 2010 with the production

Predicting the Trend of Land Use Changes Using Artificial Neural Network and Markov Chain Model (Case Study: Kermanshah City)
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Abstract: Nowadays, cities are expanding and developing with a rapid growth, so that the urban development process is currently one of the most important issues facing researchers in urban issues. In addition to the growth of the cities, how land use changes in macro

Enhancement of Cutting Parameters in En 8 Steel Using Artificial Neural Network: A Review
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ABSTRACT In a Machining process, it is essential to find the optimum cutting parameters of the surface roughness as it play a vital role in reduction of wear due to friction in mating parts. In this work a case study of Turning of EN 8 steel has been undergone an

Monitoring and Detecting Health of a Single Phase Induction Motor Using Data Acquisition Interface (DAI) module with Artificial Neural Network.
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Abstract:-This paper deals with the problem of detection of induction motor incipient faults and usefulness of Artificial Neural Network (ANN) in this respect. The research work diagnoses the three major faults such as stator inter-turn faults, bearing faults and

The artificial neural network approach based on uniform design to optimize the fed-batch fermentation condition: application to the production of iturin A
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Abstract Background: Iturin A is a potential lipopeptide antibiotic produced by Bacillus subtilis. Optimization of iturin A yield by adding various concentrations of asparagine (Asn), glutamic acid (Glu) and proline (Pro) during the fed-batch fermentation process was

A Novel Strategy for Speed up Training for Back Propagation Algorithm via Dynamic Adaptive the Weight Training in Artificial Neural Network
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Abstract: The drawback of the Back Propagation (BP) algorithm is slow training and easily convergence to the local minimum and suffers from saturation training. To overcome those problems, we created a new dynamic function for each training rate and momentum term. Improving forecasting especially time series forecasting accuracy is an important yet often difficult task facing forecasters. Both theoretical and empirical findings have indicated that integration of different models can be an effective way of improving upon their predictive

Evaluation of Two Statistical Tools (Least Squares Regression and Artificial Neural Network) in the Multivariate Optimization of Solid-Phase Extraction for
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This work proposes the use of multivariate optimization as a procedure for cadmium determination in leachate samples via flame atomic absorption spectrometry after solid phase extraction using a minicolumn packed with Amberlite XAD-4 modified with 3, 4-

Modelling and forecasting economic time series with single hidden-layer feedforward artificial neural network models
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Abstract This paper contains a statistical approach to artificial neural networks modelling. The model is defined, its estimation procedure explained, and tests for its validity developed. A simulation study, two applications to the classical benchmarks of the Lynx and Sunspot

Prediction of Viscosities of Aqueous Two Phase Systems Containing Protein by Artificial Neural Network
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Abstract The viscosities of aqueous two phase system containing bovine serum albumin (BSA) were predicted by artificial neural network (ANN) as a function of concentration of poly- ethylene-glycol (PEG), concentration of BSA and temperature. A three layer feed forward

Modeling of glycolysis of flexible polyurethane foam wastes by artificial neural networkmethodology
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Abstract The glycolysis process as a useful approach to recycling flexible polyurethane foam wastes is modeled in this work. To obtain high quality recycled polyol, the effects of influential processing and material parameters, ie process time, process temperature,

Design and Implementation of Artificial Neural Network System for Stock Exchange Prediction
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ABSTRACT Stock prediction with artificial neural network (ANN) techniques is one of the most important issues in finance being investigated by researchers across the globe. ANN techniques can be used extensively in the financial markets to help investors make

Discrete Wavelet Transform and Artificial Neural Network Based Short Circuit Fault Diagnosis in Direct Torque Control Permanent Magnet Synchronous Motor
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Abstract In this paper, an effective method to detect the faults in Direct Torque Control Permanent Magnet Synchronous Motor (DTC PMSM) drive system is proposed. It is based on the analysis of the quadrature current component of the stator current and Discrete Levulinic acid (LA) is one of the versatile chemicals that can be produced from lignocellulosic biomass. In this study, response surface methodology (RSM) and artificial neural network (ANN) were applied to optimise LA yield from glucose, empty fruit bunch (

Artificial neural network features for speaker diarization
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ABSTRACT Speaker diarization finds contiguous speaker segments in an audio recording and clusters them by speaker identity, without any a-priori knowledge. Diarization is typically based on short-term spectral features such as Mel-frequency cepstral coefficients (MFCCs

