Reinforcement learning algorithm for improving speed response of a five-phase permanent magnet synchronous motor based model predictive control. by Ahmed M Hassan, Jafar Ababneh, Hani Attar, Tamer Shamseldin, Ahmed Abdelbaset, Mohamed Eladly Metwally

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Reservoir water level prediction using combined CEEMDAN-FE and RUN-SVM-RBFNN machine learning algorithms by Lan-ting Zhou, Guan-lin Long, Can-can Hu, Kai Zhang

“…This study proposed a method for reservoir water level prediction based on CEEMDAN-FE and RUN-SVM-RBFNN algorithms. By integrating the adaptive complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) method and fuzzy entropy (FE) with the new and highly efficient Runge–Kuta optimizer (RUN), adaptive parameter optimization for the support vector machine (SVM) and radial basis function neural network (RBFNN) algorithms was achieved. …”
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Improved empirical wavelet transform combined with particle swarm optimization-support vector machine for EEG-based depression recognition by Yongxin Wang, Longqi Xu, Hongxu Qian, Haijun Lin, Xuhui Zhang

“…Therefore, there is a pressing need to develop techniques for detecting early signs of depression to enable timely intervention and potentially improve recovery rates. In this paper, we propose an improved method for the early objective diagnosis of depression utilizing an empirical wavelet transform (EWT) technique enhanced by a particle swarm optimization-support vector machine (PSO-SVM) algorithm. …”
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Improved PICEA-g-based multi-objective optimization scheduling method for distribution network with large-scale electric vehicles by Meiyi Huo, Songling Pang, Hailong Zhao

“…Abstract Large-scale electric vehicle access to the distribution grid for charging can affect the security and economic operation of the grid. In this paper, an optimal scheduling method for large-scale EV access to the distribution grid based on the improved preference-inspired co-evolutionary algorithm using goal vectors (PICEA-g) is proposed. …”
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Predicting excavation-induced lateral displacement using improved particle swarm optimization and extreme learning machine with sparse measurements by Cheng Chen, Guan-Nian Chen, Song Feng, Xiao-Zhen Fan, Liang-Tong Zhan, Yun-Min Chen

“…This study presents a novel prediction method using an extreme learning machine (ELM) optimized by an improved particle swarm optimization (IPSO) algorithm. …”
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Multi-Objective Dynamic System Model for the Optimal Sizing and Real-World Simulation of Grid-Connected Hybrid Photovoltaic-Hydrogen (PV-H₂) Energy Systems by Ayatte I. Atteya, Dallia Ali, Nazmi Sellami

“…The model integrates a Particle Swarm Optimisation (PSO) algorithm that enables minimising both the levelised cost of energy (LCOE) and the building carbon footprint with a dynamic model that considers the real-world behaviour of the system components. …”
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Prediction and Optimization for Multi-Product Marketing Resource Allocation in Cross-Border E-Commerce by Yi Xie, Heng-Qing Ye, Wenbin Zhu

“…Experiments on real-world data show that our framework significantly outperforms baseline strategies, achieving a 14.48% increase in order volume and revenue improvements ranging from 0.19% to 43.91%. The minimum-cost flow algorithm consistently outperforms the greedy approach, especially in large-scale instances. …”
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ONBOARD FUEL PUMP FAULT DIAGNOSIS BASED ON IMPROVED SUPPORT VECTOR MACHINE AND EXPERIMENTAL RESEARCH by LIANG Wei, JING Bo, JIAO XiaoXuan, QIANG XiaoQing, LIU XiaoDong

“…Aiming at solving lacking of failure data and inefficiency,high-cost of now available fault diagnosis methods,a experimental platform of fuel transfer system is developed and a fault diagnosis method based on wavelet packet analysis and improved support vector machine（ ISVM） is presented. …”
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Vehicle scheduling optimization for demand responsive transit with flexible stops by SHEN Zikang, JIN Wenzhou, ZHENG Yajing

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A Vehicle Path Planning Algorithm Based on Mixed Policy Gradient Actor-Critic Model with Random Escape Term and Filter Optimization by Wei Nai, Zan Yang, Daxuan Lin, Dan Li, Yidan Xing

