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Logic Programming In Radial Basis Function Neural Networks
Published 2013“…In this thesis also, I developed a new technique to extract the logic programming from radial basis function neural networks. …”
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A study on regional GDP forecasting analysis based on radial basis function neural network with genetic algorithm (RBFNN-GA) for Shandong economy
Published 2022“…These basic indicators can comprehensively and effectively reflect a country’s or region’s future economic development. The center of radial basis function neural network and smoothing factor to take a uniform distribution of the random radial basis function artificial neural network will be the focus of this study. …”
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Neural Network Model and Finite Element Simulation of Spring back in Plane-Strain Metallic Beam Bending
Published 2006“…To validate the finite element model physical experiments were conducted. A neural network algorithm based on the backpropagation algorithm has been developed. …”
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The Determination of Pile Capacity Using Artificial Neural-net: An Optimization Approach
Published 2001“…In this study, the developed algorithm is further expanded to include computation of the weight-matrix of a sequential associative feedback-type neural net model for the determination of service load of a single pile is introduced. …”
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Particle swarm optimization for neural network learning enhancement
Published 2006“…Two programs have been developed; Particle Swarm Optimization Feedforward Neural Network (PSONN) and Genetic Algorithm Backpropagation Neural Network (GANN). …”
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Differential evolution for neural networks learning enhancement
Published 2008“…Three programs have developed; Differential Evolution Neural Network (DENN), Genetic Algorithm Neural Network (GANN) and Particle Swarm Optimization with Neural Network (PSONN) to probe the impact of these methods on ANN learning using various datasets. …”
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Application Of Neural Network In Malaria Parasites Classification
Published 2006“…The first stage of this project is to develop the neural network using MATLAB Neural Network Toolbox and Borland C++ Builder. …”
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Monograph -
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Y-type Random 2-satisfiability In Discrete Hopfield Neural Network
Published 2024“…Experimental results demonstrated the compatibility of the proposed logical rule and the Discrete Hopfield Neural Network. Additionally, the proposed Hybrid Differential Evolution Algorithm was implemented into the training phase to ensure that the cost function of the Discrete Hopfield Neural Network is minimized. …”
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Development of vision autonomous guided vehicle behaviour using neural network
Published 2012“…The objectives of this project are to develop a line recognition algorithm for automated guided vehicle and to understand two types of neural networks that can be use in manufacturing. …”
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Undergraduates Project Papers -
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Acceleration Strategies For The Backpropagation Neural Network Learning Algorithm
Published 2001“…The backpropagation algorithm has proven to be one of the most successful neural network learning algorithms. …”
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Lithium-ion Battery State of Charge Estimation Method Using Optimized Deep Recurrent Neural Network Algorithm
Published 2023Conference Paper -
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A new hybrid fuzzy ARTMAP and radial basis function neural network with online pruning strategy
Published 2023Conference Paper -
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PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM
Published 2011“…An artificial neural network (ANN), or shortly "neural network" (NN), is a powerful mathematical or computational model that is inspired by the structure and/or functional characteristics of biological neural networks. …”
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Wind power prediction using Artificial Neural Network: article
Published 2010“…In order to get an accurate wind power prediction, several network structures, training algorithms and transfer functions have been developed and tested with different sets of data. …”
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Forecasting sunspot numbers with Feedforward Neural Networks (FNN) using 'sunspot neural forecaster' system
Published 2011“…Feedforward Neural Network will be used in this investigation by using different learning algorithms, sunspot data models and FNN transfer functions. …”
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Conference or Workshop Item -
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Neural network algorithm-based fall detection modelling
Published 2020“…This article presents results of modelling for fall detection system by using nonlinear autoregression neural network NARnet algorithm. The algorithm is trained by network training function; LM, SCG and RP by collocation with threshold-based setting value. …”
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