An optimized feature selection using triangle mutation rule and restart strategy in enhanced slime mould algorithm by Ibrahim Musa Conteh, Gibril Njai, Abass Conteh, Qingguo Du

“…This paper proposes an improved feature selection method based on an improved Slime Mould Algorithm (SMA), called the Triangular Mutation Rule Restart Strategy Slime Mould Algorithm (TRSMA), to overcome some of the shortcomings of the SMA, including premature convergence, poor population diversity, and local optima entrapment. …”
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Optimizing snow property forecasts over the tibetan plateau through hybrid assimilation of satellite precipitation and water vapor radiances using WRF model configured with Noah-MP by Jing Ren, Chunlin Huang, Jinliang Hou, Ying Zhang, Ling Yang

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Optimization of urban green space in Wuhan based on machine learning algorithm from the perspective of healthy city by Xuechun Zhou, Xiaofei Zou, Wenzuixiong Xiong

“…Adopting a healthy city development perspective, the research aims to assess the impact of green space optimization on urban health, economic performance, and social structure.MethodsA multivariable model was constructed using random forest and Support Vector Machine (SVM) algorithms to evaluate the influence of key indicators on urban green space. …”
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Using crafted features and polar bear optimization algorithm for short-term electric load forecast system by Mansi Bhatnagar, Gregor Rozinaj, Radoslav Vargic

“…Optimized hyperparameters with PBO effectively decreased RMSE, MAE, and MAPE and improved the model prediction, showcasing the capability of the PBO in hyperparameter tuning for STLF. …”
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Path planning algorithm for WCE with joint energy replenishment and data collection based on multi-objective optimization by Zhenchun WEI, Renhao SUN, Zengwei LYU, Jianghong HAN, Lei SHI, Junyi XU

“…Considering limited energy of the wireless charging equipment (WCE) in wireless rechargeable sensor network,an energy replenishment strategy and a data collection strategy are designed.On the basis of these,a path planning model for WCE with functions of joint energy replenishment and data collection based on multi-objective optimization is constructed with two optimization objectives,maximizing the total energy utility of WCE and minimizing the average delay of data transmission of all the sensor nodes in the network.To deal with it,a multi-objective ant colony optimization algorithm based on elitist strategy was proposed,where the state transition strategy and the pheromone updating strategy were improved.Then,the Pareto set was obtained in terms of this multi-objective optimization problem.The parameter setting of ant colony algorithm’s effects on the proposed algorithm were analyzed under 20 sensor nodes.50 groups of contrastive experiments show that the average number of energy utilization obtained by ES-MOAC algorithm is 4.53% higher than that of NSGA-II algorithm.The average number of average delay of all node data transmission obtained by ES-MOAC algorithm is 5.12% lower than that of NSGA-II algorithm.…”
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Dynamic response force control of electrohydraulic servo actuator of active suspension based on intelligent optimization algorithm. by Qinghe Guo, Mengchao Wang, Renjun Liu, Yurong Chen, Shenghuai Wang, Hongxia Wang

“…To address these challenges, a fractional-order PID (FOPID) controller optimization method based on the Multi-Strategy Improved Beluga Whale Optimization (MSIBWO) algorithm is proposed. …”
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Critical sliding surface location method for anisotropic slope based on anisotropic yield criterion and optimization algorithm by Zhenfu Zhang, Yongjun Zhang, Sijia Liu, Mingzhong Gao, Fei Liu, Jintao Wang

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Research on optimization design method of ship's living compartment layout based on multi-population genetic algorithm by MA Lin, CHEN Dengkai, SHI Hongqi, LIAO Wenyi

“…It combines emergency evacuation needs to establish a compartment layout optimization model. Additionally, adaptive improvements are made to the genetic operations of the multi-population genetic algorithm, enhancing its applicability to the optimization design of multi-layered ship compartments. …”
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Optimizing Solid Rocket Missile Trajectories: A Hybrid Approach Using an Evolutionary Algorithm and Machine Learning by Carlo Ferro, Matteo Cafaro, Paolo Maggiore

“…This paper introduces a novel approach for modeling and optimizing the trajectory and behavior of small solid rocket missiles. …”
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Optimization of energy consumption in mobile Ad-Hoc networks with a swarm intelligence-based ABC algorithm by Vijay U. Rathod, Shyamrao V. Gumaste, Ramakrishna Guttula, Shrikant Zade, Ramanpreet Singh

