Application Study on CPSO-FLN Model in the Steam Turbine Heat Rate Forecast by Jian HU, Chao LIU

“…The cloud model based adaptive weight strategy is introduced into the particle swarm algorithm such that the weight of the particle swarm algorithm can be self-adaptively adjusted to improve the global optimization performance of the PSO algorithm by taking advantage of the randomness and stability of cloud droplets. …”
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An Assist-as-Needed Control Strategy Based on a Subjective Intention Decline Model by Hao Yan, Fangcao Zhang, Xingao Li, Chenchen Zhang, Yunjia Zhang, Yongfei Feng

“…The subjective intention decline module collects surface electromyography (sEMG) data during patient training and optimizes support vector machine (SVM) using quantum particle swarm optimization (QPSO) algorithms to establish a subjective intention decline model. …”
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A new stochastic multi-objective model for the optimal management of a PV/wind integrated energy system with demand response, P2G, and energy storage devices by Hossein Faramarzi, Navid Ghaffarzadeh, Farhad Shahnia

“…Optimal energy hub scheduling (EHS) has emerged as a promising strategy for improving the efficiency and flexibility of power systems. …”
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Innovative application of particle swarm algorithm in the improvement of digital enterprise management efficiency by Shengnan Zhang

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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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An Improved Adaptive Car-Following Model Based on the Unscented Kalman Filter for Vehicle Platoons’ Speed Control by Caixia Huang, Wu Tang, Jiande Wang, Zhiyong Zhang

“…This study proposes an adaptive car-following model based on the unscented Kalman filter algorithm to enable coordinated speed control in vehicle platoons and to address key limitations present in conventional car-following models. …”
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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

“…The system assists in detecting and analyzing crowd density in real-time by utilizing artificial intelligence and machine learning (ML) models on surveillance videos. It detects crowded areas, manages crowd flow, and combines automated analysis with human oversight for improved public safety and early intervention. …”
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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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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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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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Energy optimization in intelligent sensor networks: application of particle swarm optimization algorithm in the deployment of electronic information sensing nodes by Wang Liang

“…Data preprocessing, including Z-score normalization and Independent Component Analysis (ICA), ensures feature scaling and dimensionality reduction for improved model performance, enabling effective optimization. …”
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Enhanced Short-Term PV Power Forecasting via a Hybrid Modified CEEMDAN-Jellyfish Search Optimized BiLSTM Model by Yanhui Liu, Jiulong Wang, Lingyun Song, Yicheng Liu, Liqun Shen

“…Each reconstructed component was then forecasted individually using a BiLSTM model, whose parameters were optimized by the JS algorithm. …”
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Unlocking The Potential of Hybrid Models for Prognostic Biomarker Discovery in Oral Cancer Survival Analysis: A Retrospective Cohort Study by Leila Nezamabadi Farahani, Anoshirvan Kazemnejad, Mahlagha Afrasiabi, Leili Tapak

“…Then, the particle swarm optimization (PSO) and genetic algorithm (GA) were used in combination with SVR for selecting features related to pseudo-survival outcome. …”
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Optimization Procedures in Affine Model Checking by N. O. Garanina

“…In this paper we suggest improved algorithms for an algebraic data representation, namely, optimization algorithms for affine data structures.…”
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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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Multi-objective optimization of grinding process parameters for complicated worm space surface based on the grey wolf optimization algorithm by Jiongkang Ren, Shisong Wang, Keqi Ren

“…To account for actual working conditions, we developed constrained models for grinding ratio and machining rigidity and improved the boundary processing method for MOGWO optimization. …”
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Fault Diagnosis Method for Transformer Winding Based on Differentiated M-Training Classification Optimized by White Shark Optimization Algorithm by Guochao Qian, Kun Yang, Jin Hu, Hongwen Liu, Shun He, Dexu Zou, Weiju Dai, Haozhou Wang, Dongyang Wang

“…The principal contributions are threefold: First, building upon the fundamental principles of the M-training algorithm, we establish a classification model incorporating diversified classifiers. …”
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A Bi-Objective Optimal Scheduling Method for the Charging and Discharging of EVs Considering the Uncertainty of Wind and Photovoltaic Output in the Context of Time-of-Use Electrici... by Xinfu Pang, Wen Jia, Haibo Li, Qingzhong Gao, Wei Liu

“…Then, the Monte Carlo method was employed to simulate electric vehicle loads and to facilitate the generation of and reduction in scenario scenes. Finally, the model was solved using an improved multi-objective barebones particle swarm optimization algorithm. …”
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Automated Generation of Hybrid Metaheuristics Using Learning-to-Rank by Xinru Xue, Ting Shu, Jinsong Xia

“…Metaheuristic algorithms, due to their superior global exploration capabilities and applicability, have emerged as critical tools for addressing complicated optimization tasks. …”
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