An Improved Adaptive Simulated Annealing Particle Swarm Optimization Algorithm for ARAIM Availability by Ershen Wang, Xiaozhu Shi, Xidan Deng, Jing Gao, Wei Zhang, Huan Wang, Song Xu

“…Aiming at this problem, we proposed an adaptive simulated annealing particle swarm optimization (ASAPSO) algorithm to redistribute integrity and continuity risks and establish a protection level optimization model. …”
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AOAFS: A Malware Detection System Using an Improved Arithmetic Optimization Algorithm by Rafat Alshorman, Bilal H. Abed-alguni, Yaqeen E. Alqudah

“…Finally, Dynamic Opposition-based Learning is utilized to improve the mutation capability of the AOAFS. Several malware datasets were used to compare the AOAFS to four popular Machine Learning algorithms and eight famous wrapper-based optimization algorithms. …”
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Application of Improved Whale Algorithm to Optimize Dephosphorization Process Parameters in Converter Steelmaking by Congrui Wu, Yueping Kong

“…This study addresses process parameter optimization challenges in converter steelmaking by proposing an improved multi-objective whale optimization algorithm (IMOWOA) that synergistically integrates metallurgical thermodynamics with data-driven modeling. …”
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Distributed photovoltaic reactive power control strategy based on improved multiobjective particle swarm algorithm by Hongli Liu, Li Hao, Li Ji, Shao Lei

“…When the algorithm is compared with three other algorithms, such as nondominated sorting genetic algorithm‐II, the results show that it reduces the network loss by about 25% and significantly improves the voltage fluctuation rate.…”
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Advances in the Application of Intelligent Algorithms to the Optimization and Control of Hydrodynamic Noise: Improve Energy Efficiency and System Optimization by Maosen Xu, Bokai Fan, Renyong Lin, Rong Lin, Xian Wu, Shuihua Zheng, Yunqing Gu, Jiegang Mou

“…In recent years, intelligent algorithms represented by data-driven algorithms and heuristic algorithms have gradually emerged, showing great potential for development in hydrodynamic noise optimization applications. …”
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Uncertainty prediction of wind speed based on improved multi-strategy hybrid models by Xinyi Xu, Shaojuan Ma, Cheng Huang

“…Due to insufficient traditional wind speed interval prediction methods for mining nonlinear features, in this paper, a novel interval prediction method was proposed by combining improved wavelet threshold and deep learning (BiTCN-BiGRU) with the nutcracker optimization algorithm (NOA). …”
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Internet of things driven object detection framework for consumer product monitoring using deep transfer learning and hippopotamus optimization by Amnah Alshahrani, Mukhtar Ghaleb, Hany Mahgoub, Achraf Ben Miled, Nojood O. Aljehane, Mohammed Yahya Alzahrani, Hasan Beyari, Sultan Alanazi

“…Moreover, the convolutional autoencoder (CAE) model is implemented for classification. Additionally, the hippopotamus optimization algorithm (HOA)-based hyperparameter selection model is implemented to improve the classification result of the CAE technique. …”
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SGA-Driven feature selection and random forest classification for enhanced breast cancer diagnosis: A comparative study by Abrar Yaqoob, Navneet Kumar Verma, Mushtaq Ahmad Mir, Ghanshyam G. Tejani, Nashwa Hassan Babiker Eisa, Hind Mamoun Hussien Osman, Mohd Asif Shah

“…Abstract In this study, we propose a novel approach for breast cancer classification that integrates the Seagull Optimization Algorithm (SGA) for feature selection with the Random Forest (RF) classifier for effective data classification. …”
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Economy Optimization by Multi-Strategy Improved Whale Optimization Algorithm Based on User Driving Cycle Construction for Hybrid Electric Vehicles by Jie Ma, Mingzhang Pan, Wei Guan, Zhiqing Zhang, Jingcheng Zhou, Nianye Ye, Haifeng Qin, Lulu Li, Xingjia Man

“…Finally, a multi-strategy improved whale optimization algorithm (MIWOA) is proposed, which can guarantee better economy of HEV compared with the original whale optimization algorithm (WOA). …”
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Robust Path Tracking Control with Lateral Dynamics Optimization: A Focus on Sideslip Reduction and Yaw Rate Stability Using Linear Quadratic Regulator and Genetic Algorithms by Karrar Y. A. Al-bayati, Ali Mahmood, Róbert Szabolcsi

