Search Results - ((((propagation algorithm) OR (selection algorithm))) OR (optimization algorithm))
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Gender classification on skeletal remains: efficiency of metaheuristic algorithm method and optimized back propagation neural network
Published 2020“…Besides that, another limitation that exists in previous researches is the absence of parameter optimization for the classifier. Thus, this paper proposed metaheuristic algorithms such as Particle Swarm Optimization, Ant Colony Algorithm and Harmony Search Algorithm based feature selection to identify the most significant features of skeleton remains. …”
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WCBP: A new water cycle based back propagation algorithm for data classification
Published 2016“…The performance of the proposed Water Cycle based Back-Propagation (WCBP) algorithm is compared with the conventional BPNN, ABC-BP and ABC-LM algorithms on selected benchmark classification problems from UCI Machine Learning Repository. …”
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Improved cuckoo search based neural network learning algorithms for data classification
Published 2014“…This research proposed an improved CS called hybrid Accelerated Cuckoo Particle Swarm Optimization algorithm (HACPSO) with Accelerated particle Swarm Optimization (APSO) algorithm. …”
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Thesis -
4
Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network
Published 2016“…First proposed algorithm is the combination of momentum algorithm with adaptive learning rate (ALR) algorithm, and second proposed algorithm is the combination of momentum algorithm with automatic learning rate selection (ALRS) algorithm. …”
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5
CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…ANN based STLF models commonly use back-propagation algorithm, which generally exhibits a slow and improper convergence that affects the forecast accuracy. …”
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6
Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification
Published 2015“…As a solution, nature inspired metaheuristic algorithms provide derivative-free solution to optimize complex problems. …”
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Advances of metaheuristic algorithms in training neural networks for industrial applications
Published 2023“…Backpropagation; Gradient methods; Neural networks; Artificial neural network models; Complex applications; Exploration and exploitation; Gradient-based learning; Industry applications; Meta heuristic algorithm; Meta-heuristic search algorithms; Near-optimal solutions; Optimization…”
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Route Optimization System
Published 2005“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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Levy slime mould algorithm for solving numerical and engineering optimization problems
Published 2022“…Therefore, for solving the SMA algorithm local optima problem, we used the Levy distribution rather than the conventional uniform distribution in the candidate selection procedure. …”
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Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed
Published 2012“…Multilayer Feedforward Back Propagation (MLFFBP) was used. Among the available learning algorithms in the Neural Network Toolbox of MATLAB, three algorithms, gradient descent back propagation (TRAINGD), gradient descent with adaptive learning rule back propagation (TRAINGDA) and the Levenberg-Marquardt (TRAINLM) were studied. …”
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Prediction of optimum compositions of parenteral nanoemulsion system loaded with low solubility drug for treatment of schizophrenia by artificial neural network
Published 2016“…It was found that the optimal algorithm and topology were the quick propagation and the configuration with 5 inputs, 4 hidden and 1 output nodes, respectively. …”
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Lithium-ion Battery State of Charge Estimation Method Using Optimized Deep Recurrent Neural Network Algorithm
Published 2023“…Alumina; Aluminum oxide; Backpropagation; Battery management systems; Bioluminescence; Charging (batteries); Cobalt compounds; Deep neural networks; Genetic algorithms; Ions; Lithium compounds; Machine learning; Nickel oxide; Radial basis function networks; Recurrent neural networks; Back-propagation neural networks; Computation intelligences; Electrochemical batteries; Firefly algorithms; Manganese-cobalt oxides; Radial basis function neural networks; Self-learning capability; State of charge; Lithium-ion batteries…”
Conference Paper -
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Predicting the optimum compositions of a transdermal nanoemulsion system containing an extract of Clinacanthus nutans leaves (L.) for skin antiaging by artificial neural network mo...
Published 2017“…Five universal learning algorithms—incremental back propagation, batch back propagation, quick propagation, genetic algorithm, and Levenberg-Marquardt—were used in the ANN to achieve the optimum topologies. …”
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Early detection of dengue disease using extreme learning machine
Published 2018“…Therefore, this research proposed an improved algorithm known as ELM which is an extension of Feed Forward Neural Network that utilize the Moore Penrose Pseudoinver matrix that gain the optimal weights of neural network architecture. …”
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Enhancement of heavy metals sorption via nanocomposites of rice straw and Fe3O4 nanopeprintss using artificial neural network (ANN)
Published 2016“…To acquire the optimum topologies, ANN was trained by quick propagation (QP), Batch Back Propagation (BBP), Incremental Back Propagation (IBP), genetic algorithm (GA) and Levenberg-Marquardt (LM) algorithms for testing data set. …”
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Improved recurrent NARX neural network model for state of charge estimation of lithium-ion battery using pso algorithm
Published 2023“…Backpropagation; Charging (batteries); Errors; Industrial electronics; Ions; Lithium-ion batteries; Mean square error; Particle swarm optimization (PSO); Recurrent neural networks; Temperature; Back-propagation neural networks; Drive cycles; Lithium ions; NARX neural network; Nonlinear AutoRegressive with eXogenous input models; Particle swarm optimization algorithm; State of charge; State-of-charge estimation; Battery management systems…”
Conference Paper -
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Enhancement of heavy metals sorption via nanocomposites of rice straw and Fe3O4 nanoparticles using artificial neural network (ANN)
Published 2016“…To acquire the optimum topologies, ANN was trained by quick propagation (QP), Batch Back Propagation (BBP), Incremental Back Propagation (IBP), genetic algorithm (GA) and Levenberg-Marquardt (LM) algorithms for testing data set. …”
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An efficient model for indoor radio signal prediction and coverage estimation / Md. Sumon Sarker
Published 2011“…And the second algorithm is the optimization technique for indoor wireless coverage. …”
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BAT-BP: A new BAT based back-propagation algorithm for efficient data classification
Published 2016“…Thus, this study investigates the use of Bat algorithm along with back-propagation neural network (BPNN) algorithm in-order to gain optimal weights to solve the local minima problem and also to enhance the convergence rate. …”
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