Lung Cancer Detection Using Artificial Neural Network Fuzzy Clustering
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Abstract: To evaluate the performance of Computer Aided Diagnosis (CAD) for Lung Cancer using artificial neural intelligence on CT scan images. Lung Cancer can be summarized by evaluating region of interest using maximum entropy and supervised learning. Lung

Gesture Recognition Using Artificial Neural Network
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Revised: 22/03/2014 Accepted: 23/04/2014 Published: 30/04/2014 Abstract-Information communication between two people can be done using various medium. These may be linguistic or gestures. Gestures recognition means identification and recognition of

An Investigation of Differencing Effect in Multiplicative Neuron Model Artificial Neural Networkfor Istanbul Stock Exchange Time Series Forecasting
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Abstract In recent years, good alternative methods have been proposed to obtain forecasts for a time series. Artificial neural networks have been commonly used for forecasting purpose in the literature. Although, multilayer perceptron artificial neural network is the

Optimisation of pumpkin mass transfer kinetic during osmotic dehydration using artificial neural network and response surface methodology modelling
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In this study, the response surface methodology (RSM) was used to optimise osmo- dehydration of pumpkin cubes. Effect of different parameters including osmotic solution temperature in the range of 5 to 50° C, the immersion time from 0 to 180 min and the

Artificial Neural Network Modeling of the Effect of Cutting Conditions on Cutting Force Components during Orthogonal Turning
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Abstract Variation in cutting force components (FX, FY and FZ in three mutually perpendicular directions X, Y and Z) with cutting conditions viz. speed (v), feed (f) and depth of cut (d) during orthogonal turning of mild steel specimen using a HSS cutting tool was

Artificial Neural Network Based Pathological Voice Classification Using MFCC Features
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Abstract: The analysis of pathological voice is a challenging and an important area of research in speech processing. Acoustic voice analysis can be used to characterize the pathological voices with the aid of the speech signals recorded from the patients. This Whole body vibration produces some serious problems for human health in the long term. Low-frequency vibration, generated during vehicle operation, and transmitted to the vehicle operator, plays a major role in the development of low-back pain. Back pain is one of

Assessment of Apple Quality based on Scaled Conjugate Gradient Technique, Using Artificial Neural Network Model
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Abstract This paper describes a new machine vision system and Artificial Neural Networks based system for quality assessment of apple in real time, attending to external quality features of the fruits as size, colour symmetry, weight and external defects. The apple is

Bioimprint Replication For Cancer Research Investigations and Its Analysis Using Artificial Neural Network
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Abstract:In this paper, we have described about the obtaining of high resolution image of abnormal cells and the analysing it through artificial neural network (ANN). High resolution images can be obtained through imprinting method. High resolution imaging techniques

COMPARING THE ARTIFICIAL NEURAL NETWORK WITH PARCIAL LEAST SQUARES FOR PREDICTION OF SOIL ORGANIC CARBON AND pH AT
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SUMMARY Visible and near infrared (vis-NIR) spectroscopy is widely used to detect soil properties. The objective of this study is to evaluate the combined effect of moisture content (MC) and the modeling algorithm on prediction of soil organic carbon (SOC) and pH.

of Process Parameters for Turning Operation on CNC Lathe for ASTM A242 Type-2 Alloy Steel by Artificial Neural Network and Regression Analysis–A Review
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Abstract The purpose of this project is focused on the modelling of cutting conditions to get lowest surface roughness in turning ASTM A242 TYPE-2 ALLOYS STEEL by Artificial neural network and Regression Analysis method on the CNC lathe. The process of metal Cutting

CONTROL PERMANENT MAGNET SYNCHRONOUS MOTOR BASED ON DISCRETE WAVELET TRANSFORM AND ARTIFICIAL NEURAL NETWORK.
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ABSTRACT The paper proposes a novel method, based on wavelet decomposition, for detection and diagnosis of bearings fault in Direct Torque Control (DTC) Permanent Magnet Synchronous Motor (PMSM). In this technique the root mean square (RMS) values of the

Comparison of Articial Neural Network Algorithm for Water Quality Prediction of River Ganga
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Abstract: The development of any region depends greatly on the availability of appropriate water supplies. The quality of water can be judged based on a variety of parameters among which the most important is the temperature. In this study, Artificial Neural Network

Use of Artificial Neural Network for the Prediction of Ammonia Emission Concentration of Granulated Blast Furnace Slag Mortar.
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Abstract In this study, an artificial neural networks study was carried out to predict the quantity of ammonia gas (NH3) of Granulated Blast Furnace Slag (GBFS) cement mortar. A data set of a laboratory work, in which a total of 4 mortars were produced, was utilized in

