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

“…To address this issue, this study proposes the optimization of the linear quadratic regulator (LQR) control system by using the genetic algorithm (GA) to support the vehicle in following the predefined path accurately, minimizing the sideslip, and stabilizing the vehicle’s yaw rate. …”
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Robotic arm path planning based on the improved dung beetle optimization algorithm by XUAN Yitong, LI Lijun, CHEN Haifei

“…ObjectiveA path planning algorithm based on an improved dung beetle optimization algorithm was proposed to address the challenges in complex scenarios where traditional algorithms for robotic arm path planning often suffer from low efficiency and susceptibility to local optima.MethodsFirstly, the robotic arm and obstacles were modeled using the bounding box method. …”
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Towards Automated Cadastral Map Improvement: A Clustering Approach for Error Pattern Recognition by Konstantinos Vantas, Vasiliki Mirkopoulou

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Improvement strategies for heuristic algorithms based on machine learning and information concepts: a review of the seahorse optimization algorithm by Shixing Zheng

“…Experimental results demonstrate that the improved SHO algorithm, integrating the logistic-KNN inertia weight optimization strategy and the entropy-based crossover-mutation mechanism, exhibits significant advantages in terms of convergence speed, solution accuracy, and algorithm stability. …”
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Improve Particle Swarm Optimization and Differential Evolution Algorithms Using Nash Bargaining Theory by Marziye Dadvar, Hamidreza Navidi, Hamid Haj Seyyed Javadi, Mitra Mirzarezaee

“…The proposed approach uses a coalition or cooperation model in the game theory to improve the DE and PSO algorithms. …”
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Learning‐based tracking control of AUV: Mixed policy improvement and game‐based disturbance rejection by Jun Ye, Hongbo Gao, Manjiang Hu, Yougang Bian, Qingjia Cui, Xiaohui Qin, Rongjun Ding

“…By combining prior dynamic knowledge and actual sampled data, the proposed approach effectively mitigates the defect caused by the inaccurate dynamic model and significantly improves the training speed of the ADP algorithm. …”
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An advanced CNN-attention model with IFTTA optimization for prediction air consumption of relay nozzles by Shen Min, Shao Ning, Cao Yongbo, Xiong Xiaoshuang, Yang Xuezheng, Wang Zhen, Yu Lianqing

“…This paper proposes a Convolutional Neural Network (CNN)-Attention regression model to predict air consumption of the relay nozzle, enhancing accuracy and efficiency with an Improved Football Team Training Algorithm (IFTTA). …”
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A Two-Stage Optimization Method for Multi-Runway Departure Sequencing Based on Continuous-Time Markov Chain by Guan Lian, Yingzi Wu, Weizhen Luo, Wenyong Li, Yaping Zhang, Xiaoyue Zhang

“…The pushback rate control strategy was extended to multi-runway scenarios to identify the optimal taxiway queue threshold in stage I. In stage II, the pushback rate control strategy with a known queue threshold was introduced into a multi-objective optimization model, aiming to minimize flight delays and operational costs including pushback waiting times, taxi fuel consumption, and environmental impact. …”
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Uncertainty prediction of wind speed based on improved multi-strategy hybrid models by Xinyi Xu, Shaojuan Ma, Cheng Huang

“…Due to insufficient traditional wind speed interval prediction methods for mining nonlinear features, in this paper, a novel interval prediction method was proposed by combining improved wavelet threshold and deep learning (BiTCN-BiGRU) with the nutcracker optimization algorithm (NOA). …”
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Impact of surrogate model accuracy on performance and model management strategy in surrogate-assisted evolutionary algorithms by Yuki Hanawa, Tomohiro Harada, Yukiya Miura

“…Surrogate-assisted evolutionary algorithms (SAEAs) are widely used to solve expensive optimization problems where evaluating candidate solutions is computationally intensive. …”
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Artificial Intelligence Algorithm for Optimal Time Series Data Model by Kang Wang

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Optimizing Models and Data Denoising Algorithms for Power Load Forecasting by Yanxia Li, Ilyosbek Numonov Rakhimjon Ugli, Yuldashev Izzatillo Hakimjon Ugli, Taeo Lee, Tae-Kook Kim

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Multi-Objective Optimal Power Flow of Integrated Transmission and Distribution Network Considering Node Carbon Emission Intensity by ZHANG Xianglong, YUAN Zhaoxiang, DONG Shufeng, LIU Ying, XIAO Zhihong, TIAN Yuzhou

“…[Methods] To address these challenges， a collaborative distributed optimal power flow model based on a heterogeneous decomposition algorithm was proposed. …”
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A Fast Recognition Method for Dynamic Blasting Fragmentation Based on YOLOv8 and Binocular Vision by Ming Tao, Ziheng Xiao, Yulong Liu, Lei Huang, Gongliang Xiang, Yuanquan Xu

“…As the primary method used in open-pit mining, blasting has a direct impact on the efficiency and cost of subsequent operations. Therefore, dynamic identification of rock fragment size after blasting is essential for evaluating blasting quality and optimizing mining plans. …”
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Harmonized Integration of GWO and J-SLnO for Optimized Asset Management and Predictive Maintenance in Industry 4.0 by A. N. Arularasan, P. Ganeshkumar, Mohammad Alkhatib, Tahani Albalawi

“…The study encompasses the application of two different advanced optimization algorithms on asset management and predictive maintenance in Industry 4.0—Grey Wolf Optimization and Jaya-based Sea Lion Optimization (J-SLnO). …”
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A novel two stage neighborhood search for flexible job shop scheduling problem considering reconfigurable machine tools by Yanjun Shi, Chengjia Yu, Shiduo Ning

“…This paper focuses on the flexible job shop scheduling problem with machine reconfigurations (FJSP-MR) and proposes an improved genetic algorithm with a two-stage neighborhood search (IGA-TNS) to minimize total weighted tardiness (TWT). …”
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Optimizing Electric Vehicle Charging with Moth Flame Control Algorithm of Boost-KY Converter by Santosh D. Gadekar, M. Murali

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Optimization on Electric Construction Machinery Considering Time‐of‐Use Electricity Price Based on the Improved Crested Porcupine Optimizer Algorithm by Dawei Wang, Bo Gao, Lei Zhang

“…This paper introduces an innovative algorithm, the improved crested porcupine optimizer (ICPO), which incorporates Latin hypercube sampling for population initialization. …”
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An improved Multi-Objective Whale Optimization Algorithm for hydrodynamic and acoustic performance optimization of Myring-shaped underwater vehicle by Qigan Wang, Yu Dong, Han Wu, Peizhan Cao, Zhijun Zhang

“…These improvements enhance the algorithm’s capability in solving Multi-Objective Optimization (MOP) problems. …”
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Congestion Management Using an Optimized Deep Convolution Neural Network in Deregulated Environment by Dhanadeepika B., Vanithasri M., Chakravarthi M.

“…The most important results for the test system indicating convergence profile, congestion cost, and change in real-power and voltage magnitude are obtained by the simulation in MATLAB, and on the basis of the obtained simulation outcomes, it is evident that the proposed Improved Lion Algorithm optimized Deep Convolution Neural Network displays phenomenal computation performance in minimizing congestion losses at minimum congestion costs. …”
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