Improving Frequency Control of Multi-Area Interconnected Hydro-Thermal Power System Using PSO Algorithm by Dao Huy Tuan, Van Nguyen Ngoc Thanh, Dat Nguyen Chi, Van Huy Pham

“…This paper explores a method that combines traditional PID control with the Particle Swarm Optimization (PSO) algorithm to improve frequency regulation in interconnected hydropower systems. …”
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Prediction method of soil water content based on SVM optimized by improved salp swarm algorithm by Xiaoqiang ZHAO, Fan YANG, Zhufeng YAN

“…Aiming at the problems of low accuracy and low efficiency of traditional soil water content prediction methods, support vector machine (SVM) was used to establish a prediction model, and the soil water content prediction method based on SVM optimized was proposed by the improved salp swarm algorithm.Firstly, the opposition-based learning and chaotic optimization were introduced to improve the standard salp swarm algorithm to solve the problem that the algorithm was easy to fall into the local optimal solution and its convergence speed was slow.Secondly, the improved salp swarm algorithm was used to optimize the parameters that affect the performance of SVM and the corresponding prediction model was built.Finally, the proposed model was compared with the particle swarm optimization SVM and the whale algorithm optimized SVM prediction model.The experimental results show that the mean square error and decision coefficient of the proposed model are 0.42 and 0.901, which are better than the other two models which verified the effectiveness of the proposed method.…”
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Prediction method of soil water content based on SVM optimized by improved salp swarm algorithm by Xiaoqiang ZHAO, Fan YANG, Zhufeng YAN

“…Aiming at the problems of low accuracy and low efficiency of traditional soil water content prediction methods, support vector machine (SVM) was used to establish a prediction model, and the soil water content prediction method based on SVM optimized was proposed by the improved salp swarm algorithm.Firstly, the opposition-based learning and chaotic optimization were introduced to improve the standard salp swarm algorithm to solve the problem that the algorithm was easy to fall into the local optimal solution and its convergence speed was slow.Secondly, the improved salp swarm algorithm was used to optimize the parameters that affect the performance of SVM and the corresponding prediction model was built.Finally, the proposed model was compared with the particle swarm optimization SVM and the whale algorithm optimized SVM prediction model.The experimental results show that the mean square error and decision coefficient of the proposed model are 0.42 and 0.901, which are better than the other two models which verified the effectiveness of the proposed method.…”
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Determining Appropriate Strategy for Managing the Energy Production System in the Presence of Renewable Energy Sources and Improved Intelligence Method by Amir Sohel, Md Faisal Bin Ashab

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Research on Optimal Configuration of Offshore Wind Power Energy Storage Based on Improved Scene Clustering Algorithm by Jingui YI, Ziwei ZHU, Qing XIE

“…Furthermore, to minimize the annual comprehensive cost of the power storage, the paper constructs an optimal configuration model for offshore wind power storage and uses the particle swarm optimization algorithm to solve the optimal configuration model. …”
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Error Analysis and Compensation of 3‒PTT Parallel Robot by CHEN Mingfang, LIANG Hongjian, WEI Songpo, HE Chaoyin

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Electromyography-based gesture recognition for quadriplegic users using hidden Markov model with improved particle swarm optimization by Xanno K Sigalingging, Alrezza Pradanta Bagus Budiarsa, Jenq-Shiou Leu, Jun-ichi Takada

“…The signals are then processed using a novel algorithm that employs hidden Markov model and improved particle swarm optimization to classify the gesture. …”
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Improved particle swarm optimization for fractional order PID control design in robotic manipulator system: A performance analysis by Gamil Ahmed, Ahmed Eltayeb, Nezar M. Alyazidi, Imil Hamda Imran, Tarek Sheltami, Sami El-Ferik

“…This study introduces an improved particle swarm optimization (IPSO) technique that maximizes the efficiency of a Fractional Order Proportional-Integral-Derivative (FOPID) controller by optimally adjusting FOPID gains in robotic manipulator systems. …”
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An Improved Particle Swarm Optimization and Adaptive Neuro-Fuzzy Inference System for Predicting the Energy Consumption of University Residence by Stephen Oladipo, Yanxia Sun, Oluwatobi Adeleke

