A Talent Cultivation and Performance Evaluation Model Based on a Fuzzy Control Algorithm by Shanshan Jiang

“…The algorithm combines an adaptive neuro-Fuzzy Inference System with Adaptive Hybrid Particle Swarm Optimization. …”
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Simultaneous high hydrogen content-synthesis gas production and in-situ CO2 removal via sorption-enhanced reaction process: modeling, sensitivity analysis and multi-objective optim... by Malihe Heravi, Mahdi Bayat, Mohammad Reza Rahimpour

“…As the last part, non-dominated sorting genetic algorithm-II is applied to perform multi-objective optimization of the SE-SMR.…”
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Parameter Adaptive Manta Ray Foraging Optimization for Global Continuous Optimization Problems and Parameter Estimation of Solar Photovoltaic Models by Zhentao Tang, Kaiyu Wang, Yongxuan Yao, Mingxin Zhu, Lan Zhuang, Huiqin Chen, Jing Li, Li Yan, Shangce Gao

“…Furthermore, to enhance population diversity and avoid premature convergence, a randomly selected individual from the top $$ G $$ G high-quality solutions replaces the current best individual in the somersault foraging behavior. Based on these improvements, a parameter adaptive manta ray foraging optimization (PAMRFO) algorithm is developed. …”
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Optimizing Multi-Echelon Delivery Routes for Perishable Goods with Time Constraints by Manqiong Sun, Yang Xu, Feng Xiao, Hao Ji, Bing Su, Fei Bu

“…The results demonstrate that the initial solutions obtained through the k-medoids clustering algorithm based on spatio-temporal distance improved the overall cost optimization by 1.85% and 4.74% compared to the other two algorithms. …”
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Multi-objective multi-workflow task offloading based on evolutionary optimization by Teliekebieke Misha, Lisheng Sun, Zheng-yi Chai

“…Simulation results demonstrate that our algorithm optimally balances delay and energy consumption requirements compared to existing methods, while enhancing the diversity and convergence of non-dominated solutions.…”
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Application of deep reinforcement learning in parameter optimization and refinement of turbulence models by Zhan Zhang

“…The DDPG algorithm was used for parameter optimization, and model parameters were gradually adjusted to minimize wind pressure simulation errors. …”
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Evaluating Task Optimization and Reinforcement Learning Models in Robotic Task Parameterization by Michele Delledonne, Enrico Villagrossi, Manuel Beschi, Alireza Rastegarpanah

“…The results demonstrate that although RL models improve task optimization efficiency by 95%, they still need more flexibility. …”
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Robust Improvement Strategy for Power Grid Hosting Capacity with Integration of High Proportion of Renewable Energy by Yangqing DAN, Lei WANG, Weimin ZHENG, Jiahui WU, Chenxuan WANG, Gaowang YU

“…And then, based on the two-stage robust optimization theory, a strategy model for improving the hosting capacity of the power grid is constructed, and the column and constraint generation (C&CG) algorithm is used to solve the model. …”
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Wakeup strategy based on multi-objective optimization for fixed relay nodes by Xue-bin MA, Ai-li LI, Xiao-juan ZHANG

“…In order to deal with the “tidal effect” when people move in the city and solve the problem of high energy consumption of fixed relay nodes in opportunistic networks,a wakeup strategy of multi-objective optimization was proposed,which made use of the message forward ability and energy consumption of fixed relay nodes.This strategy used energy efficiency as the indicator to make the nodes awake,and deployed a network revenue-energy consumption model to resolve the contradiction between energy consumption and message forward ability.As the selection problem of awake relay nodes was a NP-hard problem,genetic algorithm was used to select proper fixed relay nodes to keep awake.In this process,selection operator was improved to make the algorithm converge to solution space quickly.Experiments show that the proposed wakeup strategy can guarantee the successful rate of message transmission and improve the average message forwarding capabilities of fixed relay nodes by consuming a unit energy.…”
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Reliability Optimization Model of Stop-Skipping Bus Operation with Capacity Constraints by Zhenhua Mou, Hu Zhang, Shidong Liang

