Search Results - (( structures learning optimization algorithm ) OR ( java application using algorithm ))
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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RSA Encryption & Decryption using JAVA
Published 2006“…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction
Published 2014“…Most of the training algorithms focus on weight values, activation functions, and network structures for providing optimal outputs. …”
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Optimization of neural network architecture using genetic algorithm for load forecasting
Published 2014“…In this paper, a computational intelligent technique genetic algorithm (GA) is implemented for the optimization of artificial neural network (ANN) architecture. …”
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Binary ant colony optimization algorithm in learning random satisfiability logic for discrete hopfield neural network
Published 2024“…It aimed to optimize the performance of G-type random high-order satisfiability logic structures embedded in Discrete Hopfield Neural Networks, thereby enhancing the efficiency of the Hopfield Neural Network learning algorithm. …”
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Provider independent cryptographic tools
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Monograph -
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Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin
Published 2014“…Bat algorithm was employed to optimize the training parameters such as learning rate, momentum rate and number of neurons in hidden layers. …”
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A conceptual multi-agent framework using ant colony optimization and fuzzy algorithms for learning style detection
Published 2023“…The multi-agent system applies ant colony optimization and fuzzy logic search algorithms as tools to detecting learning styles. …”
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Hybrid bat algorithm hybrid-artificial neural network for modeling operating photovoltaic module temperature / Noor Rasyidah Hussin
Published 2014“…Bat algorithm was employed to optimize the training parameters such as learning rate, momentum rate and number of neurons in hidden layers. …”
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Machine Learning Based Optimal Design of On-Road Charging Lane for Smart Cities Applications
Published 2025“…The learning algorithms consider variables such as core structure, cross-coupling effect, and coil flux pipe length. …”
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A speech recognition system based on structure equivalent fuzzy neural network trained by firefly algorithm
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Working Paper -
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Prediction of lattice constant of pyrochlore compounds using optimized machine learning model
Published 2023“…In this study, we used an optimized machine learning technique based on Particle Swarm Optimization-Support Vector Regression (PSO-SVR) to learn the relationship between its structural properties with its lattice constants. …”
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Integration of GWO-LSSVM for time series predictive analysis
Published 2016“…In most cases, disaster prevention operation such flood warning scheme proved to be more efficient in mitigating the effects of major floods than structural measures. Thus, for this study, a hybrid algorithm of LSSVM with one of the recent bio-inspired optimization algorithm, namely Grey Wolf Optimizer (GWO-LSSVM) is presented for water level prediction. …”
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Real-Time Video Processing Using Native Programming on Android Platform
Published 2012“…However for the Android platform that based on the JAVA language, most of the software algorithm is running on JAVA that consumes more time to be compiled. …”
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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“…To overcome these limitations, there have been attempts to use genetic algorithm (GA) to optimize some of these parameters. …”
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Thesis -
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Direct approach for mining association rules from structured XML data
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Multi objective genetic algorithm for training three term backpropagation network
Published 2013“…Multi Objective Evolutionary Algorithms has been applied for learning problem in Artificial Neural Networks to improve the generalization of the training and testing unseen data.This paper proposes the simultaneous optimization method for training Three Term Back Propagation Network (TTBPN) learning using Multi Objective Genetic Algorithm.The Non-dominated Sorting Genetic Algorithm II is applied to optimize the TTBPN structure by simultaneously reducing the error and complexity in terms of number of hidden nodes of the network for better accuracy in classification problem.This methodology is applied in two kinds of multiclasses data set obtained from the University of California at Irvine repository.The results obtained for training and testing on the datasets illustrate less network error and better classification accuracy, besides having simple architecture for the TTBPN.…”
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