Search Results - back ((optimization algorithm) OR (selection algorithm))
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1
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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4
Development of multi-objective load shedding optimization via back tracking search algorithm with novel reactive power tracing index
Published 2023“…Electric power plant loads; Learning algorithms; MATLAB; Multiobjective optimization; Optimization; Reactive power; Back tracking; Backtracking search algorithms; Identification method; Load-shedding; Multi-objective functions; Power flow simulation; System contingencies; Under voltage load shedding; Electric load shedding…”
Conference Paper -
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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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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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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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8
Advances of metaheuristic algorithms in training neural networks for industrial applications
Published 2023Article -
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Optimization Of Fractional-Slot Permanent Magnet Synchronous Machine Using Analytical Sub-Domain Model And Differential Evolution
Published 2019“…Three multi-objective optimizations based on Analytical Sub-Domain (ASD) and Differential Evolution Algorithm (DEA), Analytical Sub-Domain (ASD) and Particle Swarm Optimization (PSO), Analytical Sub-Domain (ASD) and Genetic Algorithm (GA), for fractionalslot Permanent Magnet Synchronous Machines (PMSM) are formulated, computed and optimized. …”
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10
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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11
An Efficient Solution to Travelling Salesman Problem using Genetic Algorithm with Modified Crossover Operator
Published 2019“…A modified crossover method using Minimal Weight Variable, Order Selection Crossover operator, a modified mutation using local optimization and a modified selection method using KMST is proposed. …”
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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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An improved energy-efficient clustering protocol to prolong the wireless sensor network lifetime
Published 2021“…Lastly, cluster heads (CHs) are selected in optimal locations with the rotation of the CH function among members of the cluster based on a new CH selection-rotation algorithm by combining a back-off timer mechanism for CH selection and rotation mechanism for CH rotation. …”
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14
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…”
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Solving vehicle routing problem by using improved genetic algorithm for optimal solution
Published 2023Article -
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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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Prediction of optimum compositions of parenteral nanoemulsion system loaded with low solubility drug for treatment of schizophrenia by artificial neural network
Published 2016“…To obtain the optimum topologies, ANNs were trained by Incremental Back Propagation (IBP), Genetic Algorithm (GA), Batch Back Propagation (BBP), Quick Propagation (QP), and Levenberg-Marquardt (LM) algorithms for testing data set. …”
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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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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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