Artificial Neural Network IEEE PAPER 2017
Comparison ofArtificial Neural Networkand Multiple Linear Regression Models for the Prediction of Body Mass Index
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Abstract Body Mass Index (BMI) is a simple measurement that uses a weight-to-height ratio and is used to classify adults who are underweight, overweight or obese. A higher BMI is determined to be frequently associated with the increased risk of cardiovascular hearth
A Hybrid Forecasting Method Based On Exponential Smoothing and Multiplicative Neuron ModelArtificial Neural Network
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Abstract Holt exponential smoothing method is an effective method for forecasting of non seasonal time series. In Holt method, moving average operator with exponential decay weights is used. Multiplicative neuron modelartificial neural networkis a non-linear time
AnArtificial Neural Networkapproach to predicting electrostatic separation performance for food waste recovery
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Abstract This study presents the empirical exploration of food waste recovery throughout the electrostatic separation process. In addition, the paper discusses the potential ofartificial neural network(ANN) in predicting the responses. A five-level three-factor Taguchi
TRANSFORMER PROTECTION USINGARTIFICIAL NEURAL NETWORK
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Abstract This paper gives idea about use ofartificial neural networkto the protection of power transformer. The high pointed demand includes the requirements of dependability associated with no false tripping and operating speed with short fault detection and clearing
Brain Cancer classification Based on Features andArtificial Neural Network
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Abstract: MRI (Magnetic resonance Imaging) brain tumor images Classification is a difficult task due to the variance and complexity of tumors. This paper proposed techniques to classify the MR human brain images. The proposed classification technique consists of three Prediction of Number of Passengers in Public Transportation by UsingArtificial Neural NetworkMethod
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Abstract In order to organize activities efficiently in the public transportation, there are some factors such as bus lines, stops, distances, traffic conditions etc. Before making the necessary planning and scheduling activities, it is important to estimate the demand for the
Assessment of Total Dissolved Solid Concentration in Groundwater of Nadia District, West Bengal, India usingArtificial Neural Network
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Abstract: An attempt was made to predict the total dissolved solid (TDS) concentration of groundwater for Nadia district, West Bengal usingartificial neural networkapproach. The sole aim of the study was simulating TDS in groundwater as one of the major indicators of
AnArtificial Neural Networkalgorithm to solve third-order Emden-Fowler type problems
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Abstract In this article we suggest, the hybrid algorithm based on Bessel polynomials and Artificial Neural Network(BeNN) to solve non-linear Emden-Fowler type of differential equations. The problems with singular point at x= 0 which have the second order of initial Vortex Shedding Frequency Estimation of a Circular Cylinder with Splitter Plate at Incidence UsingArtificial Neural Network
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Abstract Bluff bodies such as a circular and square cylinder encountering in many engineering applications has significant disadvantages like vortex induced vibration that can be lead to resonance. Therefore, prediction of vortex shedding frequency has vital important Aerodynamic Force Estimation of A NACA 0015 Airfoil with DBD Plasma Actuator UsingArtificial Neural Network
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Abstract Flow control with dielectric barrier discharge (DBD) has significant importance because of its simple structure, rapid responds and light weight. In the laboratory research, DBD plasma actuator producing ozone and required high voltage pose a threat for the
PREDICTION OF PUNCHING SHEAR CAPACITY OF RC FLAT SLABS USINGARTIFICIAL NEURAL NETWORK
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ABSTRACT Punching shear of flat slabs is a local, brittle failure that may occur before the more favourable ductile flexural failure. This study develops anartificial neural network (ANN) modelling for the prediction of punching shear strength of flat slabs using 281 test
Identification of potentially undelivered packages with anartificial neural networkmethod
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Abstract In this paper we propose anartificial neural networkmethod to determine whether an internationally shipped package is at risk of ending up lost in post before reaching its intended recipient. Thenetworkuses several features of transactions with customers as
