Search Results - (( using solution learning algorithm ) OR ( using optimization approach algorithm ))
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A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution
Published 2018“…An intelligence strategy called quasi-oppositional based learning is incorporated into the proposed algorithm to enhance its convergence property, exploration capability, and solution optimality. …”
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An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction
Published 2014“…Here, three improved learning approaches inspired by artificial honey bee's behavior are used to train MLP. …”
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Wavelet neural networks based solutions for elliptic partial differential equations with improved butterfly optimization algorithm training
Published 2020“…Although the gradient information of the commonly used gradient descent training algorithm in WNNs may direct the search to optimal weight solutions that minimize the error function, the learning process is slow due to the complex calculation of the partial derivatives. …”
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A harmony search-based learning algorithm for epileptic seizure prediction
Published 2016“…The proposed harmony search-based learning algorithm is used in the task of epileptic seizure prediction. …”
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Improved whale optimization algorithm for feature selection in Arabic sentiment analysis
Published 2019“…The proposed algorithm is compared with six well-known optimization algorithms and two deep learning algorithms. …”
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Adaptive mechanism for enhanced performance of shark smell optimization / Nur Atharah Kamarzaman, Shahril Irwan Sulaiman and Intan Rahayu Ibrahim
Published 2021“…Various meta-heuristic approaches have been developed to find the optimal solution to optimization problems. …”
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On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing
Published 2015“…Although useful, strategies based on the aforementioned optimization algorithms are not without limitation. …”
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A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules
Published 2013“…In the first proposed algorithm, SA is used to optimize the rule's discovery activity by an ant. …”
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Optimization of balanced academic curriculum problem in educational institutions using teaching learning based optimization algorithm
Published 2025“…This study aims to optimize BACP using the Teaching-Learning Based Optimization (TLBO) algorithm, addressing the limitations of existing approaches and providing an efficient framework for curriculum balancing. …”
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Feedforward neural network for solving particular fractional differential equations
Published 2024“…The final scheme utilizes a two hidden layer FNNVA, with Adam optimization, using suitable number of nodes and value of learning rates to handle problems involving memory and fractal concepts. …”
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Optimal power flow based on fuzzy linear programming and modified Jaya algorithms
Published 2017“…In the proposed novel QOJaya algorithm, an intelligence strategy, namely, quasi-oppositional based learning (QOBL) is incorporated into the basic Jaya algorithm to enhance its convergence speed and solution optimality. …”
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Metaheuristic algorithms for feature selection (2014–2024)
Published 2025“…In this study, a case study is provided using datasets from the University of California, Irvine repository, where various metaheuristic algorithms are applied to identify optimal feature subsets.…”
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Enhanced Harris's Hawk algorithm for continuous multi-objective optimization problems
Published 2020“…Harris’s hawk multi-objective optimizer (HHMO) algorithm is a MOSIbased algorithm that was developed based on the reference point approach. …”
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The Evolutionary Convergent Algorithm: A Guiding Path of Neural Network Advancement
Published 2025“…In the past few decades, there have been multiple algorithms proposed for the purpose of solving optimization problems including Machine Learning (ML) applications. …”
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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Different mutation and crossover set of genetic programming in an automated machine learning
Published 2020“…The function of Genetic Programming is to optimize the best combination of solutions from the possible pipelines of machine learning modelling, including selection of algorithms and parameters optimization of the selected algorithm. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…While the firefly algorithm solution is superior, it has a higher time complexity compared to other algorithms used when there are more hidden layers and neurons. …”
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Differential evolution for neural networks learning enhancement
Published 2008“…These algorithms have widely been used to optimize the learning mechanism of classifiers, particularly on Artificial Neural Network (ANN) Classifier. …”
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