QQLMPA: A quasi-opposition learning and Q-learning based marine predators algorithm
Expert Systems with Applications, 2023 Many engineering and scientific problems in the real-world boil down to optimization problems, which are difficult to solve by using traditional methods. Meta-heuristics are appealing algorithms for solving optimization problems while keeping computational costs reasonable.
Shangrui Zhao +5 more
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Black-Winged Kite Algorithm Integrating Opposition-Based Learning and Quasi-Newton Strategy [PDF]
BiomimeticsTo address the deficiencies in global search capability and population diversity decline of the black-winged kite algorithm (BKA), this paper proposes an enhanced black-winged kite algorithm integrating opposition-based learning and quasi-Newton strategy
Ning Zhao, Tinghua Wang, Yating Zhu
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Application of opposition-based learning concepts in reducing the power consumption in wireless access networks [PDF]
, 2016 The reduction of power consumption in wireless access networks is a challenging and important issue. In this paper, we apply Opposition-Based Learning (OBL) concepts for reducing the power consumption of LTE base stations. More specifically, we present a
Sotirios K. Goudos +4 more
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Deep learning based thyroid prediction with opposition learning based red panda optimization feature selection [PDF]
Scientific ReportsThis research introduces a novel approach for thyroid prediction by considering three various publicly available datasets. The input data from the dataset is preprocessed to ensure standardization and balance for mitigating the biased outcomes. Then, the
K. Hema Priya, K. Valarmathi
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PSO-Incorporated Hybrid Artificial Hummingbird Algorithm with Elite Opposition-Based Learning and Cauchy Mutation: A Case Study of Shape Optimization for CSGC-Ball Curves. [PDF]
Biomimetics (Basel), 2023 Chen K, Chen L, Hu G.
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Fick’s Law Algorithm Enhanced with Opposition-Based Learning
MathematicsMetaheuristic algorithms are widely used for solving complex optimization problems without relying on gradient information. They efficiently explore large, non-convex, and high-dimensional search spaces but face challenges with dynamic environments ...
Charis Ntakolia
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Global-best brain storm optimization algorithm based on chaotic difference step and opposition-based learning [PDF]
Scientific ReportsRecently, the following global-best strategy and discussion mechanism have been prevailing to solve the slow convergence and the low optimization accuracy in the brain storm optimization (BSO) algorithm.
Yanchi Zhao +3 more
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Fireworks Algorithm Based on Opposition-Based Learning and Quantum Optimization Strategy
Journal of Physics: Conference Series, 2020 Abstract Aiming at the bottleneck of optimization performance and slow convergence speed of fireworks algorithm, a new fireworks algorithm (FWA) is proposed by integrating Opposition-Based Learning and Quantum Optimization strategy (OQFWA).
Hongbin Jin, Hao Li, Yanyan Ma, Xi Fang
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Alexandria Engineering JournalHoney badger algorithm (HBA) is a recent swarm-based metaheuristic algorithm that excels in simplicity and high exploitation capability. However, it suffers from some limitations including weak exploration capacity and an imbalance between exploration ...
Peixin Huang +5 more
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An Improved Opposition-Based Learning Particle Swarm Optimization for the Detection of SNP-SNP Interactions. [PDF]
Biomed Res Int, 2015 Shang J +5 more
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