An advanced direct torque control for doubly fed induction motor using evolutionary computational techniques by Said Mahfoud, Najib El Ouanjli, Aziz Derouich, Abderrahman El Idrissi, Elmostafa Chetouani, Azeddine Loulijat, Shimaa A. Hussien, Mohamed I. Mosaad

“…This paper presents a methodology that integrates DTC-based PID controller with two optimization algorithms, with either Genetic algorithm (GA) or ant colony optimization (ACO). …”
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Robust Tracking Control of Piezoelectric Actuators Using Super-Twisting Sliding Mode With Bouc-Wen Hysteresis Model-Based Enhanced Jaya Algorithm by Nguyen Thi Thu Hang, Nguyen Ngoc Son

“…The Bouc-Wen model, which captures the nonlinear hysteretic behavior of the PZT actuator, is estimated using a modified Jaya algorithm enhanced with Lévy flight distribution (called LeJaya). …”
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Binary Secretary Bird Optimization Clustering by Novel Fitness Function Based on Voronoi Diagram in Wireless Sensor Networks by Mohammed Abdulkareem, Hadi S. Aghdasi, Pedram Salehpour, Mina Zolfy

“…To address these limitations, we propose the binary secretary bird optimization clustering (BSBOC) method. BSBOC introduces a binary variant of the secretary bird optimization algorithm (SBOA) to handle the discrete nature of CH selection. …”
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A multi-objective optimization approach for the virtual coupling train set driving strategy by Junting Lin, Maolin Li, Xiaohui Qiu

“…Furthermore, the particle swarm optimization (PSO)-based model predictive control (MPC) algorithm has also demonstrated tracking accuracy and further improved safety during VCTS operation, with an average increase of 37.7% in tracking accuracy compared to the traditional MPC algorithm.…”
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An Actor–Critic-Based Hyper-Heuristic Autonomous Task Planning Algorithm for Supporting Spacecraft Adaptive Space Scientific Exploration by Junwei Zhang, Liangqing Lyu

“…At the bottom level of the hyper-heuristic algorithm, this paper uses the particle swarm optimization algorithm, grey wolf optimization algorithm, differential evolution algorithm, and positive cosine optimization algorithm as the basic operators. …”
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Double layered expansion planning for virtual power plants considering virtual energy storage systems by Jianghai Ma, Xuanwen Gu, Yao Zhang, Jinming Gu, Wenjie Luo, Feng Gao

“…To improve computational efficiency, a hybrid Grey Wolf Optimization algorithm is employed for model solution. …”
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NID-DETR: A novel model for accurate target detection in dark environments by Qingyuan Pan, Qiang Liu, Wei Huang

“…Finally, in the target detection output layer, we adopt strategies to reduce concatenation operations and optimize small object detection heads to decrease the model parameter count and improve precision. …”
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Transport Capacity Maximization in Rail Mass Transit Stations Under Uncertainty by Adrian Fernandez-Rodriguez, Maria Dominguez, Asuncion P. Cucala, Antonio Fernandez-Cardador

“…At the upper level, a genetic algorithm determines the optimal sequence of train services and platform assignments. …”
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SFP selection algorithm for SFC by Yongqing ZHU, Xia GONG, Huanan CHEN

“…In order to achieve the new business deployment model by the convergence of cloud and network,SFC technology has been promoted greatly.As one of the key technologies in SFC,the SFP selection strategy affects the network performance and business experience directly.Aiming at the single target defect existing in business path se-lection strategy,the minimum weight algorithm based on the network delay and load was proposed and simulated.It could optimize the resources allocation and improve the network performance.A technical reference was provided for the operators to deploy the network and resources in the future.…”
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Short-term Power Prediction of Photovoltaic Power Generation Based on LSTM and Error Correction by ZHU Tao, LI Junwei, ZHU Yuanfu, YE Zhiming, TANG Yi

“…In order to improve the stability of photovoltaic power grid connection and make full use of error information to correct the model prediction results, this paper proposes a short-term photovoltaic power prediction model based on long short-term memory (LSTM) and error correction. …”
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A Prescriptive Approach Based on Fuzzy Cognitive Maps and Genetic Algorithms for Disease Management in Beef Production by Rodrigo Garcia, Jose Aguilar, Angel Pinto, William Hoyos

