Multi-strategy collaborative optimization of gravitational search algorithm by Zhonghua Yang, Yuanli Cai, Ge Li, Peng Wang, Yu Chen

“…In the early iterations, particle positions are primarily updated using the original gravitational force, preserving the inherent characteristics of the gravitational search algorithm. In the later stages, particles with better fitness values are updated using a globally optimal Lévy random walk strategy to enhance local search capabilities, while particles with poorer fitness values are updated using the sparrow algorithm follower strategy. …”
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Modified Meerkat Clan Algorithm for Association Rules Mining by Mohamad Ab. Saleh, Ahmed T. Sadiq Sadiq

“…In our work the rules will represented using two methods which are borrowed from the genetic algorithm; in the first one each group of rules refers to object in society which is called Pittsburgh; while the second one each rule refers to an object in society which is called Michigan. …”
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Vehicle Routing Problem with Transshipment: Mathematical Model and Algorithm by Thanapat Leelertkij, Parthana Parthanadee, Jirachai Buddhakulsomsiri

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Optimizing performance of WPCN based on whale optimization algorithm by Lina Yuan, Huajun Chen, Tinghong Chang, Ging Gong

“…WPC technology is capable of providing energy to terminal devices while transmitting information, which is crucial for the operation of low-power devices in the Internet of Things. …”
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Improved Visual SLAM Algorithm Based on Dynamic Scenes by Jinxing Niu, Ziqi Chen, Tao Zhang, Shiyu Zheng

“…This work presents a novel RGB-D dynamic simultaneous localization and mapping (SLAM) method that improves accuracy, stability, and efficiency of localization while relying on deep learning in a dynamic environment, in contrast to traditional static scene-based visual SLAM methods. …”
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A Vehicle Path Planning Algorithm: QDDG-RRT by Ruixin Zhang, Qing Xu, Kai Sun, Yi Liu, Ximming Zhu, Guo Zhang, Xiang Cheng

“…The Rapidly-exploring Random Tree (RRT) algorithm, while widely used, suffers from slow search speeds, numerous inflection points, and redundant operations. …”
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A multistrategy improved hunger games search algorithm by Qiu Yihui, Zhang Xinqiang, Li Ruoyu, Li Dongyi, Xia Feihan

“…The main contributions of MHGS are fourfold: (1) a phased position update framework that dynamically coordinates global exploration and local exploitation through three distinct search phases; (2) an enhanced reproduction operator inspired by biological reproductive patterns to preserve population diversity; (3) an adaptive boundary handling mechanism that redirects out-of-bounds individuals to promising regions, thus improving search efficiency; and (4) an elite dynamic oppositional learning strategy with self-adjusting coefficients to enhance the algorithm’s ability to avoid local optima. These mechanisms work synergistically: the phased update balances global and local search, while the reproduction and boundary handling strategies jointly maintain solution diversity. …”
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Fast autoscaling algorithm for cost optimization of container clusters by José María López, Joaquín Entrialgo, Manuel García, Javier García, José Luis Díaz, Rubén Usamentiaga

“…In comparison to the heuristics, FCMA achieves similar solving times while consistently delivering more cost-effective solutions.…”
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Optimization of the Weight Processing Algorithm in Multichannel Doppler Filtering by V. I. Koshelev, Ngoc Hieu Trinh

“…The use of modified FFT algorithms increases the efficiency of MDF against the background of white Gaussian noise, while reducing the efficiency of signal accumulation in the part of signal processing channels blocked by the narrow-band clutter. …”
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Particle algorithms for animal movement modelling in receiver arrays by Edward Lavender, Andreas Scheidegger, Carlo Albert, Stanisław W. Biber, Janine Illian, James Thorburn, Sophie Smout, Helen Moor

“…Within a sound probabilistic framework, the methodology integrates the movement process and the observation processes of disparate datasets, while correctly representing uncertainty. In a simulation‐based analysis, we compare the performance of our algorithm to the prevailing heuristic methods used to study movements and space use in passive acoustic telemetry systems and analyse algorithm sensitivity. …”
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Evolving the Whale Optimization Algorithm: The Development and Analysis of MISWOA by Chunfang Li, Yuqi Yao, Mingyi Jiang, Xinming Zhang, Linsen Song, Yiwen Zhang, Baoyan Zhao, Jingru Liu, Zhenglei Yu, Xinyang Du, Shouxin Ruan

