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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Recognition of isolated elements picture using backpropagation neural network / Melati Sabtu
Published 2005“…There are three main programs work together. The programs are back-propagation neural network program, training and performance program and recognition program. …”
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Optimization of Multilayer Perceptron (MLP) network training algorithms for agrwood oil quality separation / Noratikah Zawani Mahabob ... [et al.]
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Conference or Workshop Item -
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Image classification using two dimensional wavelet coefficients with parallel computing
Published 2020“…In addition, this research does not require any pre-stored database to train the algorithm. This research requires the supervision from the users to train the algorithm by naming the region. …”
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Final Year Project / Dissertation / Thesis -
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Vision-based robot indoor navigation
Published 2022“…NodeRed links both processing units together. An algorithm is developed in the computer to achieve image processing, user input, path planning, simulation, and writing of output files. …”
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Final Year Project / Dissertation / Thesis -
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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process
Published 2004“…Building knowledge within the network was measured by calculating the total percentage of error between target machining data and the outputs from the network during the training process. The process of building the machining data knowledge (training) was successfully achieved. …”
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Neural network modeling and optimization for spray-drying coconut milk using genetic algorithm and particle swarm optimization
Published 2022“…The ANN model topology is designed using selection from the best training algorithm, transfer function, number of training runs (1000-5000), number of hidden layers (1-3) and nodes (5-15). …”
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Improve in speed and the convergence in training process for the purpose of system modeling using Hybrid Multilayer Perceptron (HMLP) neural network / Farida Karman
Published 2008“…The HMLP network is trained using a Modified Recursive Prediction Error (MRPE) algorithm to obtain the appropriate parameter for the network. …”
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Software Classification Using Structure-Based Descriptors
Published 2009“…A total of 2800 programs have been used during the training process while two different datasets of size (28) were used for testing. …”
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Flow regime identification of particles conveying in pneumatic pipeline using electric charge tomography and neural network techniques
Published 2006“…A high speed data acquisition card DAS1800HC is used to interface the sensors to a personal computer which processes the data using linear back projection algorithm (LBPA) and filtered back projection algorithm (FBPA). …”
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Application of Artificial Neural Networks (ANN) for unit commitment prediction / Robert Engkiau
Published 2003“…Results from existing Genetic Algorithm (GA) program were used as the NN training and testing data set. …”
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Thesis
