Intrusion Detection-Data Security Protection Scheme Based on Particle Swarm-BP Network Algorithm in Cloud Computing Environment by Zhun Wang, Xue Chen

“…Then, by introducing the decision tree algorithm, the overfitting is reduced and the data processing speed of the model is improved, and on this basis, the feature selection is carried out through the “gain rate” optimization method, which reduces the redundant information of the feature vector. …”
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Servo System Control of Turntable Lipstick-Filling Machine Based on Particle Swarm Optimization by Xiangqiang Zhong, Wenbo Tao, Lingling Zou, Huaian Yang, Shunyu Yao

“…The experimental results demonstrate that the qualified rate of lipstick filling, under the particle swarm optimization PID control implementation, is 97%, indicating that the particle swarm algorithm is quite applicable and has an economic impact by improving the accuracy and stability of the lipstick-filling servo system.…”
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Bionic Compass Method Based on Atmospheric Polarization Optimization in Non-Ideal Clear Condition by Yuyang Li, Xia Wang, Min Zhang, Ruiqiang Li, Qiyang Sun

“…This paper proposes a bionic navigation method based on atmospheric polarization optimization to improve heading accuracy under non-ideal clear conditions. …”
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Optimal Trajectory Planning for Minimizing Base Disturbance of a Redundant Space Robot with IQPSO by Jianxia Zhang, Fuchao Yang, Guanghua Nie, Jianxin Zhang

“…At last, the proposed improved quantum particle swarm optimization (IQPSO) algorithm was presented. …”
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Source-storage-load optimization control technology of DC microgrid with virtual energy storage by WANG Chang, JIANG Yu, FU Shouqiang, SHU Yinan, ZHANG Xiangyu

“…On this basis, under the coordinated control of source and storage of DC microgrid, particle swarm optimization algorithm is used to optimize the design of virtual capacitance values in different periods of time to improve the economic benefits of the system. …”
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Multi objective optimization and experimental investigation of the stirring performance of a novel micro actuator by Zhuowei He, Junjie Lei, Jingjing Yang, Huba Zhu

“…Subsequently, the Non-dominated Sorting Genetic Algorithm III (NSGA-III) is utilized for Multi-Objective Optimization to identify the optimal combination of structural parameters. …”
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Enhanced particle swarm optimization for feature selection in SVM-based Alzheimer’s disease diagnosis by Qian Zhang, Jinhua Sheng, Rougang Zhou, Qiao Zhang, Binbing Wang, Rong Zhang

“…In this paper, an enhanced Particle Swarm Optimization (PSO) algorithm, which integrates opposition-based Latin squares sampling initialization (OL) with dynamic inertia weights and learning factors (D), termed OLDPSO, is proposed to improve feature selection and classification within a Support Vector Machine (SVM) model for AD diagnosis using magnetic resonance imaging (MRI) data. …”
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Time Series Data Augmentation for Energy Consumption Data Based on Improved TimeGAN by Peihao Tang, Zhen Li, Xuanlin Wang, Xueping Liu, Peng Mou

“…Using deep learning algorithms to establish prediction models for sensor data is an effective approach; however, the performance of these models is significantly influenced by the quantity and quality of the training data. …”
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Multi-Objective Optimization for Artificial Island Construction Scheduling Using Cooperative Differential Evolution by Tianju Zheng, Liping Sun, Jifeng Chen, Xinyuan Cui, Shuqi Li

“…To optimize the proposed model, we propose an algorithm called Multi-objective Cooperative Differential Evolution (MOCDE). …”
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Evaluation and Application of Urban Traffic Signal Optimizing Control Strategy Based on Reinforcement Learning by Yizhe Wang, Xiaoguang Yang, Yangdong Liu, Hailun Liang

“…Based on the three key parameters of cycle, arterial coordination offset, and green split, a set of hierarchical control algorithms based on reinforcement learning is constructed to optimize and improve the current signal timing scheme. …”
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Optimized hybrid deep learning for cross-linguistic sentiment analysis: a novel approach by Vipin Jain, Lokesh Malviya, Anjana .S