“…This paper introduces an enhanced Whale Optimization Algorithm, named the Multi-Swarm Improved Spiral Whale Optimization Algorithm (MISWOA), designed to address the shortcomings of the traditional Whale Optimization Algorithm (WOA) in terms of global search capability and convergence velocity. …”
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Gravitational search algorithm optimization algorithm for grid distributed energy storage resource pool regulation matching load peak–valley and operation constraints by Zhichao Lin, Busheng Luo, Yingmin Wang, Lingfei Xie, Xiangyang Su, Gang Chen, Yuting Huang

“…Consequently, this study investigates the GSA optimization algorithm for regulating distributed energy storage resource pools in the power grid, which can address load peaks and valleys while adhering to operational constraints. …”
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Multi-Level Particle System Modeling Algorithm with WRF by Julong Chen, Bin Wang, Rundong Gan, Xuepeng Mou, Shiping Yang, Ling Tan

“…Based on the multi-scale mean-shift clustering algorithm, Adaptive Kernel Density Estimation (AKDE) is introduced to map density to bandwidth, achieving adaptive adjustment of clustering bandwidth while reducing computational resources and improving cloud hierarchy. …”
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Feature-based enhanced boosting algorithm for depression detection by Muhammad Sadiq Rohei, Kasturi Dewi Varathan, Shivakumara Palaiahnakote, Nor Badrul Anuar

“…Thus, this study has developed a novel feature-based enhanced boosting algorithm (F-EBA). The proposed model covers two pipelines, the feature engineering pipeline which improves the quality of features by picking up the most relevant features while the classification pipeline uses an ensemble approach designed to boost/elevate the model’s performances. …”
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Feature engineering through two-level genetic algorithm by Aditi Gulati, Armin Felahatpisheh, Camilo E. Valderrama

“…This study highlights the utility of evolutionary algorithms to generate feature sets that enhance the performance of interpretable machine learning models.…”
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An underground coal mine multi-target detection algorithm by FAN Shoujun, CHEN Xilin, WEI Liangyue, WANG Qingyu, ZHANG Shiyuan, DONG Fei, LEI Shaohua

“…The results showed that: ① The mAP@0.5 of the FEDSC-FFBD algorithm was 97.00%, the number of model parameters was 4.22×106, and the number of floating point operations per second was 21.7×109. ② The mAP@0.5 of the FEDSC-FFBD alorithm was 3.40% higher than the YOLOv8n algorithm, and the recognition accuracy of the helmet small target was 90.90%, 11% higher than the YOLOv8n algorithm. ③ Compared with other YOLO series algorithms, the FEDSC-FFBD algorithm achieved the highest mAP@0.5, which was 3.60%, 1%, 10.50%, and 6.40% higher than YOLOv5s, YOLOv9c, YOLOv10n, and YOLOv11n algorithms, respectively. ④ The FEDSC-FFBD algorithm improved the detection accuracy of multi-class targets and reduced missed detection and false detection of small targets under conditions of uneven light intensity distribution, complex target environments, and imbalanced target scale distribution in underground coal mine. …”
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An empirical study of the naïve REINFORCE algorithm for predictive maintenance by Rajesh Siraskar, Satish Kumar, Shruti Patil, Arunkumar Bongale, Ketan Kotecha, Ambarish Kulkarni

“…Abstract Reinforcement Learning (RL) is a biologically inspired, autonomous machine learning method. RL algorithms can help generate optimal predictive maintenance (PdM) policies for complex industrial systems. …”
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Using machine learning algorithms to predict colorectal cancer by Xingjian Xiao, Bo Hong, Kubra Maqsood, Xiaohan Yi, Guoqun Xie, Hailei Zhao, Bo Sun, Jianying Mao, Shiyou Liu, Xianglong Xu

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Pairing explainable deep learning classification with clustering to uncover effects of schizophrenia upon whole brain functional network connectivity dynamics by Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun

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Machine learning-based prognostic prediction for acute ischemic stroke using whole-brain and infarct multi-PLD ASL radiomics by Zhenyu Wang, Chaojun Jiang, Xianxian Zhang, Tianchi Mu, Qingqing Li, Shu Wang, Congsong Dong, Yuan Shen, Zhenyu Dai, Fei Chen

“…Five machine learning algorithms were used to construct radiomics models (whole-brain, infarct, and combined), clinical models, and comprehensive models integrating radiomics and clinical data. …”
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