Electrical Characterization of a Photovoltaic Module ThroughArtificial Neural Network : A Review
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Abstract: The aim of this paper is to present a review of IV characteristics of photovoltaic module usingartificial neural network(ANN). The ANN approach has found to be the efficient tool over complex non-linear mathematical equations and complicated models for
Artificial Neural Networkmodelling for pressure drop estimation of oil-water flow for various pipe diameters
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Abstract The flow of two immiscible liquids in pipeline occurs many times in chemical industries. Oil-water mixture is dispersion and estimation of pressure gradient for flow through pipeline using empirical equation is tedious and less accurate. The present work is
Superensembling ofArtificial Neural NetworkModels for Investigating The Effect of Polar Sea Ice on Sea Surface Temperature in Indian Ocean Region
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Abstract: There are two broad sources of errors when prediction of any atmospheric parameter is made by dynamical models-one due to errors in model initializations and two due to limited understanding of the physical phenomenon at hand. The error introduced by
Artificial Neural NetworkModeling of NixMnxOx based Thermistor for Predicative Synthesis and Characterization
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As foremost sensors of ambient conditions, temperature sensors are regarded as the most vital ones in wide-ranging applications touching the societal life. Amongst the temperature sensors, NTC thermistors have captured their unique place due to the favorable metrics
Application of Taguchi OA array andArtificial Neural Networkfor Optimizing and Modeling of Drilling Cutting Parameters
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Abstract This paper consists of two phases, in first phase experiments have been conducted with the use of Taguchi FFE (Fractional Factorial experimentation) to find optimal cutting process parameters spindle speed, feed rate and drill diameter with the objective of
RECOGNITION OF SILVERLEAF WHITEFLY AND WESTERN FLOWER THRIPS VIA IMAGE PROCESSING ANDARTIFICIAL NEURAL NETWORK
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Abstract-IPM (Integrated Pest Management) is used to minimize or reduce the use of chemicals in greenhouse agriculture. IPM is basically depends upon early detection and continuous monitoring of pest populations which is very critical or time consuming task as it
Artificial Neural NetworkBased Trend Analysis and Forecasting Model for Course Selection
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Abstract Selection of the proper higher educational courses is absolutely necessary for the prospective students. Selecting appropriate courses are really cumbersome job for the students who are having less information about present trend of education relating to get
Water Quality Evaluation Using Back PropagationArtificial Neural NetworkBased on Self-Adaptive Particle Swarm Optimization Algorithm and Chaos Theory
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Abstract To overcome the shortcomings of the traditional methods of water quality evaluation, in this paper, a novel model combines particle swarm optimization (PSO), chaos theory, self-adaptive strategy and back propagationartificial neural network(BP ANN) that
Coin Recognition System usingArtificial Neural Networkon Static Image Dataset
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Abstract: Coins are frequently used in everyday life at various places like in banks, grocery stores, supermarkets, automated weighing machines, vending machines etc. So, there is a basic need to automate the counting and sorting of coins. However, currently available
QSAR studies of breast carcinoma usingArtificial neural network , Bayesian classifier and Multiple linear regression
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Abstract-Breast cancer is a disease that affects millions. It starts as a tumor but end up spreading all over the body. It uses nutrition of body for its own growth and there is no regulatory mechanism for its growth. Breast cancer has no cure once it progresses to an
Predicting strength of SCC usingartificial neural networkand multivariable regression analysis
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Abstract. In the present study anArtificial Neural Network(ANN) was used to predict the compressive strength of selfcompacting concrete. The data developed experimentally for self-compacting concrete and the data sets of a total of 99 concrete samples were used in
Dynamic Adsorption Modelling of P-nitrophenol in Aquous Solution UsingArtificial Neural Network