Artificial Neural Network Approach to Predict the Abrasive Wear of AA2024-B4C Composites
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Abstract A neural network (ANN) model was developed to predict the abrasive wear behavior of AA2024 aluminum alloy matrix composites reinforced with B4C particles. Al2024- B4C powder mixtures with various reinforcement volume fractions (3–10%) and particle

The Application of an Artificial Neural Network to Support Decision Making in Edentulous Maxillary Implant Prostheses
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Cite this Article as: Leyla Sadighpour, Susan Mir Mohammad Rezaei, Mojgan Paknejad, Fatemeh Jafary and Pooya Aslani (2014), The Application of an Artificial Neural Network to Support Decision Making in Edentulous Maxillary Implant Prostheses, Journal of Research and Practice in

Predicting Student Performance Using Artificial Neural Network: in the Faculty of Engineering and Information Technology
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Abstract In this paper an Artificial Neural Network (ANN) model, for predicting the performance of a sophomore student enrolled in engineering majors in the Faculty of Engineering and Information Technology in Al-Azhar University of Gaza was developed This paper reports on the effectiveness of a back–propagation artificial neural network model that predicts the wear loss of Al–Mg alloys samples. Artificial neural networks (ANNs) have the capacity to eliminate the need for expensive and difficult experimental

Prediction and optimization of micro EDM process parameter using multiple regression andartificial neural network
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ABSTRACT The main objective of this paper is to find the optimum machining parameter for higher Material Removal Rate (MRR) in micro EDM on 316L stainless steel. The most important parameters like machining voltage, capacitance and sparkgap are considered

Simulation Modelling of Sensor less Speed Control of BLDC Motor Using Artificial Neural Network
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Abstract: This project presents an intelligent speed controller for BLDC motor, based on a single artificial neuron. Artificial neural network-based motor controllers require no offline training, which is both time consuming and requires extensive knowledge of motor

Using artificial neural network for monitoring and supporting the grid scheduler performance
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ABSTRACT Task scheduling and resource allocations are the key issues for computational grids. Distributed resources usually work at different autonomous domains with their own access and security policies that impact successful job executions across the domain

Artificial neural network modeling for surface roughness prediction in cylindrical grinding of Al-SiCp metal matrix composites and ANOVA analysis
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Metal matrix composites (MMC) having aluminium (Al) in the matrix phase and silicon carbide particles (SiCp) in reinforcement phase, ie Al-SiCp type MMC, have gained popularity in the re-cent past. In this competitive age, manufacturing industries strive to A risk assessment for urban water hazard based on RBF artificial neural network-Cloud model (RBF-ANN-Cloud) is proposed, according to the nonlinear characteristics, randomness and fuzziness in water hazard. Four assessment factors influencing urban

Cryptography Algorithms using Artificial Neural Network
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Abstract: In the recent years there has been quite a development in the field of artificial intelligence one of which has been the introduction of the artificial neural networks (ANN). The ANN can be considered as an information processing unit which to a great extent

Comparing the Univariate Modeling Techniques, Box-Jenkins and Artificial Neural Network(ANN) for Measuring of Climate Index
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Abstract The purpose of the article is to determine the most suitable technique to generate the forecast models using the data from the series of climate index in Sitiawan, Perak. This study are using univariate time series models and box-jenkin consists of Naïve with Trend

Artificial Neural Network Based Load Forecasting Using Levenberg-Marquardt Method
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Abstract:In this paper, Electrical load forecasting has been done using the feed forward neural network based on the Levenberg-Marquardt Back-Propagation (LMBP) Algorithm by incorporating the effect of weather parameters, time factors and the previous day load Determining optimum level of inventory is very important for any organisation which depends on various factors. In this research, six main factors have been considered as input parameters and the inventory level has been considered as the single output for this

An Artificial Neural Network Based Short-term Dynamic Prediction of Algae Bloom
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Abstract: This paper proposes a method of short-term prediction of algae bloom based on artificial neural network. Firstly, principal component analysis is applied to water environmental factors in algae bloom raceway ponds to get main factors that influence the

Classification of Readily Biodegradable Molecules Using Principal Component Analysis andArtificial Neural Network
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Abstract: This paper proposes a classification method in order to discriminate readily and not readily biodegradable molecules by means of principal component analysis and Artificial Neural Networks. The data used is taken from UCI machine learning repository. Each

