Maximum Torque per Ampere Control of PMSMs Using Real-Time Numerical Optimization by Yong Xu, Min-Yi Lin, Wen-Jie Wan, Yunchong Wang, Jian-Xin Shen

“…A flux-linkage based nonlinear PMSM model was developed to improve the torque control under dynamic conditions. …”
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PCA-Kriging-Based Oscillating Jet Actuator Optimization and Wing Separation Flow Control by Qixiang Sun, Wanbo Wang, Jiaxin Pan

“…The optimization objectives are to improve the sweeping uniformity and range of the jet. …”
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Coordinated multi-objective optimization scheduling for electric vehicle swapping station cluster and grid by Xiang Liao, Ziyu Zheng, Beibei Qian, Haiwei Wang, Dianling Zhan, Junyi Shi, Chaoshun Li, Wei Huang

“…Meanwhile, an electricity mutual assistance strategy between EVBESS is proposed to improve overall energy efficiency. Subsequently, an improved many-objective optimization algorithm based on multiple update strategies (G-MOMUS) is used to solve the model. …”
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Smart deep learning model for enhanced IoT intrusion detection by Faisal S. Alsubaei

“…The optimized SNN model also performed well on the NSL-KDD dataset with an accuracy of 99.0% and an AUC of 1.00. …”
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Variants of the Sliding Mode Control in Presence of External Disturbance for Quadrotor by Irfan Ahmad, Muwaida Liaquat, Fahad Mumtaz Malik, Hameed Ullah, Usman Ali

“…Secondly, kinodynamic Rapidly Exploring Random Tree with Fixed Node (RRT*FN) which is an incremental sampling-based optimal algorithm has been implemented for online navigation and flight control of the quadrotor system. …”
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Enhancing Precision in OLT Measurements and Improving Agreement in Surgical Decision-Making: A Comprehensive Evaluation Using WBCT and Distance Mapping for Preoperative Planning by Agustin Barbero MD, Ben Efrima MD, Jari Dahmen MD, Amit Benady MD PhD, Camilla Maccario MD, Cristian Indino MD, Gino M M.M.J. Kerkhoffs MD, PhD, Federico Giuseppe Usuelli MD

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Optimizing Route Planning via the Weighted Sum Method and Multi-Criteria Decision-Making by Guanquan Zhu, Minyi Ye, Xinqi Yu, Junhao Liu, Mingju Wang, Zihang Luo, Haomin Liang, Yubin Zhong

“…Secondly, this study compares seven heuristic algorithms—the genetic algorithm (GA), particle swarm optimization (PSO), the tabu search (TS), genetic-particle swarm optimization (GA-PSO), the gray wolf optimizer (GWO), and ant colony optimization (ACO)—to solve the TOPSIS model, with GA-PSO performing the best. …”
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Robust Path Tracking Control with Lateral Dynamics Optimization: A Focus on Sideslip Reduction and Yaw Rate Stability Using Linear Quadratic Regulator and Genetic Algorithms by Karrar Y. A. Al-bayati, Ali Mahmood, Róbert Szabolcsi

“…Under external and internal disturbances, such as road conditions, lateral wind, and actuator delay, the model demonstrates improved tracking performance and reduced sideslip angle and lateral acceleration by adjusting the longitudinal vehicle speed. …”
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A configuration and scheduling optimization method for integrated energy systems considering massive flexible load resources by Zihao Wang, Shenhua Wang, Hanwen Ni, Junyin Wang, Jun Zhang

“…Additionally, an enhanced Kepler Optimization Algorithm (EKOA) was proposed, incorporating chaos mapping and adaptive learning rate strategies to improve search scope, convergence speed, and solution efficiency. …”
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Optimization of Vessel Traffic Scheduling in a Compound Channel of an Estuarine Port with Opposing Distribution of Inner Anchorages and Terminals by Bolin Yin, Chengji Liang, Yu Wang, Xiaojie Xu, Yue Zhang

“…In terms of port scheduling performance, the proposed model and algorithm outperform the traditional First-Come-First-Served (FCFS) strategy and the Non-Dominated Sorting Genetic Algorithm II (NSGA-II), reducing total vessel waiting time by 33.8% and improving total channel occupancy ratio by 8.8%. …”
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Advanced Computational Methods for Mitigating Shock and Vibration Hazards in Deep Mines Gas Outburst Prediction Using SVM Optimized by Grey Relational Analysis and APSO Algorithm by Xiang Wu, Zhen Yang, Dongdong Wu