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Abstract This work aims at developing anartificial neural networkto describe the dynamic adsorption of p-nitrophenol from an aqueous solution using an NDA-100 resin as adsorbent under different conditions. Nine neurons were used in the input layer corresponding to the
Shortcomings of CurrentArtificialNodalNeural NetworkModels
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Published: February 15, 2017 The usefulness of small-networks to model large-networks is limited in biological systems and synaptic studies give little insight into conduction in more highly evolved brain- neural -networks where axon conduction is diverse and seemingly
An Optimization Study on Solid Lipid Nanoparticles UsingArtificial Neural Network
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SUMMARY. Common use of supportive programs in finding the best in R D studies provides positive results and thus ensures benefits to companies in terms of cost and time. The aim of this work was to develop, evaluate and optimize solid lipid nanoparticles (SLNs)
Blade Fault Diagnosis usingArtificial Neural Network
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Abstract Fourier and wavelet analysis of vibration signals are the two most commonly used techniques for blade faults diagnosis in turbo-machinery. However, blade faults diagnosis based on visual comparison of vibration spectrum and wavelet maps are very subjective as
Anticipation of Software Development Effort usingArtificial Neural Networkfor NASA Data Sets
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Abstract: Failures of software are mainly due to the faulty project management practices, which include effort estimation. Continuous changing outlines of software development technology make effort estimation more challenging. Several methods are available in order
Cursive Handwriting Recognition System Using Feature Extraction andArtificial Neural Network
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Abstract Cursive Handwriting recognition is a very challenging area due to the unique styles of writing from one person to another. Various researches have been conducted in this field since around four decades. In this paper, an offline cursive writing character
Review onArtificial Neural Networkusing Back propagation Algorithm
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Abstract--- NeuralNetworks (NN) are significant tool used for classification and clustering of data. This paper presents an attempt to build machine that will imitate brain activities and will be able to learn. NN usually learns by illustration. If this type ofnetworkis supplied with
PREDICTION OF GREENHOUSE MICRO-CLIMATE USINGARTIFICIAL NEURAL NETWORK
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Abstract. The aim of this study is to develop anArtificial Neural Network(ANN) model for prediction of one day ahead mean air temperature and relative humidity of greenhouse located in the sub-humid sub-tropical regions of India. The adequacy of back propagation
Artificial neural networkmodeling of contact electrical resistance profiles for detection of rock wall joint behavior
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ABSTRACT: The contact area and stress distribution along rock wall joints, play an important role in the behavior and mechanical properties of the rock mass in mining and tunneling. Although properties of rock fractures such as aperture, roughness, filling, contact area, and
Application ofartificial neural networkfor estimating the qualitative characteristics of cantaloupe melon and comparison with the regression model
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ABSTRACT: In this paper, the quality characteristics of melon was estimated by using color parameters andneuralnetworks for three fertilizing stages (no fertilizer, fertilizing 5 and 10 ton/ha). For this purpose, chemical parameters including fructose, glucose and sucrose, and
OF MASS CONCRETE AT CONSTRUCTION PHASE OF CONCRETE DAMS USING GENETIC PROGRAMMING ANDARTIFICIAL NEURAL NETWORK
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Effective decision on temperature control plan can be taken in advance by designer and contractor, understanding the influence of the parameters that affects the temperature development of concrete at construction phase of massive concrete structures. This study is
Prediction of First Order Focusing Properties of Ideal Hemispherical Deflector Analyzer UsingArtificial Neural Network
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In many branches of collision physics, it is required to analyze the energies of the collected electrons emanating from the interaction region. As a solution, hemispherical deflector analyzers (HDAs) are designed as vital devices to disperse electrons depending on their Criteria for improving the traditionalartificial neural networkmethodology applied to predict COP for a heat transformer
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All rights reserved. Desalination and Water Treatment www.deswater.com doi:10.5004/dwt.
