Predicting the Likelihood of Operational Risk Occurrence in the Banking Industry Using Machine Learning Algorithms by Hamed Naderi, Mohammad Ali Rastegar Sorkhe, Bakhtiar Ostadi, Mehrdad Kargari

“…Specifically, the RF algorithm achieved an accuracy of 0.9690, while the SVM algorithm attained an accuracy of 0.9587 in State 1, making them the most effective models in this setting. …”
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Harnessing synergy of machine learning and nature-inspired optimization for enhanced compressive strength prediction in concrete by Abba Bashir, Esar Ahmad, Shashivendra Dulawat, Sani I. Abba

“…This study assesses nine machine learning models, integrating conventional AI algorithms, such as artificial neural network (ANN), support vector regression (SVR), and random forest (RF) with nature-inspired optimization techniques including chicken swarm optimization (CSO), moth flame optimization algorithm (MFO), and whale optimization algorithm (WOA). …”
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RETRACTED: Adolescents’ Algorithmic Resistance to Short Video APP’s Recommendation: The Dual Mediating Role of Resistance Willingness and Resistance Intention by Xing Lv, Yang Chen, Weiqi Guo

“…The findings revealed that the perceived threat to freedom, algorithmic literacy, and peer influence were positively associated with the resistance willingness and intention; while the independent psychology on algorithmic recommendations significantly weakened resistance willingness and intention. …”
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Prediction method of soil water content based on SVM optimized by improved salp swarm algorithm by Xiaoqiang ZHAO, Fan YANG, Zhufeng YAN

“…Aiming at the problems of low accuracy and low efficiency of traditional soil water content prediction methods, support vector machine (SVM) was used to establish a prediction model, and the soil water content prediction method based on SVM optimized was proposed by the improved salp swarm algorithm.Firstly, the opposition-based learning and chaotic optimization were introduced to improve the standard salp swarm algorithm to solve the problem that the algorithm was easy to fall into the local optimal solution and its convergence speed was slow.Secondly, the improved salp swarm algorithm was used to optimize the parameters that affect the performance of SVM and the corresponding prediction model was built.Finally, the proposed model was compared with the particle swarm optimization SVM and the whale algorithm optimized SVM prediction model.The experimental results show that the mean square error and decision coefficient of the proposed model are 0.42 and 0.901, which are better than the other two models which verified the effectiveness of the proposed method.…”
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Prediction method of soil water content based on SVM optimized by improved salp swarm algorithm by Xiaoqiang ZHAO, Fan YANG, Zhufeng YAN

“…Aiming at the problems of low accuracy and low efficiency of traditional soil water content prediction methods, support vector machine (SVM) was used to establish a prediction model, and the soil water content prediction method based on SVM optimized was proposed by the improved salp swarm algorithm.Firstly, the opposition-based learning and chaotic optimization were introduced to improve the standard salp swarm algorithm to solve the problem that the algorithm was easy to fall into the local optimal solution and its convergence speed was slow.Secondly, the improved salp swarm algorithm was used to optimize the parameters that affect the performance of SVM and the corresponding prediction model was built.Finally, the proposed model was compared with the particle swarm optimization SVM and the whale algorithm optimized SVM prediction model.The experimental results show that the mean square error and decision coefficient of the proposed model are 0.42 and 0.901, which are better than the other two models which verified the effectiveness of the proposed method.…”
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Enhanced Framework for Lossless Image Compression Using Image Segmentation and a Novel Dynamic Bit-Level Encoding Algorithm by Erdal Erdal, Alperen Önal

“…This study proposes a dynamic bit-level encoding algorithm (DEA) and introduces the S+DEA compression framework, which enhances compression efficiency by integrating the DEA with image segmentation as a preprocessing step. …”
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Implementation of Fisher-Yates Shuffle and Fuzzy Tsukamoto in Nusantara Educational Game by Khairul Insan Karim, Chairunnisa Lamasitudju, Ryfial Azhar, Fizar Syafaat, Anisa Yulandari

“…The findings show that the Fisher-Yates Shuffle enhances challenge and engagement, while the Fuzzy Tsukamoto algorithm ensures balanced scoring, fostering motivation. …”
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Optimizing energy efficiency and indoor thermal comfort in rural self-built housing: A comparative study of GA and EA algorithms by Chen Chen, Yuanyuan Wei

“…With the growing global focus on sustainable building design, reducing energy consumption and carbon emissions while improving indoor thermal comfort has become a critical research goal. …”
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A Novel Bio-Inspired Bird Flocking Node Scheduling Algorithm for Dependable Safety-Critical Wireless Sensor Network Systems by Issam Al-Nader, Rand Raheem, Aboubaker Lasebae

“…The proposed algorithm integrates the Lyapunov function to maintain connected coverage while optimizing energy efficiency, ensuring service availability and reliability. …”
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Lithium-ion battery RUL prediction based on optimized VMD-SSA-PatchTST algorithm by Pei Tang, Zetao Qiu, Zhongran Yao, Jiahao Pan, Dashuai Cheng, Xiaoyong Gu, Changcheng Sun

