Innovative application of particle swarm algorithm in the improvement of digital enterprise management efficiency by Shengnan Zhang

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A hybrid model for short-term offshore wind power prediction combining Kepler optimization algorithm with variational mode decomposition and stochastic configuration networks by Bingbing Yu, Yonggang Wang, Jun Wang, Yuanchu Ma, Wenpeng Li, Weigang Zheng

“…Compared with the basic VMD model, the data decomposition efficiency of the optimized VMD model has been improved by 28.86%. …”
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Enhancing Continuum Robotics Accuracy Using a Particle Swarm Optimization Algorithm and Closed-Loop Wire Transmission Model for Minimally Invasive Thyroid Surgery by Na Guo, Haoyun Zhang, Xingshuai Li, Xinnan Cui, Yang Liu, Jiachen Pan, Yajuan Song, Qinjian Zhang

“…By integrating rigid mechanisms and continuum joints within a closed-loop cable-driven framework, the system achieves a balance between flexibility in narrow spaces and operational stiffness. To tackle kinematic model inaccuracies caused by manufacturing errors, an innovative joint decoupling strategy combined with the Particle Swarm Optimization (PSO) algorithm is developed to dynamically identify and correct 19 critical parameters. …”
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Research on Parameter Extraction Method of Photovoltaic Module Based on Improved Hybrid Algorithm by Haitao Wu, Zhou Shang

“…Firstly, the analytical method is applied to simplify the equivalent circuit model and improve the efficiency of the algorithm. …”
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Improved marine predator MPPT algorithm for photovoltaic systems in partial shading conditions by Hanbo Zheng, Qi Du, Shuqin Mo, Tuanfa Qin, Shusheng Wang, Zhe Li

“…This algorithm is optimized and improved accordingly based on the Marine Predator Algorithm (MPA). …”
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Resource allocation strategies for improved mayfly algorithm in cognitive heterogeneous cellular network by Damin ZHANG, Yi WANG, Chengcheng ZOU, Peiwen ZHAO, Linna ZHANG

“…Aiming at the optimization of uplink resource allocation in cognitive heterogeneous cellular networks, a resource allocation algorithm based on improved discrete mayfly algorithm was proposed.In the cognitive heterogeneous cellular network model, the power control strategy was introduced to control the interference suppression of transmitted power, and the improved discrete mayfly algorithm was used to optimize and solve the optimal distribution scheme based on the user’s quality of service (QoS) requirements and interference threshold constraints to maximize the energy efficiency (EE).In order to improve the convergence rate and search ability of the mayfly algorithm, the dynamic adaptive weights of incomplete Gamma and Beta distribution functions and the golden sine position updating strategy were introduced.The simulation results show that the closed-loop power control based on SINR can dynamically adjust the transmitting power of users and effectively restrain the interference between users.The GSWBMA has good optimization efficiency and convergence performance to solve the resource allocation problem, effectively improve the energy efficiency of the system and the transmission rate of users, and ensure the QoS requirements of users.…”
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Prediction of China’s Silicon Wafer Price: A GA-PSO-BP Model by Jining Wang, Hui Chen, Lei Wang

“…This study addresses the issue by enhancing the BP model. It integrates the principles of genetic algorithm (GA) with particle swarm optimization (PSO) to develop a new model called the GA-PSO-BP. …”
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Multi-Objective Improved Differential Evolution Algorithm-Based Smart Home Energy Management System Considering Energy Storage System, Photovoltaic, and Electric Vehicle by Mina GhasemiGarpachi, Moslem Dehghani, Mokhtar Aly, Jose Rodriguez

“…A multi-objective improved differential evolution algorithm is used to solve the HEMSs. …”
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Research on Multi-peak MPPT of Photovoltaic Array Based on Improved ICA Algorithm by ZANG Xiaodi, LIU Lu

“…Secondly, the adaptive revolution factor is introduced to improve the local optimization ability of the algorithm, and the optimal value selection mechanism is used to retain the excellent factor of the original empire to improve the convergence speed of the algorithm. …”
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Performance Assessment of Solar-Transformer-Consumption System Using Neural Network Approach by Ritu Gupta, Ekata, C.M. Batra