2017.20357 Criteria for improving the traditionalartificialneuralnetworkmethodology applied
to predict COP for a heat transformer E. Martínez-Martíneza, BA Escobedo-Trujilloa, D. Coloradob,*,
SOLAR ENERGY POTENTIAL MAPPING OF INDIA USINGARTIFICIAL NEURAL NETWORK
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Abstract-The initial objective of the study is to forecast the solar irradiation potential of India usingartificial neuralnetworks (ANNs) method. Mapping the predicted potential using GIS software on monthly basis is the second objective. The data was obtained from satellite
Online Composition Prediction of a Debutanizer Column UsingArtificial Neural Network
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ABSTRACT: The current method for composition measurement of an industrial distillation column includes offline method, which is slow, tedious and could lead to inaccurate results. Among advantages of using online composition designed are to overcome the long time
Artificial Neural NetworkBased Development of Pavement Depreciation Models for Urban Roads
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ABSTRACT A productive road transportation framework is of fundamental significance to economy of any country. Road transport in India, involves a predominant position in the general transportation arrangement of the nation because of its favourable circumstances as
Artificial Neural Network -Based Classification System for Lung Nodules on Computed Tomography Scans
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Abstract: The paper describes aneural - network -based system for the computer aided detection of lung nodules in chest radiograms. In recent years the image processing mechanisms are used widely in several medical areas for improving earlier detection and
Drift Avoidance Mechanism in Maximum Power Point Tracking UsingArtificial Neural Network
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As the requirement of Photovoltaic System escalates since it uses the solar energy which is one of the renewable energies for the electrical energy its production has an enormous potential. The development of PV system is very rapid as compared to its counterparts of the
Improving estimation accuracy of metallurgical performance of industrial flotation process by using hybrid genetic algorithmartificial neural network(GA-ANN)
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Abstract: In this study, a back propagation feed forwardneural network , with two hidden layers (10: 10: 10: 4), was applied to predict Cu grade and recovery in industrial flotation plant based on pH, chemical reagents dosage, size percentage of feed passing 75 µm,
MODELLING OF CARBONATION OF REINFORCED CONCRETE STRUCTURES IN INTRAMUROS, MANILA USINGARTIFICIAL NEURAL NETWORK
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ABSTRACT: Corrosion is a perennial problem in reinforced concrete structures, and is a serious concern due to the deterioration that it causes to reinforced concrete members. Though regarded as having a minor influence to corrosion compared to chloride-induced
AnArtificial Neural NetworkClassifier for the Prediction of Protein Structural Classes
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Abstract As there are quite a few difficulties for us to predict a protein structural class directly from its primary sequence, the protein structural prediction based on the predicted secondary structure will undoubtedly be the first choice we would like to take. Protein Transfer Improvement in Automotive Brake Disks via Shape Optimization of Cooling Vanes Using Improved TPSO Algorithm Coupled withArtificial Neural Network
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Abstract One important safety issue in automotive industry is the efficient cooling of brake system. This research work aims to introduce an optimized cooling vane geometry to enhance heat removal performance of ventilated brake disks. The novel idea of using airfoil
Artificial Neural Networkand Inverse Solution Method for Assisted History Matching of a Reservoir Model
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Abstract A typical inverse problem encountered in petroleum industries is referred to as history matching. In the early days, history matching was undertaken by manually changing sensitive reservoir parameters until a reasonable match between observed and simulated
Artificial Neural NetworkBased Voltage Stability Analysis of Radial Distribution System
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Abstract Voltage instability is a big problem in modern power system. Increasing load demand on Distribution system gives lower voltage. This is the reason of voltage instability in Distribution system. So, analysis of voltage stability is very important. Different techniques
DESIGN A NOVEL SELF ADAPTING SIEM TECHNIQUE USINGARTIFICIAL NEURAL NETWORK
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Information Management (SIM) and Security Event Management (SEM), where SIM collects accounting and audits logs at large volume and SEM analysis those logs, picks out the important behaviours and flagging them for review via alerts. It is focused on the need of