“…The prescriptive model yielded high performance with average <inline-formula> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula> values above 0.93 and low RMSE values, demonstrating that the recommended treatments closely matched the optimal solutions. …”
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Distributionally robust microgrid formation for service restoration in distribution systems against extended extreme events by Ran Zhu, Hongzhe Liu, Wenwu Yu, Wei Gu, Jin Zhao

“…Furthermore, to enhance the computational efficiency, a parallel solving strategy is developed, based on the column-and-constraint generation algorithm, the alternating optimization procedure, and the progressive hedging algorithm. …”
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Integrating Machine Learning and Multi-Objective Optimization in Biofuel Systems: A Review by Ivan P. Malashin, Dmitry A. Martysyuk, Vadim S. Tynchenko, Andrei P. Gantimurov, Vladimir A. Nelyub, Aleksei S. Borodulin

“…While existing models demonstrate improvements in predictive accuracy and optimization effectiveness, challenges remain in model generalization, computational complexity, and real-time adaptability. …”
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Ways to improve the efficiency of automatic control systems of pressing current collectors for railway service of high speeds by A. S. GOLUBKOV, O. A. SIDOROV, S. N. SMERDIN

“…For the considered current collector model, the optimal values of the controller coefficients are kp = 1.5 and ki= 1.0. …”
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Artificial intelligence model for predicting early biochemical recurrence of prostate cancer after robotic-assisted radical prostatectomy by Miguel Angel Bergero, Pablo Martínez, Patricio Modina, Ricardo Hosman, Wenceslao Villamil, Romina Gudiño, Carlos David, Lucas Costa

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Integrating artificial neural networks, multi-objective metaheuristic optimization, and multi-criteria decision-making for improving MXene-based ionanofluids applicable in PV/T sol... by Tao Hai, Ali Basem, As’ad Alizadeh, Kamal Sharma, Dheyaa J. jasim, Husam Rajab, Abdelkader Mabrouk, Lioua Kolsi, Wajdi Rajhi, Hamid Maleki, Narinderjit Singh Sawaran Singh

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Multi-criteria decision model for multicircular flight control of unmanned aerial vehicles through a hybrid approach by Noorulden Basil, Hamzah M. Marhoon, Bayan Mahdi Sabbar, Abdullah Fadhil Mohammed, Osamah Albahri, Ahmed Albahri, Abdullah Alamoodi, Iman Mohamad Sharaf, Amare Merfo Amsal, Mahrous Ahmed, Enas Ali, Sherif S. M. Ghoneim

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Sensorless Control of Ultra-High-Speed PMSM via Improved PR and Adaptive Position Observer by Xiyue Bai, Weiguang Huang, Chuang Gao, Yingna Wu

“…To improve the precision of the position and speed estimation in ultra-high-speed (UHS) permanent magnet synchronous motors (PMSM) without position sensors, multiple refinements to the traditional extended electromotive force (EEMF) estimation algorithm are proposed in this paper. …”
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Evaluation Method for Remaining Life of XLPE Insulated Power Cable by MA Hanchao, GAO Baoqi, LI Xiangyang, WU Suzhou, ZHANG Xiaojun

“…The results show that this method can obtain the optimal solution fitness value quickly, improve the efficiency of the surplus life evaluation of the analysis object, determine the weight value of the assessment factor under the measurement of the iterative period, and improve the residual life of the cable. …”
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Advanced long-term actual evapotranspiration estimation in humid climates for 1958–2021 based on machine learning models enhanced by the RReliefF algorithm by Ahmed Elbeltagi, Salim Heddam, Okan Mert Katipoğlu, Abdullah A. Alsumaiei, Mustafa Al-Mukhtar

“…To address this issue and guarantee more accurate ET predictions, this study attempts the following: i) to assess the performance of five machine learning (ML) models optimized by the RReliefF algorithm in estimating actual ET values for each month in four Chinese provinces under various agroclimatic conditions; and ii) to select the optimal model based on statistical metrics while minimizing discrepancies between the estimated and actual ET values. …”
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