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Effective long-term tracking with contrast optimizer
The main challenge of long-term tracking includes data uncertainty in long-term observations. Previous methods tackle the long-term tracking task by...
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Equilibrium optimizer: a comprehensive survey
Equilibrium optimizer (EO) is a recent optimization method inspired by the physical equation of the mass balance that provides the conservation of...
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Digital Channel Equalizer Using Functional Link Artificial Neural Network Trained with Quantum Aquila Optimizer
In digital communication, channel equalization plays an important role in mitigating the effects of inter-symbol interference, non-linearity and...
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Lero : applying learning-to-rank in query optimizerIn recent studies, machine learning techniques have been employed to support or enhance cost-based query optimizers in DBMS. Although these...
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Boosting manta rays foraging optimizer by trigonometry operators: a case study on medical dataset
The selection of attributes has become a crucial research focus in the domains of pattern recognition, machine learning, and big data analysis. In...
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Enhanced handwritten digit recognition using optimally selected optimizer for an ANN
Handwritten digit recognition is a complex problem that has stumped even the brilliant minds of this century. Getting precise results from different...
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Ehnanced Grey Wolf Optimizer
In this paper, we propose EGWO, a new version of Grey Wolf Optimizer. The EGWO algorithm works in almost the same way as the original algorithm, only...
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Multiplayer battle game-inspired optimizer for complex optimization problems
Various popular multiplayer battle royale games share a lot of common elements. Drawing from our observations, we summarized these shared...
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Multi-strategy enhanced Grey Wolf Optimizer for global optimization and real world problems
The Grey Wolf Optimizer (GWO) is one of the more successful swarm-based intelligent algorithms in recent years, but the shortcomings of the Grey Wolf...
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Improved aquila optimizer with mRMR for feature selection of high-dimensional gene expression data
Accurate classification of gene expression data is crucial for disease diagnosis and drug discovery. However, gene expression data usually has a...
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Multi-objective fitness-dependent optimizer algorithm
This paper proposes the multi-objective variant of the recently-introduced fitness dependent optimizer (FDO). The algorithm is called a...
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Eel and grouper optimizer: a nature-inspired optimization algorithm
This paper proposes a meta-heuristic called Eel and Grouper Optimizer (EGO). The EGO algorithm is inspired by the symbiotic interaction and foraging...
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Wind farm layout optimization using adaptive equilibrium optimizer
The layout optimization of wind turbines seeks to improve wind power conversion efficiency by minimizing the wake effect in wind farm. However, the...
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Puma optimizer (PO): a novel metaheuristic optimization algorithm and its application in machine learning
Optimization techniques, particularly meta-heuristic algorithms, are highly effective in optimizing and enhancing efficiency across diverse models...
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Improving rating predictions with time-varying attention and dual-optimizer
Due to the rapid expansion of online platforms, review-based recommender systems have become the standard way to determine consumers’ preferences for...
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A binary hybrid sine cosine white shark optimizer for feature selection
Feature Selection (FS), a pre-processing step used in the majority of big data processing applications, aims to eliminate irrelevant and redundant...
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Pied kingfisher optimizer: a new bio-inspired algorithm for solving numerical optimization and industrial engineering problems
In this study, we introduce the pied kingfisher optimizer (PKO), a novel swarm-based meta-heuristic algorithm that draws inspiration from the...
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An Improved Competitive Swarm Optimizer with Super-Particle-Leading
Competitive swarm optimizer (CSO) has been concerned in recent years due to its achievements in solving global optimization problems. However, the...
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An enhanced sea-horse optimizer for solving global problems and cluster head selection in wireless sensor networks
An efficient variant of the recent sea horse optimizer (SHO) called SHO-OBL is presented, which incorporates the opposition-based learning (OBL)...
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Bacteria phototaxis optimizer
This paper introduces a new metaheuristic algorithm called bacteria phototaxis optimizer (BPO). It is designed to solving optimization issues....