“…The objective function is to minimize the total costs of bus operation system. Besides, a Genetic Algorithm combined with Monte Carlo Simulation method is defined and implemented to solve the reliability optimization model. …”
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Optimization design on process parameters of copper wire bonding for power modules by HU Biao, CHENG Lanxian, LI Zhenling, DAI Xiaoping

“…In order to improve the copper wire bonding performance of the power modules, an optimization design scheme of process parameters for copper wire bonding was proposed by using the six-factor five-level orthogonal test method, and combining the back propagation (BP) neural network and genetic algorithm (GA). …”
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Improving with Hybrid Feature Selection in Software Defect Prediction by Muhammad Yoga Adha Pratama, Rudy Herteno, Mohammad Reza Faisal, Radityo Adi Nugroho, Friska Abadi

“…Feature selection is often used by some researchers to overcome these problems, because these methods have an important function in the process of reducing data dimensions and eliminating uncorrelated attributes that can cause noisy. Naive Bayes algorithm is used to support the process of determining the most optimal class. …”
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A Mobile Wireless Sensor Coverage Optimization Method for Bridge Monitoring by Cong Mu, Jiguang Yang, Jiuyuan Huo

“…Aiming at the problem of resource allocation optimization of heterogeneous mobile wireless sensor (HMWS) networks in bridge structural health monitoring, this study proposes an enhanced coverage strategy for heterogeneous sensors based on an improved Hiking Optimization Algorithm (HOA). …”
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Presenting the detection algorithm of all types of vessels in the Persian Gulf region using radar images in order to improve the security of navigation by Ali Hanafi, Mehdi Keykhaee

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A monthly runoff prediction model based on ICEEMD-L-SHADE-SRU by Ziyang Kou, Yang Yang, Zhiping Li, Xiaoshuang Fu

“…L-SHADE is employed to complete the parameter optimization of the SRU. The results showed that ICEEMD-L-SHADE-SRU achieved the best performance in runoff prediction, showing distinct improvements when compared to tested models in terms of both NSE (0.91–0.93) and QR (72%–74%). …”
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Assessment and optimization of power networks based on a dual-loop model by Junchi Cui, Zhaoyang Guo, Shuliang Wang, Bo Song

“…The framework combines network restoration strategies with reconfiguration to improve power network resilience. Initially, a network model and its corresponding resilience index are given, and the recovery capabilities of different repair strategies are analyzed to identify the optimal repair strategy. …”
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A survey on autonomous navigation for mobile robots: From traditional techniques to deep learning and large language models by Abderrahim Waga, Said Benhlima, Ali Bekri, Jawad Abdouni, Fatima Zahrae Saber

“…The review extends to modern metaheuristic algorithms, including genetic algorithms (GA), particle swarm optimization (PSO), and ant colony optimization (ACO). …”
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Study of Fair Strategy for Merchant Self-Operated Takeaway Delivery Based on Delivery Plan Optimization by Jing Chen, Chengbo Guo, Jiahua Kou, Jiali Du, Shufa Sun, Yanling Guo

“…This study presents a mathematical model for merchant-operated takeaway delivery, using an improved ant colony algorithm integrated with K-means to cluster customer locations and determine optimal routes. …”
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Optimal Modeling of Wireless LANs: A Decision-Making Multiobjective Approach by Tomás de Jesús Mateo Sanguino, Jhon Carlos Mendoza Betancourt

“…To reduce this gap, this paper describes an optimization algorithm—based on evolutionary strategy—created as an aid for decision-making prior to the real deployment of wireless LANs. …”
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RE-YOLOv5: Enhancing Occluded Road Object Detection via Visual Receptive Field Improvements by Tianyu Li, Xuanrui Xiong, Yuan Zhang, Xiaolin Fan, Yushu Zhang, Haihong Huang, Dan Hu, Mengting He, Zhanjun Liu

“…The proposed method achieves a mean average precision (mAP) of 82.04% on KITTI, representing an improvement of 2.34% over the baseline model. For heavily occluded objects on CityPersons, the Log Average Miss Rate (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>MR</mi><mrow><mo>−</mo><mn>2</mn></mrow></msup></semantics></math></inline-formula>) is reduced to 40.31%, which is a decrease of 9.65% compared to the baseline. …”
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