A FPGA Accelerator of Distributed A3C Algorithm with Optimal Resource Deployment by Fen Ge, Guohui Zhang, Ziyu Li, Fang Zhou

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Optimization of Combat Resource Allocation Based on Restricted Tournament Selection Social Genetic Algorithm by Shandong Yuan, Yun Ren, Han Zhou, Yongjing Cheng, Kai Yan

“…In addition, we innovatively incorporate the concept of ‘group effect’ from sociology, adding a socialization operator to the algorithm to accelerate convergence and improve the quality of optimal solutions. …”
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Load optimization of cogeneration units based on intuitive multi-objective fish swarm algorithm by Xueqiang Shen, Jiaxin Wang

“…A cogeneration unit model incorporating operational characteristics and historical data demonstrates the method’s efficacy: multi-objective balance is maintained across iterations, achieving a 1.41% thermoelectric load increase and 1.54% optimal coal consumption reduction. The algorithm reduces heat/electricity losses and operational costs under diverse conditions while enhancing load utilization rates. …”
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Optimization Design Method of Pipe-Insulating Joints Based on Surrogate Model and Genetic Algorithm by Chen Guo, Zheng Yang, Jianbo Dong, Yanchao Yue, Linjun Tian, Ping Ma

“…This improves the computational efficiency of the optimization algorithm by establishing a surrogate model, which can be used to optimize the dimensions of insulation joints.…”
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Trajectory Similarity Algorithm Based on DTW and Trajectory Point Compression by GAO Wei, QIAN Chengyang, ZHANG Qi, XIE Hongquan

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Intelligent Modeling and Experimental Investigation of the Collar's Impact on Reducing Scour around the Spur Dike by Hojat Karami, Alireza Rezaei, Amin Atarodi

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Dynamic Optimization of Xylitol Production Using Legendre-Based Control Parameterization by Eugenia Gutiérrez, Marianela Noriega, Cecilia Fernández, Nadia Pantano, Leandro Rodriguez, Gustavo Scaglia

“…This dimensionality reduction improves the robustness of the optimization by decreasing the likelihood of convergence to local optima while also reducing the computational cost and enhancing feasibility for implementation. …”
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Research on Early Diagnosis Methods for Broiler Chicken Diseases Based on Swarm Intelligence Optimization Algorithms and Random Forest by X Peng, C Chen, L Yu, X Kong, B Sun

“…A baseline Random Forest (RF) model achieved 94.01% diagnostic accuracy for broiler diseases. To optimize performance, we developed RF_WOA_DBO-an integrated algorithm combining RF with enhanced Whale Optimization Algorithm (WOA) for global feature selection and modified Dung Beetle Optimizer (DBO) for local parameter tuning. …”
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Performance optimization of electrical equipment in high-altitude photovoltaic power stations based on PSO–MOEAD algorithm by Zhijun Xiao

“…To reduce energy consumption and operation and maintenance costs, a hybrid algorithm based on particle swarm optimization and multi-objective evolutionary decomposition algorithm is proposed in this study. …”
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Low-carbon economic dispatching of integrated energy system based on improved white shark algorithm by LI Haobo, CUI Shuangxi, FAN Weijie

“…The white shark algorithm is improved by integrating directed differential mutation and other strategies to solve the low-carbon economic scheduling model of the integrated energy system, and the optimal scheduling scheme of each time period is obtained by combining the advantages and disadvantages of the solution distance method. …”
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GVDF-RRT*: An Improved F-RRT* Path Planning Algorithm Based on Generalized Voronoi Diagram by Yitao Zhong, Xiaojing Zhu, Jianfang Huang, Yaokun Ye, Zhaoming Wang, Yuhuai Wang

“…Finally, simulations in three test environments show that, compared to RRT*, Q-RRT*, and F-RRT*, the GVDF-RRT* algorithm reduces the initial number of sampled nodes by 47.42%-76.57%, the initial time by 37.07%-86.00%, and the initial path cost by 0.47%-0.91%, while significantly improving the success rate in narrow passage environments. …”
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An Improved Symbiosis Particle Swarm Optimization for Solving Economic Load Dispatch Problem by Jianxia Zhang, Jianxin Zhang, Feng Zhang, Minglu Chi, Linbin Wan

“…In addition, two different kinds of practical examples were also adopted for algorithm evaluation. From the simulation results, it can be seen clearly that the costs of electric-power generation gained were the lowest compared with the results of particle swarm optimization algorithm, improved chaos particle swarm optimization algorithm, and symbiotic organisms search algorithm, well demonstrating the effectiveness of the improved symbiosis particle swarm optimization algorithm in solving the economic load dispatch problem.…”
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Optimizing energy cost in the residential sector through home energy management systems in a smart grid environment by Nabeeha Qayyum, Umar Jamil, Anzar Mahmood

“…The results show that GA achieved a 48% cost reduction compared to PSO, with significant peak load reduction and improved energy optimization when integrated with PV systems. …”
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Evaluating the Efficiency of Gray Wolf Optimization and Colonial Competition Algorithm in Load Balancing of Distributed Systems by Asghar Molaei-Yeznabad, Amirhossein Dehghani

“…Recent years have seen the development of numerous resource allocation algorithms aimed at reducing costs and energy consumption in distributed systems. …”
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An Improved Spider Wasp Optimizer for Green Vehicle Route Planning in Flower Collection by Mengxin Lu, Shujuan Wang

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Grouping control of electric vehicles based on improved golden eagle optimization for peaking by Yang Yu, Yuhang Huo, Shixuan Gao, Qian Wu, Mai Liu, Xiao Chen, Xiaoming Zheng, Xinlei Cai

“…Second, the design of IGEO has improved the global exploration and local development capabilities of the golden eagle optimizer (GEO) algorithm. …”
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Image Reconstruction Algorithm Based on Extreme Learning Machine for Electrical Capacitance Tomography by SU Ziheng, CHEN Deyun, WANG Lili

“…Aiming at the problem that the traditional ECT is not accurate in complex situations, this paper proposes a depth learning based inversion method Through the improvement and optimization of the traditional extreme learning machine, the image feature information obtained by the reconstructed image method is used as the training data, and the result obtained by inputting the data into the predictive model is used as the prior information The cost function is used to encapsulate the prior knowledge and domain expertise, and spatial regularizers and time regularizers are introduced to enhance sparsity The separated Bregman (SB) algorithm and the iterative shrinkage threshold (FIST) method are used to solve the specified cost function The final imaging result is obtained The simulation results show that the image reconstructed by this method has less than 10% error compared with the original flow pattern, and reduces artifacts and distortion, which improves the reconstructed image quality…”
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AI-driven genetic algorithm-optimized lung segmentation for precision in early lung cancer diagnosis by Yahia Said, Riadh Ayachi, Mouna Afif, Taoufik Saidani, Saleh T. Alanezi, Oumaima Saidani, Ali Delham Algarni

“…This study presents an advanced AI-driven framework, optimized through genetic algorithms, for precise lung segmentation in early cancer diagnosis. …”
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An intelligence technique for route distance minimization to store and marketize the crop using computational optimization algorithms by Saikat Banerjee, Abhoy Chand Mondal

“…This research aims to develop connectivity across many cold storage facilities utilizing the traveling salesperson problem algorithm. Various computational intelligence algorithms such as Greedy Algorithm, Simulated Annealing, 2-opt Algorithm, Particle Swarm Optimization, and Ant Colony Optimization are employed to determine the minimum route. …”
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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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