“…Moreover, adaptive particle swarm optimization (APSO) was used to optimize the penalty factor and kernel parameters of the support vector machine to improve the global search ability and avoid the occurrence of the local optimal solutions. …”
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A Virtual Power Plant-Integrated Proactive Voltage Regulation Framework for Urban Distribution Networks: Enhanced Termite Life Cycle Optimization Algorithm and Dynamic Coordination by Yonglin Li, Zhao Liu, Changtao Kan, Rongfei Qiao, Yue Yu, Changgang Li

“…While virtual power plants (VPPs) and network reconfiguration mitigate operational risks, extant methods inadequately model load flexibility and suffer from algorithmic stagnation in non-convex optimization. …”
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Optimization analysis of air cooled open cathode proton exchange membrane fuel cell flow channel structure by Zhijun Deng, Qingwei Wang, Xun Fang, Yaru Han, Kunxiang Liu, Chen Zhao

“…In addition, in order to further improve the power density of the fuel cell, two agent models, support vector regression and Gaussian process regression, are constructed and trained, and a genetic algorithm is used to find the parameter optimization for the bending angle, width and height of the cathode channel. …”
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Proactive detection of anomalous behavior in Ethereum accounts using XAI-enabled ensemble stacking with Bayesian optimization by Vasavi Chithanuru, Mangayarkarasi Ramaiah

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Sustainable phytoprotection: a smart monitoring and recommendation framework using Puma Optimization for potato pathogen detection by Amal H. Alharbi, Faris H. Rizk, Khaled Sh. Gaber, Marwa M. Eid, Marwa M. Eid, El-Sayed M. El-kenawy, El-Sayed M. El-kenawy, Pushan Kumar Dutta, Doaa Sami Khafaga

“…This study proposes a novel hybrid framework for potato disease classification that integrates copula-based dependency modeling with a Restricted Boltzmann Machine (RBM), further enhanced through hyperparameter tuning using the biologically inspired Puma Optimization (PO) algorithm. …”
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DGCA3QM: DESIGN OF A DUAL GENETIC ALGORITHM BASED AUTOREGRESSION MODEL FOR CORRELATIVE PREDICTION OF AIR QUALITY METRICS by Harna M. Bodele, G. M. Asutkar, Kiran G. Asutkar

“…Due to incorporation of dual bioinspired optimizers with autoregressive correlation, the model is able to improve prediction accuracy by 8.5%, precision by 4.9%, recall by 1.5%, while reducing computational delay by 3.4% when compared with standard air quality analysis models. …”
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Reconstruction of Highway Vehicle Paths Using a Two-Stage Model by Weifeng Yin, Junyong Zhai, Yongbo Yu

“…To address the challenge of multiple possible paths due to missing trajectory data, this study proposes a novel two-stage model for vehicle path reconstruction. In the first stage, a Gaussian Mixture Model (GMM) is integrated into a path choice model to estimate the mean and standard deviation of travel times for each road segment, utilizing an improved Expectation Maximization (EM) algorithm. …”
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Multimodal data-based human motion intention prediction using adaptive hybrid deep learning network for movement challenged person by Mustufa Haider Abidi

“…Further, to enhance the prediction, the parameters in both the AH-CNN-LSTM and AH-CNN-Res-LSTM techniques are optimized using the Improved Yellow Saddle Goatfish Algorithm (IYSGA). …”
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Prediction of dam deformation using adaptive noise CEEMDAN and BiGRU time series modeling by WANG Zixuan, OU Bin, CHEN Dehui, YANG Shiyong, ZHAO Dingzhu, FU Shuyan

“…【Method】The model uses sample entropy reconstruction and the K-means clustering algorithm to optimize the adaptive noise complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) process, generating multiple intrinsic mode functions (IMF). …”
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Evolutionary Synthesis of High-Capacity Reconfigurable Multilayer Road Networks Using a Multiagent Hybrid Clustering-Assisted Genetic Algorithm by Andranik S. Akopov, Levon A. Beklaryan

“…To achieve this goal, a new multiagent hybrid clustering-assisted genetic algorithm (MA-HCAGA). The proposed algorithm combines the use of binary-coded crossovers and mutations as genetic operators, and biobjective discrete particle swarm optimization (BODPSO) techniques to improve the evolutionary search process. …”
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