Face Recognition Using Artificial Neural Network
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Abstract:This paper proposed a noble face recognition algorithm which integrates the principal component analysis; back propagation neural network (BPNN) and discrete cosine transform to improve the performance of face recognition. A whole face recognition system

artificial neural network (ANN) of simultaneous heat and mass transfer model during reconstitution of gari granules into thicksaste
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Abstract:Artificial neural network (ANN) based model of transient simultaneous heat and mass transfer was used for the prediction of some thermo-physical during reconstitution of gari into thick paste. Temperature changes in the paste and moisture losses were

Application of artificial neural network in fixed offshore structures
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Several types of offshore structures are in use for oil and gas exploration due to global energy demand. Fixed types (jacket and gravity) offshore structures are economically viable for shallow water regions. Period of their service life depends on various environmental

Prediction of California Bearing Ratio of Soils Using Artificial Neural Network
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Abstract: California Bearing Ratio (CBR) value is an important parameter in indexing the resistance offered by soils in the sub grade layers or in the foundation of a structure. The laboratory and field tests are extensively used for its determination to assess the strength In the present study, empirical relations have been reported for estimation of performance characteristics when EN-31 steel is machined by wire electrical discharge machining (WEDM) process using response surface methodology (RSM). The experimental plan was

Predicting the Water Level Fluctuation in an Alpine Lake Using Physically Based, Artificial Neural Network, and Time Series Forecasting Models
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Accurate prediction of water level fluctuation is important in lake management due to its significant impacts in various aspects. This study utilizes four model approaches to predict water levels in the Yuan-Yang Lake (YYL) in Taiwan: a three-dimensional hydrodynamic

Use of an Artificial Neural Network to Predict Risk Factors of Nosocomial Infection in Lung Cancer Patients
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Abstract Statistical methods to analyze and predict the related risk factors of nosocomial infection in lung cancer patients are various, but the results are inconsistent. A total of 609 patients with lung cancer were enrolled to allow factor comparison using Student's t-test or

New Supported Catalytic Binary System for the Green and Sustainable Production of Cyanogen Fumigant Optimization Using Artificial Neural Network
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Abstract: We report a new binary Cu (n)/Fe (m) supported catalytic system for a green and sustainable oxidation of hydrogen cyanide to cyanogen by hydrogen peroxide action. The binary catalytic system Cu (n)/Fe (m), wherein n has the value of I or II, m is II or III, is

Comparison of artificial neural network (ANN) and multiple regression analysis for predicting the amount of solid waste generation in a tourist and tropical area
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Abstract:Prediction of the accurate amount of solid waste is difficult work because several parameters affect it. There is a high degree of fluctuation in the prediction of amount of solid waste generation. Therefore, applying neural network as intelligent system can be a good

How to estimate and predict the expenses incurred by diabetes treatment using Artificial Neural Network (ANN)
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ABSTRACT Diabetes is considered a great health problem due to its economic importance and the fact that it is a chronic disease. The aim of this study was to determine the costs imposed on diabetic patients using Artificial Neural Network. The study data were

Artificial Neural Network Use for Design Low Pass FIR Filter a Comparison
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Abstract:The present paper investigates an approach for comparison of different types of artificial neural network used in design and analysis of low pass FIR filter. The simulated values for training and testing the neural network are obtained by designing low pass FIR

An intelligent Switching Over-voltages Estimator for Power System Restoration using Artificial Neural Network
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AbstRact. One of the most important issues in power system restoration (PSR) is switching overvoltage caused by power equipment energization. This phenomenon may damage some equipment and delay power system restoration. This paper proposes an intelligent

Identification of Conifer Species Based on Laboratory Spectroscopy and an Artificial Neural Network
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ABSTRACT Remote identification of individual tree species contributing to a forest's ecosystem is essential for the proper utilization and protection of our forest resources. In this study, we propose a novel neural network method, termed LAP-BF (which modifies the

The Kingdom of Saudi Arabia Vehicle License Plate Recognition using Learning Vector Quantization Artificial Neural Network
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ABSTRACT In the today scenario technological intelligence is a higher demand after commodity even in traffic-based systems. These intelligent systems do not only help in traffic monitoring but also in commuter safety, law enforcement and commercial applications.