Anomalous Behaviour Detection in Crowded Environments Using ClassifiersArtificial Neural Networkand Support Vector Machine
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Abstract: Our proposed method focuses to detect and localize anomalous behavior in videos of the crowded area means different scenario from the dominant pattern. Proposed method consist motion and appearance information, therefore, different kinds of anomalies can be
DOUBLE CIRCUIT TRANSMISSION LINE PROTECTION USING LINE TRAP ARTIFICIAL NEURAL NETWORKMATLAB APPROACH
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Abstract-The protection of double circuit transmission lines could be a difficult task. This paper presents a protection technique supported the high-frequency transients generated by the fault to hide nearly the entire length of double circuit line. For this purpose, befittingly
AUDIO CLASSIFICATION USINGARTIFICIAL NEURAL NETWORKWITH DENOISING ALGORITHM (INTELLIGENT MUSIC PLAYER)
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Abstract-Customizable software application are in trend of the state of art technologies. This project work integrates a audio filter training algorithm into a windows platform music player and embeds into a single software application. A Matlab based audio filter will be developed
An application of Kalman Filtering andArtificial Neural Networkwith K-NN Position Detection Technique
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Abstract RFID technology is one of the important technologies to determine the object locations. Distances are calculated with respect to calibration curves of RSSI amplitudes. The aim of this study is to determine the 2D position of mobile objects in the indoor
Time Series andArtificial Neural NetworkForecasting of the Electricity Demand for a Private Electricity Distribution Company
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Abstract Electricity is an energy source that can be transported from the region where it is produced by transmission and distribution networks, whereas it cannot be stored. For this reason, estimation of electricity energy demand is very important in terms of operational and
Prediction of Co (II) and Ni (II) ions removal from wastewater usingartificial neural networkand multiple regression models
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Abstract: In this research, carboxymethyl chitosan-bounded Fe3O4 nanoparticles were synthesized and used for removal of Co (II) and Ni (II) ion metals from wastewater. The capability of magnetic nanoparticles for metal ions removal was investigated under different
ARTIFICIAL NEURAL NETWORKBASED LOAD FORECASTING
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Abstract: A large number of researchers have advised theartificial neural networktechnique for forecasting of load. This paper studies the technique for load forecasting using two training algorithms and comparing their applicability and efficiency. For this purpose, a
Age Estimation Using ClassifiersArtificial Neural Networkand Support Vector Machine Based on Face Images
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Abstract: The most prominent challenge in the facial age estimation is a lack of sufficient and incomplete training data. Aging is slower and gradual process, therefore, faces near close ages look quite similar this can allow us to utilize the face images at neighbouring ages with
An Improved Collaborative Algorithm withArtificial Neural Networkin Multidisciplinary Design Optimization of AUV
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Abstract: Multidisciplinary Design Optimization (MDO) is the most active field in the design of current complex system engineering, which is possessed with such two difficulties as subsystem information exchange and analytical and computational complexity of systems.
Convergence Optimization of BackpropagationArtificial Neural NetworkUsed for Dichotomous Classification of Intrusion Detection Dataset.
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Abstract: There are distinguished two categories of intrusion detection approaches utilizing machine learning according to type of input data. The first one representsnetworkintrusion detection techniques which consider only data captured innetworktraffic. The second one
Calculating Student Performance of Jagannath University UsingArtificial Neural Network
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ABSTRACT: In this paper anArtificial Neural Network(ANN) display, for estimating the execution of a sophomore understudy selected in designing majors in the Faculty of Science in Jagannath University of Bangladesh was created and tried. Various variables that may
-48 CATALYST SYNTHESIS CONDITIONS AND PERFORMANCES IN THE STEAM REFORMING PROCESS THROUGHARTIFICIAL NEURAL NETWORK
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Hydrogen continues to be an important energy carrier for the future due to is low impact on the environment and its potential as a fuel for more efficient energy conversion. In this way fuel cell oriented hydrogen production from ethanol reforming has attracted great interest.