“…Unlike previous techniques, our model includes the Grey Wolf Optimization (GWO) algorithm for hyperparameter tweaking, which improves both accuracy and efficiency in multilingual sentiment analysis. …”
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Ensemble Learning-Based Wine Quality Prediction Using Optimized Feature Selection and XGBoost by Sonam Tyagi, Ishwari Singh Rajput, Bhawnesh Kumar, Harendra Singh Negi

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Fuzzy LQR-based control to ensure comfort in HVAC system with two different zones by Elif Çinar, Tayfun Abut

“…The core novelty of this work lies in the development and comparison of advanced control algorithms, including the Linear Quadratic Regulator (LQR), a Particle Swarm Optimization (PSO)-based LQR, and a newly designed PSO-based Fuzzy LQR (FLQR) controller. …”
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Adaptive Bayesian optimization for proportional derivative control in double-acting piston pump ventilators by Cong Toai Truong, Trung Dat Phan, Van Tu Duong, Huy Hung Nguyen, Thanh Truong Nguyen, Tan Tien Nguyen

“…The method integrates a conventional proportional derivative control algorithm with Bayesian optimization to rapidly determine optimal control parameters without a precise system model and adaptively re-tune these parameters in response to fluctuations in patient respiratory conditions. …”
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Optimization Study of PVT Coupled Water Loop Heat Pump Energy Supply System by Lv Tiangang, Liu Bing, Wu Jun, Zhu Li, Hou Jingxuan

“…This study designs a building energy supply system integrating PVT and a water-loop heat pump based on Tianjin's meteorological data, using TRNSYS software to establish a dynamic model. By employing the Hooke-Jeeves algorithm, the system's design and operation parameters were optimized with annual cost and system COP as objective functions. …”
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Distributed energy storage hierarchical partition dispatch control of virtual power plant based on SaDE-BBO algorithm by Tianyi Yu, Shijia Wei, Tao Lu, Zhipeng Zhang, Ning Sun

“…This method is based on the operation structure of the virtual power plant, analyzes the operating characteristics of the distributed energy storage system and the output of uncertainty factors, considers the grid load, renewable energy and distributed energy storage on the time scale, and constructs hierarchical partitions of the virtual power plant. The dispatch model determines the day-ahead and day-in-day hierarchical partition dispatch control objective functions, and sets corresponding constraints; the dispatch control model based on the solution of the SaDE-BBO algorithm outputs the virtual power plant distributed energy storage hierarchical partition dispatch control optimization plan. …”
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Performance Evaluation and Optimization of 3D Gaussian Splatting in Indoor Scene Generation and Rendering by Xinjian Fang, Yingdan Zhang, Hao Tan, Chao Liu, Xu Yang

“…The results demonstrate significant performance improvements in the optimized 3DGS algorithm: the PSNR metric increases by 4.3%, and the SSIM metric improves by 0.2%. …”
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Truck Lifting Accident Detection Method Based on Improved PointNet++ for Container Terminals by Yang Shen, Xintai Man, Jiaqi Wang, Yujie Zhang, Chao Mi

“…To tackle these challenges, this paper proposes an accident detection method based on multi-line LiDAR and an improved PointNet++ model. This method uses multi-line LiDAR to collect point cloud data from operational lanes in real time and enhances the PointNet++ model by integrating a multi-layer perceptron (MLP) and a mixed attention mechanism (MAM), optimizing the model’s ability to extract local and global features. …”
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Optimizing resource allocation in industrial IoT with federated machine learning and edge computing integration by Ala'a R. Al-Shamasneh, Faten Khalid Karim, Yu Wang

“…This algorithm adeptly balances resource expenditures with model quality, employing Lyapunov-driven optimization theory to convert long-term stochastic challenges into short-term deterministic resolutions. …”
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Integrated Optimization on Train Control and Timetable to Minimize Net Energy Consumption of Metro Lines by Yuhe Zhou, Yun Bai, Jiajie Li, Baohua Mao, Tang Li

“…This paper developed an integrated optimization model on train control and timetable to minimize the net energy consumption. …”
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