Comparison of Multiple Lenear Regression Artificial Neural Network for Reservoir Operation–Case Study Of Gosikhurd Reservoir
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ABSTRACT:-In recent years, artificial intelligence techniques like Artificial Neural Networks (ANN) have arisen as an alternative to overcome some of the limitations of traditional methods. The most important advantage of ANN is that it can effectively approximate a

Artificial Neural Network Approach for Classification of Heart Disease Dataset
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Abstract Artificial Neural Networks (ANNs) play an important role in the field of medical science in solving health problems and diagnosing various diseases. To accurately diagnose the persons' disease condition it is important to use appropriate methods that

The Application of BP Artificial Neural Network in Geotechnical Engineering
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Based on MATLAB, the article apply BP artificial neural network theory on the forecasting problem of time sequence in geotechnical engineering, and find it is an effecting way to

The Competition between Regression and Artificial Neural Network Models in Earning Management Prediction
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In a world characterized by uncertainty and divergence of interests, reported earnings in financial statements have become increasingly precious information for investors, creditors, and other users of financial statements to make accurate decisions. Therefore, financial

Performance Analysis of Artificial Neural Network Based Breast Cancer Detection System
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Abstract:Breast cancer is one of the leading cancers among women in developed countries including India. Early diagnosis of the cancer allows treatment which could lead to high survival rate or avoids further clinical evaluation or breast biopsy reducing the

Wavelet Transformation and Artificial Neural Network Approach for Image Compression
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ABSTRACT In this paper a wavelet transformation and artificial neural networks (ANN) approach is proposed for the image compression. The inputs to the network are the preprocessed data of original image, while the outputs are reconstructed image data,

Comparative study of linear mixed-effects and artificial neural network models for longitudinal unbalanced growth data of Madras Red sheep.
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Sheep are efficient converters of unutilized poor quality grass and crop residues into meat and skin. Growth is a trait of economic importance in sheep as sheep rearing is an important livelihood for a large number of small and marginal farmers in India. Information about

Lung Cancer Risk Prediction Method Based on Feature Selection and Artificial Neural Network
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Abstract A method to predict the risk of lung cancer is proposed, based on two feature selection algorithms: Fisher and ReliefF, and BP Neural Networks. An appropriate quantity of risk factors was chosen for lung cancer risk prediction. The process featured two steps,

DETECTION OF NORMAL ECG AND ARRHYTHMIA USING ARTIFICIAL NEURAL NETWORK SYSTEM
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At the present we have various intelligent computing tools such as Artificial Neural Network (ANN) approaches are proving to be skilful when applied to a range of problems. In this paper we applied the ANN tool for detecting the normal and abnormal signal. Here the

Residual Capacity Estimation for Ultracapacitors in Electric Vehicles Using Artificial Neural Network
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Abstract: The energy storage system (ESS) plays a significant role in fulfilling the driving performance requirements and ensuring operational safety in an electric vehicle. Ultracapacitors (UCs) are being actively studied and used in parallel with batteries or fuel

An apt material model for drying shrinkage and specific creep of HPC using artificial neural network
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Abstract. In the present work appropriate concrete material models have been proposed to predict drying shrinkage and specific creep of High-performance concrete (HPC) using Artificial Neural Network (ANN). The ANN models are trained, tested and validated using

Speed Prediction of DC Shunt Motor by using Artificial Neural Network.
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Abstract:This paper explicitly and effectively examines the application of ANN to speed forecast of dc motors. Artificial neural networks (ANN's) is an approach to evolve an efficient model for prediction of DC motor speed, based on a set of input conditions. Neural

Artificial Neural Network based Classification of Lungs Nodule using Hybrid Features from Computerized Tomographic Images
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Abstract: An automated pulmonary nodule detection system is necessary to help radiologist to identify and detect the nodules at early stage. In this paper, a novel pulmonary nodule detection system is proposed using Artificial Neural Networks (ANN) based on hybrid

A New Algorithm For Prediction WIMAX Traffic Based On Artificial Neural Network Models
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Abstract:In this paper, WIMAX traffic forecasting system for predicting traffic time series based on the traffic data recorded (TRD) along with Artificial Neural Networks (ANN) was proposed. The data used in this work are the maximum online user, minimum online user,

A Novel Approach to Recognition of English Characters Using Artificial Neural Network
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ABTRACT: This paper presents an Artificial Neural Network (ANN) based approach for the recognition of English characters in the presence of noise. Noise has been regarded as one of the major issue that degrades the performance of character recognition system. In order

Discharge and Sediment Time Series: Uncertainty Analysis using the Maximum Likelihood Estimator and Artificial Neural Network
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Abstract Discharge and sediment in rivers have multidimensional aspects due to association of hydrology as well as hydraulics. Discharge and sediment time series data collected from field which represents the fundamental existent scenario. Mathematical exploration

