ann artificial neural network IEEE PAPER , IEEE PROJECT
artificial neural network is an interconnected group of nodes, inspired by a simplification of neurons in a brain. Here, each circular node represents an artificial neuron and an arrow represents a connection from the output of one artificial neuron to the input of another.
Artificial Neural Network models to predict energy
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Climate change, the decrease in fossil-based energy resources and the need of reducing the greenhouse gas emissions require energy efficient and smart buildings. Moreover, the ratio of renewable energy sources should be increased against traditional energy sources
Artificial Neural Network Based Path Planning of Excavator Arm
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This paper presents a solution in path planning for a robotic arm based on the artificial neural network (ANN) architecture, particularly a Static (Feedforward) Neural Network (SNN). The inputs of the network are the sample sets that are obtained from some specific
Artificial Neural Network for Diagnose Autism Spectrum Disorder
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Artificial Neural Network for Diagnose Autism Spectrum Disorder University- Gaza, Faculty of Engineering and Information Technology
Prediction of Hourly Cooling Energy Consumption of Educational Buildings Using Artificial Neural Network
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Predicating the required building energy when it is in the design stage and before being constructed considers a crucial step for in charge people. Hence, the main aim of this research is to accurately forecast the needed building cooling energy per hour for
Gait Feature Based on Human Identification Classification by Using Artificial Neural Network and Project Management Approaches for Its Implementation
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With the increased threat of terrorism and identity theft, human recognition is one of the basic elements of present eras security applications installed in commercial malls, banks, hospitals, military installations, airports, religious places etc. The basic aim of this research
PREDICTIVE MODELS OF THE DOMINANT PERIOD OF SITE USING ARTIFICIAL NEURAL NETWORK AND MICROTREMOR MEASUREMENTS
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Direct drilling method and the use of microtremor studies are among the most commonly used available methods utilized to estimate dynamic parameters for a site. One of the most important parameters is the dominant period of the site whose estimation plays a pivotal role
ARTIFICIAL NEURAL NETWORK PREDICTION MODEL OF KARST WATER IN COAL MINES
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ABSTRACT A neural network algorithm based on backpropagation algorithm was proposed in this paper. An artificial neural network prediction model for karst water in coal mines was established for the first time to study the supply characteristics of karst water and its key
An Innovative Approach for Study of Thermal Behavior of an Unsteady Nanofluid Squeezing Flow between Two Parallel Plates Utilizing Artificial Neural Network
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This study reveals the thermal behavior of an unsteady nanofluid streaming between two parallel plates by using artificial neural network (ANN). Initially, a similarity solution is employed to simplify the partial differential equations (PDSs) and convert them into a system
Harmonic Analysis of Photovoltaic-Fed Symmetric Multilevel Inverter using Modified Artificial Neural Network
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This paper presents a control scheme to eliminate the harmonics in a symmetric cascaded multilevel inverter-connected grid system. It is controlled by modified artificial neural networks and genetic algorithm. The solar photovoltaic acts as input source and the output
Evaluating Potential of Artificial Neural Network and Neuro-Fuzzy Techniques for Global Solar Radiation Prediction in Isfahan, Iran
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In this study, two widely used artificial intelligence techniques, ie Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS), were applied for global solar radiation (GSR) prediction in Isfahan Province, Iran. Different sets of meteorological data
A Model for English to Urdu and Hindi Machine Translation System using Translation Rules and Artificial Neural Network
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This paper illustrates the architecture and working of a proposed multilingual machine translation system which is able to translate from English to Urdu and Hindi. The system applies translation rules based approach with artificial neural network . The efficient pattern
Prediction of life of piercing punches using artificial neural network and adaptive neuro fuzzy inference systems
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Predicting the life of piercing punch is one of the major concerns in the design of compound dies. Finite element analysis is performed to determine the maximum and minimum principal stresses through which fatigue limit of punch is estimated. The factors affecting the life of
Fingers movements control system based on artificial neural network model
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Surface electromyographic (sEMG) signal is used in the various fields of applications where the need exists to measure the activity of body muscles, such as brain-computer interfaces, game industry, medical engineering, and other practical spheres. Even more, the use of
Application of an Artificial Neural Network in the Diagnosis of Chronic Lymphocytic Leukemia
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Chronic lymphocytic leukemia (CLL) is one of the most common types of leukemia, and the early diagnosis of patients coincides with their proper treatment and survival. If patients are diagnosed late or proper treatment is not applied, it may lead to harmful results. Several
Prediction and verification of compressive strength of historical masonry structures with artificial neural network
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Compressive strength and modulus of elasticity are the key material properties of historical structures to adapt finite element model to obtain correct structural assessment. Generally, modulus of elasticity is adapted by multiplying compressive strength of the material. In this
A survey on rainfall forecasting using artificial neural network
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Rainfall has a great impact on agriculture and peoples daily travel, so accurate prediction of precipitation is well worth studying for researchers. Traditional methods like numerical weather prediction (NWP) models or statistical models cant provide satisfied effect of rainfall
Estimation of Austenitizing and Multiple Tempering Temperatures from the Mechanical Properties of AISI 410 using Artificial Neural Network
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This research involved a study of the heat treatment conditions effect on the mechanical properties of martensitic stainless steel type AISI 410. Heat treatment process was hardening of the metal by quenching at different temperature 900 C, 950 C, 1000 C, 1050 C
A study on machinability evaluation of Al-Gr-B 4 C MMC using response surface methodology-based desirability analysis and artificial neural network technique
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In this work, machinability behaviour of aluminium-graphite-boron carbide metal matrix composite is performed during wire-cut electrical discharge machining (WEDM) process. Experiments were designed using central composite-face centred design of response
BACK PROPAGATION ARTIFICIAL NEURAL NETWORK MODELING OF FLEXURAL AND COMPRESSIVE STRENGTH OF CONCRETE REINFORCED WITH
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The production of fiber reinforced concrete involves a complex reaction system. This imposes an immense challenge in deriving appropriate material proportions of concrete to achieve desired mechanical properties. In order to facilitate selection of a design matrix for
ARTIFICIAL NEURAL NETWORK AND PHYSICAL BASED MODELS FOR WATER-LEVEL FORECASTS OF INNER NIGER DELTA IN MALI
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The Niger Inner Delta (NID) is a wetland that was selected as an International Important Wetland under the Ramsar Convention (on February 1st, 2004) and can still be considered a hotspot of biodiversity in the Sahel. The Niger River is the main water source for the NID
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