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AdaSpline-Net for Improved Short-Term Solar Irradiance Forecasting by Ngiap Tiam Koh, Anurag Sharma, Jianfang Xiao, Cheng Siong Chin, Chin Jun Xing, Wai Lok Woo

“…This research highlights the potential of optimized B-spline activation functions to improve the accuracy and dependability of neural network-based forecasting models.…”
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An improved preconditioned conjugate gradient method for unconstrained optimization problem with application in Robot arm control by Lawal Muhammad, Mohammad Y. Waziri, Ibrahim Mohammed Sulaiman, Issam A.R. Moghrabi, Aceng Sambas

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An Intelligent 5G Unmanned Aerial Vehicle Path Optimization Algorithm for Offshore Wind Farm Inspection by Congxiao Jiang, Lingang Yang, Yuqing Gao, Jie Zhao, Wenne Hou, Fangmin Xu

“…We propose a novel Sea Wind-Aware Improved A*-Guided Genetic Algorithm (SWA-IAGA), which integrates an improved A* algorithm to guide the genetic algorithm for efficient path planning, with the assistance of relevant graphical knowledge. …”
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Enhanced vehicle routing for medical waste management via hybrid deep reinforcement learning and optimization algorithms by Norhan Khallaf, Osama Abd-El Rouf, Abeer D. Algarni, Mohy Hadhoud, Ahmed Kafafy

“…This approach not only improved performance but also enhanced environmental sustainability, making it the most effective and challenging solution among all the algorithms used in the study.…”
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MULTIDISCIPLINARY DESIGN OPTIMIZATION OF TURBINE STAGE BASED ON IMPROVED BI-LEVEL INTEGRATED SYSTEM SYNTHESIS by ZHANG LiZhang, YIN ZeYong, MI Dong, QIAN ZhengMing, JIA ZhiGang

“…To improve the optimization efficiency of turbine stage optimization,an improved optimization strategy based on Bi-level integrated system synthesis（ BLISS2000） procedure to the multidisciplinary design optimization（ MDO） of turbine stage was proposed. …”
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Optimization and Multimachine Learning Algorithms to Predict Nanometal Surface Area Transfer Parameters for Gold and Silver Nanoparticles by Steven M. E. Demers, Christopher Sobecki, Larry Deschaine

“…However, the expansion and testing of this model for nanoparticles of different metal composition is needed to develop a greater variety of nanosensors for medical and commercial applications. …”
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Hybrid Deep Neural Network Optimization with Particle Swarm and Grey Wolf Algorithms for Sunburst Attack Detection by Mohammad Almseidin, Amjad Gawanmeh, Maen Alzubi, Jamil Al-Sawwa, Ashraf S. Mashaleh, Mouhammd Alkasassbeh

“…The results demonstrate the effectiveness and robustness of the suggested hybrid DNN model. Furthermore, an extensive analysis was conducted by evaluating the suggested hybrid PSO–GWO along with other hybrid optimization techniques, namely Genetic Algorithm (GA), Differential Evolution (DE), and Ant Colony Optimization (ACO). …”
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Multi-Objective Optimization Design of Ship Propulsion Shafting Based on Response Surface Methodology and Genetic Algorithm by ZHANG Cong, SHU Bingnan, ZHANG Jiangtao, JIN Yong

“…In order to reduce the power loss of the transmission equipment, enhance the transmission efficiency of the propulsion shafting, and improve the vibration performance of the shafting, a multi-objective optimization design of a ship shafting experimental platform is performed based on the response surface model and genetic algorithm. …”
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Efficient identification of photovoltaic cell parameters via Bayesian neural network-artificial ecosystem optimization algorithm by Bo Yang, Ruyi Zheng, Yucun Qian, Boxiao Liang, Jingbo Wang

“…Furthermore, the AEO algorithm is utilized to identify unknown parameters in the single-diode model (SDM), double-diode model (DDM), and three-diode model (TDM). …”
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Prediction of Soil Liquefaction Using a Multi-Algorithm Technique: Stacking Ensemble Techniques and Bayesian Optimization by Long Tsang, Mahdi Akbari, Pouyan Fakharian

“…A Bayesian optimization method is also used to improve the accuracy of the predictions of soil liquefaction by adjusting the hyperparameters of these four classification algorithms. …”
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