“…To enhance decomposition quality, the Whale Optimization Algorithm (WOA) optimizes the number of modes K and penalty factor α by minimizing mean envelope entropy. …”
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Electric vehicle battery state of charge estimation using metaheuristic-optimized CatBoost algorithms by Mohd Herwan Sulaiman, Zuriani Mustaffa, Ahmad Salihin Samsudin, Amir Izzani Mohamed, Mohd Mawardi Saari

“…Three distinct metaheuristic algorithms were investigated: Barnacles Mating Optimizer (BMO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Whale Optimization Algorithm (WOA), each integrated with CatBoost to optimize critical parameters including learning rate, tree depth, regularization, and bagging temperature. …”
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GWO and WOA variable step MPPT algorithms-based PV system output power optimization by Abderrahim Zemmit, Abdelouadoud Loukriz, Khaled Belhouchet, Yahya Z. Alharthi, Muhannad Alshareef, Prabhu Paramasivam, Sherif S. M. Ghoneim

“…This study proposes two innovative Maximum Power Point Tracking (MPPT) algorithms based on the Whale Optimization Algorithm (WOA) and Grey Wolf Optimization (GWO). …”
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Miniaturized NIRS Coupled with Machine Learning Algorithm for Noninvasively Quantifying Gluten Quality in Wheat Flour by Yuling Wang, Chen Zhang, Xinhua Li, Longzhu Xing, Mengchao Lv, Hongju He, Leiqing Pan, Xingqi Ou

“…Through a comparative evaluation of five wavelength selection techniques, 25–30 optimal wavelengths were identified, enabling the development of optimized SVR models. The improved whale optimization algorithm iWOA-based SVR (iWOA-SVR) model exhibited the strongest predictive capability among the five optimal wavelengths-based models, achieving comparable accuracy to the full-range spectra SVR for all gluten parameters (R_P = 0.9190–0.9385, RMSEP = 0.3927–0.5743%, and RPD = 3.0424–3.2509). …”
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A Comparative Study on DG Placement Using Marine Predator and Osprey Algorithms to Enhance Loss Reduction Index in the Distribution System by Syazwan Ahmad Sabri, Siti Rafidah Abdul Rahim, Azralmukmin Azmi, Syahrul Ashikin Azmi, Muhamad Hatta Hussain, Ismail Musirin

“…The Marine Predator Algorithm (MPA) and Osprey Optimization Algorithm (OOA) are nature-inspired metaheuristic techniques used for optimizing the location and sizing of distributed generation (DG) in power distribution systems. …”
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A multi-objective optimization-based ensemble neural network wind speed prediction model by Haoyuan Ma, Chang Liu, Ziyuan Qiao, Yuan Liang, Hongqing Wang

“…Built upon the NSGA-II framework, NS-ADPOA enhances offspring generation by leveraging a probabilistic error-driven fusion of Particle Swarm Optimization (PSO) and Whale Optimization Algorithm (WOA), combining their strengths in local and global search, respectively. …”
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A Chemistry-Based Optimization Algorithm for Quality of Service-Aware Multi-Cloud Service Compositions by Mona Aldakheel, Heba Kurdi

“…The experimental results demonstrated significant improvements over existing methods, such as Genetic Algorithms (GAs), Simulated Annealing (SA), and Tabu Search (TS), across multiple performance metrics, i.e., reductions of 14–33% are observed in combined clouds, while reductions of 20–85% are observed in examined clouds, and reductions of 74–98% are observed in examined services. …”
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Real-Time Drilling Performance Optimization Using Automated Penetration Rate Algorithms with Vibration Control by Dan Sui

“…Automation has transformed process optimization across industries by enhancing efficiency, safety, and reliability while minimizing human intervention. This paper presents a model-based optimization strategy tailored for automated drilling operations, focusing on maximizing performance while maintaining operational safety. …”
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Online platform algorithmic control and gig workers’ turnover intention in China: The mediating role of relative deprivation by Shengxian Yu, Shanshi Liu, Xiaoxiao Gong, Chang-e Liu, Wei Cai

“…The results reveal that algorithmic behavioral constraints and algorithmic tracking evaluation are positively related to turnover intention, while algorithmic standardized guidance is negatively related to turnover intention. …”
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DGA-ACO: Enhanced Dynamic Genetic Algorithm—Ant Colony Optimization Path Planning for Agribots by Zhenpeng Zhang, Pengyu Li, Shanglei Chai, Yukang Cui, Yibin Tian

“…A multi-objective fitness function simultaneously optimizes path length, energy efficiency, and safety metrics, while genetic operators prevent algorithmic stagnation. …”
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A dual-domain perception gate-controlled adaptive fusion algorithm for road crack detection by Ziyang Zhang, Yong’an Feng

“…The current object detection algorithms demonstrate deficiencies in considering feature redundancy across channel-spatial dimensions, employ indiscriminate fusion strategies for multi-stage feature information, and particularly neglect the high-frequency characteristics inherent in crack features, leading to inefficient network performance and a loss of crucial information. …”
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