Artificial Neural NetworkModel for Predicting Lung Cancer Survival
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Abstract The object of our present study is to develop a piecewise constant hazard model by using anArtificial Neural Network(ANN) to capture the complex shapes of the hazard functions, which cannot be achieved with conventional survival analysis models like Cox
APPLICATION OF DISCRETE HOPFIELD ALGORTIHM TYPEARTIFICIAL NEURAL NETWORKFOR PATTERN RECOGNITION OF EYES IRIS
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ABSTRACTArtificial Neural Network(ANN) was used to identify the characteristics of the input slice is represented by the binary value. Input from these characteristics trained by discrete Hopfieldneural networkalgorithm for therecognizedor NOT. Eyes iris can be
Batik Classification withArtificial Neural NetworkBased on Texture-Shape Feature of Main Ornament
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Abstract Batik is a textile with motifs of Indonesian culture which has been recognized by UNESCO as world cultural heritage. Batik has many motifs which are classified in various classes of batik. This study aims to combine the features of texture and the feature of shapes
Faults detection in PMSM drive usingArtificial Neural Network
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Abstract. In this paper, simulation research results of PMSM drive with open phase fault detection are presented. Proposed fault detection system is implemented using twoartificial neuralnetworks. One of them isneuralmodel of healthy PMSM and another one generates
ARTIFICIAL NEURAL NETWORK(ANN) MODELING OF COD REDUCTION FROM LANDFILL LEACHATE BY THE ULTRASONIC PROCESS
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In the study, the use of anartificial neural network(ANN) has been applied for the prediction of COD removal from landfill leachate by the ultrasonic process. The configuration of the backpropagationneural networkgiving the lowest mean square error (MSE) was a three-
EVALUATION OF CHLORIDE USING EMBEDDED SYSTEM BASED ANALYSER ANDARTIFICIAL NEURAL NETWORKCOMPUTATION IN BIOLOGICAL AND
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R VASUMATHI, P Neelamegam - 2017 - 14.139.186.108 1.1 Chloride 1 1.1. 1 Pivotal Roles of Chloride in human body 2 1.1. 2 Sources of Chloride 2 1.2 Roles of Chloride in biological samples 3 1.3 Roles of Chloride in environmental samples 4 1.3. 1 Soil Chloride importance in plants 4 1.3. 2 Yield and quality response of
Rapid Particle Size Analysis of Suspensions Based on Video Technology andArtificial Neural Networkwith Additional Training During Operation
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Abstract The original system for rapid determination of suspensions particle size distribution is proposed. The system is based on video technology andartificial neural network(ANN) that has training procedure not only in time of initial calibration but during operation too. The
AnArtificial Neural Networkfor the Design of Concrete Mixes that Satisfies Green Construction for Radiation Safety Criteria
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Abstract: Green construction is a process to construct buildings with minimum harmful effects on human health and environment. One of the main strategies to achieve green buildings is to improve air quality. This can be fulfilled by choosing building materials with low natural
Calibration of Osteoporosis UsingArtificial Neural Network
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Abstract: Osteoporosis is a very common Bone disease that leads to Fracture. Electromyography (EMG) is a major diagnostic tool used for analyzing the health of muscles and the nerve cells that control them (motor neurons). Motor neurons transmit electrical
ARTIFICIAL NEURAL NETWORKBASED ULTRASONIC SENSOR SYSTEM FOR DETECTION OF ADULTERATION IN EDIBLE OIL
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Abstract This paper presents the design, development and experimental validation of an ultrasonic sensor system for the detection of adulteration in edible oil. Variation of ultrasonic wave propagation characteristics like attenuation coefficient, reflection coefficient and
Comparing the Efficiency ofArtificial Neural Networkand Gene Expression Programming in Predicting Coronary Artery Disease
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Abstract Background: Angiography, as the gold standard for the diagnosis of coronary artery disease, has made an attempt to predict coronary artery disease by comparing the efficiency of gene expression programming, as a new data mining technique, andartificial neural
SWARM OPTIMIZATION FOR OPTIMIZING LEARNING PARAMETERS OF FUNCTION FITTINGARTIFICIAL NEURAL NETWORKFOR SPEECH SIGNAL
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ABSTRACT Speech signals are effected by noise generated by various sources of interferences. Removing noise from speech signals can be regarded as an active research area in signal processing. Thus, we need powerful methods in this area. Therefore, Function
Optimization of Biodiesel Production from Mixed Jatropha curcas Ceiba pentandra UsingArtificial Neural Network -Genetic Algorithm: Evaluation of Reaction