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Forecasting and decision making of firm’s financial indicators based on the SSA-MLP-BPNN model by Xin Xu

“…By comparing the prediction results of SSA-MLP-BP model with other optimization algorithms, it is found that the SSA optimization algorithm performs superiorly in improving the performance of the MLP-BP model, and it is easier to find the global optimal solution, which improves the prediction accuracy of the model. …”
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Optimization of Enterprise Labor Resource Allocation Based on Quality Optimization Model by Gaoyang Liang, Long Xu, Liang Chen

“…The problem of the highest skill level of labor resources allocated to all projects of the enterprise is designed, and algorithms are designed to achieve the optimization of project quality through the optimal allocation of labor resources. …”
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Integrating Explainable Artificial Intelligence With Advanced Deep Learning Model for Crowd Density Estimation in Real-World Surveillance Systems by Sultan Refa Alotaibi, Hanan Abdullah Mengash, Mohammed Maray, Faiz Abdullah Alotaibi, Abdulwhab Alkharashi, Ahmad A. Alzahrani, Moneerah Alotaibi, Mrim M. Alnfiai

“…This study proposes an Osprey Optimization Algorithm with Deep Learning Assisted Crowd Density Detection and Classification (OOADL-CDDC) technique for smart video surveillance systems. …”
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Deep learning and fuzzy algorithm in improving the effectiveness of college English translation teaching by Biao Kong, Che He

“…This study combines deep learning and fuzzy algorithm to improve the effect of translation teaching. …”
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Minimum cost of job assignment in polynomial time by adaptive unbiased filtering and branch-and-bound algorithm with the best predictor by Jeeraporn Werapun, Witchaya Towongpaichayont, Anantaporn Hanskunatai

“…The minimum cost of job assignment (Min-JA) is one of the practical NP-hard problems to manage the optimization in science-and-engineering applications. …”
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Research on Collaborative Optimization Strategy of Railway Signal Nonlinear Control System Based on BBO Algorithm and Multi-objective Optimization by Xue Li, Yixuan Yang, Zheng Li, Hui He

“…The research constructs a mathematical model with multiple objective constraints, accurately identifies the adaptation shortcomings of the existing system in dynamic scenarios, and then employs a Biogeography-Based Optimization (BBO) algorithm for global optimization of control parameters. …”
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Marine Voyage Optimization and Weather Routing with Deep Reinforcement Learning by Charilaos Latinopoulos, Efstathios Zavvos, Dimitrios Kaklis, Veerle Leemen, Aristides Halatsis

“…These algorithms are computationally costly, so we split optimization into an offline phase (costly pre-training for a route) and an online phase where the algorithms are fine-tuned as updated weather data become available. …”
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Sensor-layout Optimization of Autonomous Vehicle Based on Perceptual Area Coverage by AN Tai, DIAO Wangcheng

“…Finally, a particle swarm optimization algorithm was designed to solve the model, and the correctness of the model and the effectiveness of the optimization method were verified by computer experiment and simulation.…”
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Optimization of Analog Circuit Parameters Using Bidirectional Long Short-Term Memory Coupled with an Enhanced Whale Optimization Algorithm by Hengfei Yang, Shiyuan Yang, Debiao Meng, Chenghao Hu, Chaosheng Wu, Bo Yang, Peng Nie, Yuan Si, Xiaoyan Su

“…However, the training of BiLSTM involves the adjustment of multiple hyperparameters (such as the number of layers, the number of hidden units, and the learning rate), which complicates the training process of the model. To enhance the efficiency and accuracy of neural network model development, this study proposes an Improved Whale Optimization Algorithm-assisted BiLSTM establishment strategy (IWOA-BiLSTM). …”
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Multi-objective optimal scheduling of cascade reservoirs in complex basin systems: Case study of the Jinsha River-Yalong River confluence basin in China by Zhaocai Wang, Zhihua Zhu, Hualong Luan, Tunhua Wu

“…Study focus: Scheduling cascade reservoirs is a high-dimensional, nonlinear multi-objective optimization problem. In complex basins with multiple converging rivers, the ''dimensional catastrophe'' effect increases with more decision variables, requiring improved robustness and optimization of the scheduling algorithm. …”
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