Optimization of Mixed Flow Pump Impeller Blade Thickness Using Artificial Neural Network
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Abstract: The design of mixed flow pump impeller blade is complicated, to refine the blade cross-section with design parameters to exert the maximum deflection is time consuming. In this optimization work of mixed flow pump impeller blade through artificial neural network (

Voltage Sag Evaluation during Induction Motors Starting Using Artificial Neural Network
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Abstract One of the most important concerns in electrical systems is to deliver energy to the consumers with high power quality (PQ). Because of great importance of voltage sag among all PQ events, this paper presents evaluation of voltage sags caused by induction motors (

Systematic Approach for the Prediction of Ground-Level Air Pollution (around an Industrial Port) Using an Artificial Neural Network
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ABSTRACT The prediction of air pollution levels is critical to enable proper precautions to be taken before and during certain events. In this paper a rigorous method of preparing air quality data is proposed to achieve more accurate air pollution prediction models based The technical screening guide system was developed using and artificial neural network (ANN) to assist in the selection of production methods such as drilling, completion, and stimulation in a coalbed methane (CBM) reservoir. The ANN was trained with a Bayesian

Algorithm for Modeling Wire Cut Electrical Discharge Machine Parameters using Artificial Neural Network.
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Abstract-Unconventional machining process finds lot of application in aerospace and precision industries. It is preferred over other conventional methods because of the advent of composite and high strength to weight ratio materials, complex parts and also because of

Real-Time Credit-Card Fraud Detection using Artificial Neural Network Tuned by Simulated Annealing Algorithm
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Abstract:Now-a-days, Internet has become an important part of human's life, a person can shop, invest, and perform all the banking task online. Almost, all the organizations have their own website, where customer can perform all the task like shopping, they only have to

Simulation Modelling on Artificial Neural Network Based Voltage Source Inverter Fed PMSM
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Abstract: In this proposed work a control of permanent magnet synchronous motor by using an artificial neural network and the motor is supplied by the voltage source inverter. The inverter gate pulses are controlled by using an artificial neural network. In the proposed

Optimization of anaerobic baffled reactor (ABR) using artificial neural network in municipal wastewater treatment
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Abstract This study is focused on simulating and optimizing design and configuration of anaerobic baffled reactor (ABR) by means of artificial neural network (ANN). This approach is aimed to assess an efficient ABR performance in various operational conditions treating

Artificial Neural Network Travel Time Prediction Model for Buses Using Only GPS Data
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Abstract Real-time and accurate travel time information of transit vehicles is valuable as it allows passengers to plan their trips to minimize waiting times. The objective of this research was to develop a dynamic artificial neural network (ANN) model that can provide accurate Fragility functions have become widely adopted in the seismic risk assessment of highway bridges, or even a transportation network. The computational effort required for a fragility analysis of highway bridges using incremental dynamic analysis (IDA) can become

Predicting the Motion of a Robot Manipulator with Unknown Trajectories Based on an Artificial Neural Network
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Abstract Mathematically, the motion of a robot manipulator can be computed through the integration of kinematics, dynamics, and trajectories calculations. However, the calculations are complex and only can be applied if the configuration of the robot and the Abstract Recently, more and more attention has been drawn by the aircraft's maneuvering problem. This problem is very significant for improving performance of the nonlinear and unsteady modeling methods used for aircrafts at high angles of attack. In this paper,

Comparison of Artificial Neural Network and Binary Logistic Regression for Classification of Chiropteran Dietary Specializations
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Abstract Discrimination between dietary specializations of bats has been largely analyzed using multivariate techniques such as discriminant and principal component analysis. In this study, models based on an artificial neural network (Multi-layer feed forward neural

Approach of software cost estimation with hybrid of imperialist competitive and artificial neural network algorithms
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Abstract: Software is reckoned to be one of the most expensive the application tools in the computer system and accurate estimates the cost of software projects is always the most important concern of project managers. Accuracy in Software Cost Estimation (SCE)

IMPACT OF DROUGHTS ON BARLEY YIELD IN NORTH DAKOTA, USA USING MULTIPLE LINEAR REGRESSION AND ARTIFICIAL NEURAL NETWORK
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Abstract: This research investigated the effect of different drought conditions on Barley (Hordeum vulgare L.) yield in North Dakota, USA, using Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) methods. Though MLR method is widely used, the