“…In addition, filter optimization has been innovatively introduced in this paper, and the step size of each iteration of the model is selected through the filter optimization algorithm to achieve the better iterative effect. …”
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Deep Learning-Augmented Evolutionary Strategies for Intelligent Global Optimization by Absalom El-Shamir Ezugwu, Olaide Nathaniel Oyelade, Jeffrey Ovre Agushaka, Apu Kumar Saha

“…SIRO integrates deep learning into its initialization and parameter setting to enhance its efficiency, enabling intelligent and adaptive behavior. This hybridization improves solution quality, accelerates convergence, enhances robustness, and reduces computational costs. …”
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Research on Oil Well Production Prediction Based on GRU-KAN Model Optimized by PSO by Bo Qiu, Jian Zhang, Yun Yang, Guangyuan Qin, Zhongyi Zhou, Cunrui Ying

“…First, the MissForest algorithm is employed to handle anomalous data, improving data quality. …”
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Control of a compliant gripper via least-squares support vector regression (LS-SVR) with particle swarm optimization (PSO) algorithm by Poonnapa Chaichudchaval, Archawin Chaitrekal, Nawin Sutthiprapa, Dung-An Wang, Teeranoot Chanthasopeephan

“…To address this, an algorithm developed to mitigate the effect of hysteresis is seen to improve control accuracy. …”
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Bus frequency optimization in a large-scale multi-modal transportation system: integrating 3D-MFD and dynamic traffic assignment by Kai Yuan, Dandan Cui, Jiancheng Long

“…However, as far as the authors know, most proposed bus frequency optimization formulations are based on static demand and the Bureau of Public Roads function, and do not properly consider the congestion dynamics and their impacts on mode choices. …”
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A new approach for bin packing problem using knowledge reuse and improved heuristic by Jie Fang, Xubing Chen, Yunqing Rao, Yili Peng, kuan Yan

“…The classic packing solution is a hybrid algorithm based on heuristic positioning and meta-heuristic sequencing, which has the problems of complex solving rules and high time cost. …”
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An Improved NSGA‐III With Hybrid Crossover Operator for Multi‐Objective Optimization of Complex Combined Cooling, Heating, and Power Systems by Lejie Ma, Dexuan Zou

“…The effectiveness of CCHP‐Plus is assessed using three key indicators: primary energy consumption, operational cost, and CO2 emissions. NSGAIII‐AC‐GM delivers a 20% reduction in operational costs and a 10% decrease in CO2 emissions, outperforming seven other algorithms in optimization efficiency on DTLZ and IMOP problems. …”
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Optimizing the Joint Replenishment and Channel Coordination Problem under Supply Chain Environment Using a Simple and Effective Differential Evolution Algorithm by Lin Wang, Hui Qu, Shan Liu, Can Chen

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Artificial Flora Algorithm-Based Feature Selection With Support Vector Machine for Cardiovascular Disease Classification by M. M. Asha, G. Ramya

“…This approach utilizes the Cleveland dataset by combining the Artificial Flora Optimization algorithm with the Support Vector Machine. …”
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Revolutionizing Electric Vehicle Charging Stations with Efficient Deep Q Networks Powered by Multimodal Bioinspired Analysis for Improved Performance by Sugunakar Mamidala, Yellapragada Venkata Pavan Kumar, Rammohan Mallipeddi

“…These approaches rely on fixed models, often leading to inefficient energy use, higher operational costs, and increased traffic congestion. This paper proposes a novel framework that integrates deep Q networks (DQNs) for real-time charging optimization, coupled with multimodal bioinspired algorithms like ant lion optimization (ALO) and moth flame optimization (MFO). …”
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Coordinated Optimization Method for Distributed Energy Storage and Dynamic Reconfiguration to Enhance the Economy and Reliability of Distribution Network by Caihong Zhao, Qing Duan, Junda Lu, Haoqing Wang, Guanglin Sha, Jiaoxin Jia, Qi Zhou

“…Subsequently, a hybrid optimization algorithm combining an improved Aquila Optimizer-Second-Order Cone Programming (IAO-SOCP) is proposed to solve the coordinated optimization model. …”
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