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Biodiesel production from non-edible vegetable oil is one effective way to anticipate the problems associated with fuel crisis and environmental issues. In this study,artificial neural networkand genetic algorithm based Box Behnken experimental design used to optimize
AnArtificial Neural NetworkBased Real-Time Optimal Reactive Power Flow for Improving Operation Efficiency
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Abstract This paper presents a developed controller for a Static Var Compensator (SVC) System by using anArtificial NeuralNetworks (ANNs) for compensating unbalanced fluctuating loads and enhancing the efficiency of operating the distributionnetworknamely; Operating and maintenance cost in seawater reverse osmosis desalination plants.Artificial neural networkbased model
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ABSTRACT The implementation of seawater reverse osmosis (SWRO) desalination plants was key to ensure the fresh water supply in arid and coastal regions. The high operating and maintenance (O M) cost in these plants are an impediment. In this paper,the O M cost of twelve SWRO desalination
LOCATION OF VOLTAGE SAG SOURCE BY USINGARTIFICIAL NEURAL NETWORK
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Power quality (PQ) is a major concern for number of electrical equipment such as sophisticated electronics equipment, high efficiency variable speed drive (VSD) and power electronic controller. The most common power quality event is the voltage sag. The objective
Illumination Normalization for Fingerprint Recognition using Enhanced Multi-scale Low Rank+ Sparse Decomposition withArtificial Neural Network
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Abstract Image recognition are very sensitive to light conditions. In order to obtain the best possible performance it is desired to remove illumination variations from images. Low rank modeling are often used to model biometrical images as faces, fingers etc. Low rank+
Predicting Honey Production using Data Mining andArtificial Neural NetworkAlgorithms in Apiculture
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This survey was conducted on all the 85 beekeeping farms collected with census study method in Igdir province of Turkey with the purpose of determining some factors influencing average honey yield (AHY) per beehive in the year 2014. For this purpose, predictive Forecasting TRY/USD Exchange Rate with VariousArtificial Neural NetworkModels
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Abstract-Exchange rate forecasting is one of the most common subjects among the forecasting problem field. Researchers and academicians from many different disciplines proposed various approaches for better exchange rate forecasting. In recent years, for
A Review of Heuristic Global Optimization BasedArtificial Neural NetworkTraining Approahes
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Artificial NeuralNetworks have earned popularity in recent years because of their ability to approximate nonlinear functions. Training aneural networkinvolves minimizing the mean square error between the target andnetworkoutput. The error surface is nonconvex and
ARTIFICIAL NEURAL NETWORKPERMEABILITY MODELING OF SOIL BLENDED WITH FLY ASH
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ABSTRACT: The determination of the permeability properties of soil is important in designing civil engineering projects where the flow of water through soil is a concern. ASTM D2434 Standard Test Method for Permeability of Granular Soils (Constant HeadFalling
WIND TURBINE FAULT DIAGNOSIS THROUGH TEMPERATURE ANALYSIS: ANARTIFICIAL NEURAL NETWORKAPPROACH
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Abstract Wind turbines undergo dynamic loads along all the phases of transformation of wind kinetic energy into power output to be fed into the grid. Gearbox breakdowns are one of the most common and most severe causes of energy losses and it is therefore crucial to
Automatic cerebral magnetic resonance image segmentation usingartificial neural network
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Imaging (MRI) is used in various fields of study and diagnosis of brains structures and tissues. Image zoning is one of the fundamental phases in vision systems of machine. Due to adverse factors such as noise, low contrast and heterogeneity intensity of MRI images and
CONNECTING SOCIAL MEDIA TO ECOMMERCE USING MICROBLOGGING ANDARTIFICIAL NEURAL NETWORK
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Abstract: To develop an enhanced web application, using web services for interconnecting three various servers like, socialnetwork , E-commerce application and news channels. By UsingArtificial Neural Network(ANN) and Text categorization the recommended products
NovelArtificial Neural NetworkPath Loss Propagation Models for Wireless Communications
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Abstract Different propagation models proposed for different scenarios but a unique model did not exist, which will be suitable for all types of environments.Artificial Neural Network model is developed by training it to the entire expected domain. It calculates the path loss.