Prediction of Road Traffic Accidents in Jordan using Artificial Neural Network (ANN)
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Abstract:Highway related accidents are considered one of the most serious problems in the modern world as traffic accidents cause serious threat to human life worldwide. Jordan, a developing country, has high and growing level of traffic accidents resulting in more than

Artificial neural network modeling of grinding of ductile cast iron using water based SiO2 nanocoolant
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ABSTRACT This paper presents optimization of the grinding progress of ductile cast iron using water-based SiO2 nanocoolant. Conventional and water-based nanocoolant grinding was performed using a precision surface grinding machine. The study is aimed to

EDGE PRESERVING IMAGE COMPRESSION AND DECOMPRESSION TECHNIQUE USINGARTIFICIAL NEURAL NETWORK
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ABSTRACT: The aim of the paper is to develop an edge preserving image compression technique using one hidden layer feed forward neural network of which the neurons are determined adaptively. Edge detection and multi-level thresholding operations are

Forecasting Rail Transport Petroleum Consumption Using an Integrated Model of Autocorrelation Functions-Artificial Neural Network
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Abstract: This paper presents the application of time-series and artificial neural network for improvement of energy forecasting in rail transport section. An integrated artificial neural network (ANN) model is presented that uses autocorrelation and partial autocorrelation

Air quality prediction using artificial neural network
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Abstract Over the last few years, the use of artificial neural networks (ANNs) has increased in many areas of engineering. Artificial neural network have been applied to many environmental engineering problems and have demonstrated some degree of success.

Facial Expression Classification Using Artificial Neural Network and K-Nearest Neighbor
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Abstract:Facial Expression is a key component in evaluating a person's feelings, intentions and characteristics. Facial Expression is an important part of human-computer interaction and has the potential to play an equal important role in humancomputer interaction. The

Modeling of Solar Radiation Using Artificial Neural Network
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The objective of this study is to develop multilayer perceptron (MLP) neural networks model for estimating daily solar radiation using limited weather variables at Champaign and Springfield stations in Illinois. The best input combinations (one, two, and three inputs) can

Artificial Neural Network Modeling and Optimization using Genetic Algorithm of Machining Process
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Abstract:In the present work an attempt is made to model and optimize the complex wire electric discharge machining (WEDM) using soft computing techniques. The purpose of this research work is to develop the artificial neural network (ANN) model to predict the cutting

Artificial Neural Network Modeling Studies to Predict the Amount of Carried Weight by Iran Khodro Transportation System
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Abstract: This paper investigates the use of three artificial neural network (ANNs) algorithms, namely, incremental back propagation algorithm (IBP), genetic algorithm (GA) and Levenberg–Marquardt algorithm (LM) for predicting Carried weight, with an automobile

Fingerprint Based Gender Classification Using Discrete Wavelet Transform Artificial Neural Network
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Abstract:This research implements a novel method of gender classification using fingerprints. Two methods are combined for gender classifications. The first method is the wavelet transformation employed to extract fingerprint characteristics by doing

Fast Efficient Artificial Neural Network for Handwritten Digit Recognition
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Abstract:-Handwriting recognition is having high demand in commercial academics. In recent years lots of good work has been done on hand written digit recognition to improve accuracy. Handwritten digit recognition system needs larger dataset and long training time

An Accurate Heave Signal Prediction Using Artificial Neural Network
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Abstract An accurate heave modeling is required for several applications, including hydrographic surveying. This paper proposes an adaptive heave signal modeling, which uses a neural network-based modelling. A recurrent neural network and three-layer feed

Evaluating the Performance of Artificial Neural Network Model in Downscaling Daily Temperature, Precipitation and Wind Speed Parameters
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ABSTRACT: Numerous studies yet have been carried out on downscaling of the large-scale climate data using both dynamical and statistical methods to investigate the hydrological and meteorological impacts of climate change on different parts of the world. This study

Artificial neural network based equation to estimate head loss along drip irrigation laterals
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SUMMARY: This work proposes an equation based on Artificial Neural Network (ANN) to estimate head loss along emitting pipes accounting for cylindrical in-line emitters. The following input variables were used to fit the model: total head loss between two

Application of Artificial Neural Network for Optimization of Cold Chamber Aluminium Die Casting
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Abstract--In the present paper an optimization of process parameters of a cold chamber aluminium die casting operation is discussed. The quality problem encountered during the manufacturing of a die casted component was porosity and the various potential factors

