Search Results - (( based selection ((bat algorithm) OR (_ algorithm)) ) OR ( swarm optimization max algorithm ))*
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A particle swarm optimization and min-max-based workflow scheduling algorithm with QoS satisfaction for service-oriented grids
Published 2017“…The algorithm selects the best scheduling solutions based on the proposed constraint-handling strategy. …”
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Social spider optimisation algorithm for dimension reduction of electroencephalogram signals in human emotion recognition
Published 2018“…Due to some limitations of current heuristics and evolutionary algorithms, this paper proposed a new swarm based algorithm for feature selection method called Social Spider Optimization (SSO-FS). …”
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Reactive memory model for ant colony optimization and its application to TSP
Published 2014“…The performances of six (6) ant colony optimization variants were evaluated to select the base for the proposed model.Based on the results, Max-Min Ant System has been chosen as the base for the modification.The modified algorithm called RMMAS, was applied to TSPLIB95 data and results showed that RMMAS outperformed the standard MMAS.…”
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Bats echolocation-inspired algorithms for global optimisation problems
Published 2016“…The aim of the research is to introduce novel form of swarm intelligence algorithms based on real echolocation behaviour of bats. …”
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Opposition-Based Learning Binary Bat Algorithm as Feature Selection Approach in Taguchi's T-Method
Published 2024Subjects: “…Binary Bat Algorithm…”
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Taguchi?s T-method with Normalization-Based Binary Bat Algorithm
Published 2025“…Therefore, a variable selection technique using a swarm-based Binary Bat algorithm is proposed. …”
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Reservoir operation based on evolutionary algorithms and multi-criteria decision-making under climate change and uncertainty
Published 2018“…A genetic algorithm and a particle swarm algorithm were selected for comparison with the bat algorithm. …”
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Performance comparison of GA and PSO based ANN training on medical dataset / Muhammad Amirul Danish Jamal
Published 2025“…This research performs a comparative analysis of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) as methods for optimizing the training of ANNs, utilizing three medical datasets: Breast Cancer Wisconsin, Cleveland Heart Disease, and Pima Indian Diabetes. …”
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9
Opposition-Based Quantum Bat Algorithm to Eliminate Lower-Order Harmonics of Multilevel Inverters
Published 2021“…This study proposes an opposition-based quantum bat algorithm (OQBA) to determine these optimum switching angles. …”
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Opposition-Based Quantum Bat Algorithm to Eliminate Lower-Order Harmonics of Multilevel Inverters
Published 2021“…This study proposes an opposition-based quantum bat algorithm (OQBA) to determine these optimum switching angles. …”
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Multivariable PID controller design tuning using bat algorithm for activated sludge process
Published 2018“…The selected optimization technique is Bat Algorithm (BA). …”
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Performance comparison of differential evolution and particle swarm optimization in constrained optimization
Published 2012“…Particle swarm optimization (PSO) and differential evolution (DE) are among the well-known modern optimization algorithms. …”
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The performance of Taguchi�s T-method with binary bat algorithm based on great value priority binarization for prediction
Published 2023“…This paper proposes an optimization algorithm based on the Binary Bat algorithm methodology for replacing the conventional orthogonal array approach. …”
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Bat algorithm for rough set attribute reduction
Published 2023“…In this paper, a new optimization method has been introduced called bat algorithm for attribute reduction (BAAR), the proposed method is based mainly on the echolocation behavior of bats. …”
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Multi-Swarm bat algorithm
Published 2023“…In this study a new Bat Algorithm (BA) based on multi-swarm technique called the Multi-Swarm Bat Algorithm (MSBA) is proposed to address the problem of premature convergence phenomenon. …”
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Data normalization techniques in swarm-based forecasting models for energy commodity spot price
Published 2014“…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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Artificial neural network-salp-swarm algorithm for stock price prediction
Published 2024“…Additionally, the SSA-ANN model is compared with other two hybrid models: the ANN optimized by the Whale Optimization Algorithm (WOA-ANN) and Moth-Flame Optimizer (MOA-ANN), as well as a single model, namely the Autoregressive Integrated Moving Average (ARIMA). …”
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An enhanced binary bat and Markov clustering algorithms to improve event detection for heterogeneous news text documents
Published 2022“…The effectiveness of ABBA-AMCL was compared to 8 FS methods based on meta-heuristic algorithms and 6 graph-based ED methods. …”
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Bat Algorithm Based Hybrid Filter-Wrapper Approach
Published 2023“…This paper presents a new hybrid of Bat Algorithm (BA) based on Mutual Information (MI) and Naive Bayes called BAMI. …”
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