“…To address this issue, this study proposes the optimization of the linear quadratic regulator (LQR) control system by using the genetic algorithm (GA) to support the vehicle in following the predefined path accurately, minimizing the sideslip, and stabilizing the vehicle’s yaw rate. …”
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Improving Parameter Estimation of Fuel Cell Using Honey Badger Optimization Algorithm by Rolla Almodfer, Mohammed Mudhsh, Samah Alshathri, Laith Abualigah, Laith Abualigah, Mohamed Abd Elaziz, Mohamed Abd Elaziz, Mohamed Abd Elaziz, Khurram Shahzad, Mohamed Issa

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Optimization Design for Reliability of the Oscillating Follower Disk Cam Mechanism Based on Improved Hunter-Prey Optimization Algorithm by Chao Wang, Wei Peng

“…To maximize the motion reliability of the mechanism, an improved Hunter Prey Optimization (IHPO) algorithm was proposed to identify the optimal dimensional parameters of the oscillating follower disk cam mechanism. …”
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Improvement strategies for heuristic algorithms based on machine learning and information concepts: a review of the seahorse optimization algorithm by Shixing Zheng

“…Experimental results demonstrate that the improved SHO algorithm, integrating the logistic-KNN inertia weight optimization strategy and the entropy-based crossover-mutation mechanism, exhibits significant advantages in terms of convergence speed, solution accuracy, and algorithm stability. …”
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Multi-constraints QoS routing optimization based on improved immune clonal shuffled frog leaping algorithm by Yi LU, Mengying XU, Jie ZHOU

“…Aiming at the multi-constraint routing problem,a mathematical model was designed,and an improved immune clonal shuffled frog leaping algorithm (IICSFLA) was proposed,which combined immune operator with traditional SFLA.Under the constraints of bandwidth,delay,packet loss rate,delay jitter and energy cost,total energy cost from the source node to the terminal node was computed.The proposed algorithm was used to find an optimal route with minimum energy cost.In the simulation,the performance of IICSFLA with adaptive genetic algorithm and adaptive ant colony optimization algorithm was compared.Experimental results show that IICSFLA solves the problem of multi-constraints QoS unicast routing optimization.The proposed algorithm avoids local optimum and effectively reduces energy loss of data on the transmission path in comparison with adaptive genetic algorithm and adaptive ant colony optimization algorithm.…”
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Multi-Stage and Multi-Objective Optimization of Solar Air-Source Heat Pump Systems for High-Rise Residential Buildings in Hot-Summer and Cold-Winter Regions by Zhen Wang, Jiaxuan Wang, Chenxi Lv

“…When optimizing the renewable energy system configuration of residential buildings for solar-air source heat pump systems, the optimization algorithm and the setting of parameter ranges will have an impact on the optimization results. …”
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Towards Automated Cadastral Map Improvement: A Clustering Approach for Error Pattern Recognition by Konstantinos Vantas, Vasiliki Mirkopoulou

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Artificial Intelligence Algorithm for Optimal Time Series Data Model by Kang Wang

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Advanced Computational Methods for Mitigating Shock and Vibration Hazards in Deep Mines Gas Outburst Prediction Using SVM Optimized by Grey Relational Analysis and APSO Algorithm by Xiang Wu, Zhen Yang, Dongdong Wu

“…Moreover, adaptive particle swarm optimization (APSO) was used to optimize the penalty factor and kernel parameters of the support vector machine to improve the global search ability and avoid the occurrence of the local optimal solutions. …”
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Multi-objective optimization of current-assisted splitting spinning of small module tooth-shaped part based on the combination of BP neural network and NSGA-II algorithm by Zhou Haoyang, Xia Qinxiang, Xiao Gangfeng, Chen Can

“…The results show that the material at the tooth tip along the radial direction is in the state of tensile stress along radial and compressive stresses along tangential and axial directions, which promotes the radial flowing of the material and is beneficial the tooth filling of SMTSPs; the tooth saturation increases obviously under pulse current comparing without pulse current; the BPNN combined with the NSGA-II algorithm can reliably optimize the process parameters of the CASS, improving the forming quality of SMTSPs; experiments verified the feasibility of the process and the accuracy of the predictive model based on the optimization results.…”
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Optimized feature selection and advanced machine learning for stroke risk prediction in revascularized coronary artery disease patients by Yong Si, Armin Abdollahi, Negin Ashrafi, Greg Placencia, Elham Pishgar, Kamiar Alaei, Maryam Pishgar

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