“…To address this problem, the velocity update equation of the original PSO algorithm is modified by incorporating a dynamic linear decreasing inertia weight, which improves the PSO algorithm’s convergence behaviour and aids both local and global search. …”
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Prediction and reliability analysis of rigid pipeline response in soft soil using improved particle swarm neural network by Laifu Song, Shun Zhang, Jun Wang, Hongtao Fu, Jiayu Cai

“…The simulation results are validated against data from field tests. Second, an improved particle swarm optimization (PSO) algorithm is introduced to optimize the weights and thresholds of a backpropagation neural network (BPNN). …”
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Particle Swarm Optimization Based Sliding Mode Controller for Performance Improvement of Unified Power Quality Controllers Inverters by Mohammad Amin Heidari, Mehdi Nafar, Taher Niknam

“…In this paper particle swarm optimasation algorithm (PSO) based sliding mode controller(SMC) introduced to control invrters of Uniefied power quality Controllers(UPQC) to control and improve the power quality in microgrids through controlling the output power of the distributed generation source. …”
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Performance Improvement of Spaceborne SAR Using Antenna Pattern Synthesis Based on Quantum-Behaved Particle Swarm Optimization by Young-Jin Won, Kyun Ho Lee, Jae-Hyun Lee

“…This study proposes a method for antenna mask design that is based on several previous studies as well as the antenna pattern synthesis algorithm, which is based on quantum-behaved particle swarm optimization (QPSO) for an active phased array SAR system. …”
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A hybrid particle swarm optimization algorithm for solving engineering problem by Jinwei Qiao, Guangyuan Wang, Zhi Yang, Xiaochuan Luo, Jun Chen, Kan Li, Pengbo Liu

“…Abstract To overcome the disadvantages of premature convergence and easy trapping into local optimum solutions, this paper proposes an improved particle swarm optimization algorithm (named NDWPSO algorithm) based on multiple hybrid strategies. …”
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Immune particle swarm optimization algorithm based on the adaptive search strategy by ZHANG Chao, LI Qing, WANG Wei-qian, CHEN Peng, FENG Yi-nan

“…The particle swarm algorithm is often trapped in a local optimum due to poor diversity, resulting in a premature stagnation phenomenon. …”
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IDS alert clustering algorithm based on chaotic particle swarm optimization by Xiao-bo XU, Qin-qin JIANG, Kang-feng ZHENG, Bin WU, Yi-xian YANG

“…In order to improve the quality of alerts in intrusion detection system (IDS) and reduce the large number of redundant alarms, an IDS alerts clustering algorithm based on chaotic particle swarm optimization was proposed.It made the motion of particles with characteristics of chaos,so as to make particles move between the state of chaos and stable, and gradually close to the optimal value. …”
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Search Guidance Network Assisted Dynamic Particle Swarm Optimization Algorithm by LIU Zhi, SONG Wei

“…To this end, a search guidance network-based particle swarm optimization (SGN-PSO) is proposed. …”
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Research on Fractional-Order Control of Anchor Drilling Machine Optimized by Intelligent Algorithms by Jingkai Li, Jun Zhang, Jiaquan Xie, Wei Shi, Jianzhong Zhao

“…To achieve precise docking in unmanned conditions, we employed an inner-loop fractional-order proportional–integral–derivative (FOPID) controller optimized by an improved particle swarm optimization (ILPSO) algorithm. …”
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On the Use of an Improved Artificial Fish Swarm Algorithm-Backpropagation Neural Network for Predicting Dam Deformation Behavior by Bo Dai, Hao Gu, Yantao Zhu, Siyu Chen, E. Fernandez Rodriguez

“…In this paper, an artificial neural network (ANN), trained by the improved artificial fish swarm algorithm (IAFSA) and backpropagation algorithm (BP), is proposed for predicting the dam deformation. …”
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Path Planning for Coal Mining Masonry Robots Combined With Trajectory Optimization by Xingyi Qian, Yan Wang

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Noise Processing Method of MEMS Tilt Sensor Using Improved Kalman Filter Based on Quantum Particle Swarm Optimization by Yutong Ge, Weizheng Ren, Kaile Yu, Yiran Zhang, Yuxiao Li

“…According to the experimental findings, the proposed method exhibits a superior noise reduction effect, as evidenced by its smaller mean absolute error (MAE) and mean square error (MSE) compared to alternative techniques such as variational mode decomposition (VMD) combined with wavelet transform (WT), back propagation (BP) neural network optimized Kalman filter and particle swarm optimization (PSO) improved Kalman filter. …”
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