An Algorithm to Predict Accurate Output Power of a Glass-Glass (Semitransparent) Solar Thermal Module UsingArtificial Neural Network
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Abstract This paper presents an algorithm to predict output power or performance parameters ie, open circuit voltage and short circuit current of a glass-glass (GG) ie, semitransparentsolar thermal module very close to the experimental values. The predicted
ANARTIFICIAL NEURAL NETWORKAPPROACH TO PROJECTILE MOTION WITH AIR FRICTION
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Abstract Three dimensional projectile motion of a particle with air friction is investigated. The algebraic equations defining the relations among the coordinates, initial velocity and angle of inclination are derived. For a given target point in the space, the corresponding
Comparative Analysis between Conventional PI, Fuzzy Logic andArtificial Neural NetworkBased Speed Controllers of Induction Motor with Considering Core
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Abstract: Most of the controllers of IM (induction motor) for industrial applications have been designed based on PI controller without consideration of CL (core loss) and SLL (stray load loss). To get the precise performances of torque as well as rotor speed and flux, the above
A COMPARATIVE STUDY ON DIFFERENT PROPAGATIONS FOR DEVELOPMENT OFARTIFICIAL NEURAL NETWORKMODEL TO STUDY THE
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Abstract In this research work, the present study is emphasized on the behavior of Composite Steel Tubes filled with concrete under monotonic loading. The prime factors considered to get ultimate axial load and corresponding axial shortening under axial
ANARTIFICIAL NEURAL NETWORKMODEL FOR MONTHLY PRECIPITATION FORECASTING INHOMS STATION, SYRIA
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ABSTRACT Background: One of the major problems in water resources management is the precipitation forecasting. Given the effect of precipitation on water resources, it is found that a more accurate prediction of precipitation would enable more efficient utilization of water
Devanagari Character Recognition UsingArtificial Neural Network
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Abstract Devanagari is one of the Ancient Scripts that is in regular use in India as well as Nepal. Devanagari is currently used by more than 120 languages including Hindi, Nepali, Marathi, and Pali which defines the prevalence and the domination of Devanagari [1].
ApplyingArtificial Neural Networkto Deep Learning and Prescriptive Analysis in Telemedicine Systems using Microsoft Azure Machine Learning
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Abstract The study aims to establish a deep learning and predictive model in the semantic TCM telemedicine system usingArtificial Neural NetworkMicrosoft Azure Machine Learning. In Chinese Medicine diagnosis, four examination methods: Questioning/history taking,
ESTIMATION OF REFERENCE EVAPOTRANSPIRATION BASED ON ONLY TEMPERATURE DATA USINGARTIFICIAL NEURAL NETWORK
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ABSTRACT Background: Evapotranspiration is an important component of the hydrological cycle, and the accurate estimation of this parameter is very important for many water resources applications. Objectives: The objective of this study was to estimate monthly
MODELLING OF FUNCTIONAL PARAMETER OF EARTHEN DAM BREACH BYARTIFICIAL NEURAL NETWORKAND RANDOM FOREST
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ABSTRACT The paper investigates the modelling of functional parameter of earthen dam breach. The output values of breach depth of embankment dam were calculated by with the help ofartificial neural network(ANN) and Random Forest (RF) modelling techniques. Two
Symposium on NDT in Aerospace, November 3-5, 2016 Lamb Wave Based Damage Detection using Orthogonal Matching Pursuit andArtificial Neural Network
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Abstract This work presents a damage detection technique which involves three steps, namely, data generation, signal processing or sparse signal approximation, and classification using machine learning algorithm ieArtificial Neural Network(ANN). Lamb-
Prediction of Ultimate Load Capacity of Tapered Members UsingArtificial Neural Network
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Abstract Members with non-prismatic geometry are commonly used in building or bridge structures. One of the important checks in the process of design of this type of members is the control of their buckling load capacity. In this paper, the backpropagation feed-forward
Evaluation of Software Testing Techniques UsingArtificial Neural Network
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ABSTRACT Software Industry plays a vital role in the current environment, it is very essential to minimize the fault in the existing software products. In SDLC life cycle, software testing becomes very much important which finds faults in the software that increases the efficiency
Study of Electric Fields on High Voltage Composite Insulators under Polluted Conditions UsingArtificial Neural Network
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Abstract This paper attempts to applyartificialintelligent techniques in high voltage applications and especially to estimate the electric field distribution on a polluted insulator surface. The paper presents, a three-dimensional (3D) electric fields estimation program, to
Artificial Neural NetworkModel for Short-Term Electric Load Demand Forecasting: A Case of Nairobi Region
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Abstract Power engineers and energy planners require accurate electric load demand forecasts for efficient load dispatch, good generation mix and generation planning. Load forecasting using traditional statistical methods is often difficult because a number of non- CSE PROJECTS