Artificial Neural Network Modeling for the Prediction of Surface Roughness in ECM
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Abstract: In the present study, artificial neural network (ANN) model is developed to predict surface roughness in electrochemical machining (ECM) of EN 31 tool steel. In the development of predictive models, machining parameters viz., electrolyte concentration,

AN ARTIFICIAL NEURAL NETWORK CLASSIFICATION APPROACH FOR IMPROVING ACCURACY OF CUSTOMER IDENTIFICATION IN E-COMMERCE
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ABSTRACT With the advancesin Web-based oriented technologies, experts are able to capture user activities on the Web. Users' Web browsing behavior is used for user identification. Identifying users during their activities is extremely important in electronic

Evaluation of Winter Maintenance Chemicals and Crashes with an Artificial Neural Network
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The objective of this study was to investigate and evaluate the effects of winter maintenance chemicals on road safety. To this end, a winter chemical usage model was developed. A methodology combining artificial neural network (ANN) methods and sensitivity analysis is

Artificial Neural Network Based Approach for Identification of Operating System Processes
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Abstract A computer system can be secured by using various methods like firewalls, anti- virus tools, network security tools, malware removal tools, monitoring tools etc. These tools and applications are being by most of the computer users. These computer security tools

Implementation of Artificial Neural Network for Short Term Load Forecasting
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Abstract:In this paper an attempt has been made to solve nonlinear and complex problem of load forecasting using Artificial Neural Network (ANN). ANN are able to learn weather variables and the relationship among past, current and future load data. The standard

Optimization of wheat grain yield by artificial neural network
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ABSTRACT: Wheat is more important than other grain crops. Maximum grain yield can be determined by several components that reflect positive or negative effects. The objective of this article is optimization of wheat grain yield by artificial neural network. Field experiment

Analysis of Building Electrical Lighting Energy Saving Based on Artificial Neural Network
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Abstract:According to the actual situation in an office building electrical lighting in Zhengzhou area, this study gives a solution of energy saving, and energy saving calculation, establishes an evaluation model of artificial neural network based on the lighting energy

Implementation of Pid Trained Artificial Neural Network Controller for Different DC Motor Drive
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Abstract: The Speed of the DC motors is controlled by Hybrid PID-ANN controller. The Hybrid PID-ANN (Artificial Neural Network) controller is designed and tested for different types of DC motors like DC separately excited motor and DC series motor. The motor is

Integrated Model of DNA Sequence Numerical Representation and Artificial Neural Networkfor Human Donor and Acceptor Sites Prediction
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Abstract:Human Genome Project has led to a huge inflow of genomic data. After the completion of human genome sequencing, more and more effort is being put into identification of splicing sites of exons and introns (donor and acceptor sites). These invite

Maintainability Prediction from Project Metrics Data Analysis Using Artificial Neural Network: An Interdisciplinary Study
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Abstract: Software maintainability is an important aspect for all software engineering paradigms. Considering the maintainability a factor influencing the software quality and reliability, the estimation can help to improve overall software quality. Maintainability is an

URBAN GROWTH MODELING USING AN ARTIFICIAL NEURAL NETWORK A CASE STUDY OF SANANDAJ CITY, IRAN.
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ABSTRACT: Land use activity is a major issue and challenge for town and country planners. Modelling and managing urban growth is a complex problem. Cities are now recognized as complex, non-linear and dynamic process systems. The design of a system that can

Automatic Defect Detection Algorithm for Woven Fabric using Artificial Neural NetworkTechniques
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ABSTRACT: Textile industry is one of the main sources of revenue-generated industry. The price of fabrics is severely affected by the defects of fabrics that represent a major threat to the textile industry. A very small percentage of defects are detected by the manual

Flame Shape Prediction with Artificial Neural Network
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Abstract A flame shape descriptor based on coordinates of edge of a flame is proposed. Artificial Neural Network is used to predict flame image edges. A flame with constant x- coordinate is used in the present study. Y-coordinates of flame edge are predicted using

Artificial Neural Network approach to Fabric Defect Identification system.
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Abstract Textile industry is one of the revenue generating industry to India. In textile industry the detection of defect in fabric is a major threat. Woven fabrics produced by weaving. Weaving is a process of interlacing two distinct yarns namely warps and weft. A fabric fault

Artificial Neural Network: A Tool for Diagnosing Osteoporosis
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Abstract The most important concern in the medical domain is to consider the interpretation of data and perform accurate diagnosis. To improve diagnostic process and avoid misdiagnosis, many e-Health systems use artificial intelligence method and especially

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