Kinematic Constrained RRT Algorithm with Post Waypoint Shift for the Shortest Path Planning of Wheeled Mobile Robots by Sisi Liu, Zhan Zhao, Jun Wei, Qianqian Zhou

“…Once the distance between the new node and the target is within a certain threshold, the tree growth stops and a target connection based on minimum turning radius arc is proposed to generate an initial complete random path. The most significant difference from traditional RRT-based methods is that the proposed method optimizes the path based on Dubins curves through a post waypoint shift after a random path is generated, rather than through parent node selection and rewiring during the exploring tree growth. …”
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Gait and Trajectory Optimization by Self-Learning for Quadrupedal Robots with an Active Back Joint by Ariel Masuri, Oded Medina, Shlomi Hacohen, Nir Shvalb

“…The algorithm actively optimizes 12 of the robot’s dynamic walking parameters. …”
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Performance Improvement of Ensemble Empirical Mode Decomposition for Roller Bearings Damage Detection by Ali Akbar Tabrizi, Luigi Garibaldi, Alessandro Fasana, Stefano Marchesiello

“…It is shown that the proposed method (performance improved EEMD) achieves higher damage detection success rate and creates larger Margin than the original algorithm. …”
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Abnormal Electricity Consumption Behaviors Detection Based on Improved Deep Auto-Encoder by Nvgui LIN, Lanxiu HONG, Daoshan HUANG, Yang YI, Zhixuan LIU, Qifeng XU

“…Because the effective data characteristics are destroyed by the abnormal behaviors, the abnormal behaviors can be detected through comparing the difference between the reconstruction error and the detection threshold. To improve the feature extraction ability and the robustness of AE network, the sparse restrictions and the noise coding are introduced into the auto-encoder, and the hyper-parameters of AE network are optimized through the particle swarm optimization algorithm to improve the learning efficiency and generalization ability. …”
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Application of Machine Learning for Bulbous Bow Optimization Design and Ship Resistance Prediction by Yujie Shen, Shuxia Ye, Yongwei Zhang, Liang Qi, Qian Jiang, Liwen Cai, Bo Jiang

“…Then, a convergence factor is introduced to balance the global and local search abilities of the whale algorithm to improve the convergence speed. The sample space is then iteratively searched using the improved whale algorithm. …”
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Reconstruction of porous media pore structure and simulation effect analysis of multi-index based on SNESIM algorithm by Qing Xie, Jiaqi Gao, Xiaochuang Ye, Jia Li, Yifei Song, Siwen Hu

“…In particular, when dealing with complex pore structures, the accuracy and performance of the SNESIM algorithm need further improvement. Future research will focus on optimizing the algorithm to handle more diverse pore structures and exploring 3D reconstruction methods to more comprehensively describe and analyze the pore characteristics in actual porous media.…”
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Multi-objective operation optimization method of microgrid considering the influence of electric vehicle by Tiefeng Xu, Xiaofang Meng, Fangfang Zheng, Yiduo Zhang, Xin Wu, Mingyang Li

“…Taking the minimum total operating cost and the minimum peak-valley difference of the microgrid in one day as the optimization objective, and considering many constraints such as power balance constraints and output constraints of distributed generation units, the multi-objective optimization function is transformed into a single-objective optimization function by linear weighting method, and the model is solved by particle swarm optimization algorithm. …”
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Low-cost and scalable machine learning model for identifying children and adolescents with poor oral health using survey data: An empirical study in Portugal. by Susana Lavado, Eduardo Costa, Niclas F Sturm, Johannes S Tafferner, Octávio Rodrigues, Pedro Pita Barros, Leid Zejnilovic

“…Such a model could enable scalable and cost-effective screening and targeted interventions, optimizing limited resources to improve oral health outcomes. …”
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Multi-objective production scheduling optimization strategy based on fuzzy mathematics theory. by Heshuai Shen

“…Multi-objective production scheduling faces the problems of inter-objective conflicts, many uncertainty factors and the difficulty of traditional optimization algorithms to deal with complexity and ambiguity, and there is an urgent need to introduce the theory of fuzzy mathematics in order to improve the scheduling efficiency and optimization effect. …”
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Two-Stage Integrated Optimization Design of Reversible Traction Power Supply System by Xiaodong Zhang, Wei Liu, Qian Xu, Zhuoxin Yang, Dingxin Xia, Haonan Liu

“…The parallel cheetah algorithm is employed to solve this complex optimization problem. …”
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Improving energy efficiency and network performance in IaaS cloud with virtual machine placement by Jian-kang DONG, Hong-bo WANG, Yang-yang LI, Shi-duan CHENG

“…The existing virtual machine(VM) placement schemes mostly reduce energy consumption by optimizing utilization of physical server or network element.However,the aggressive consolidation of these resources may lead to network performance degradation.In view of this,a VM placement scheme was proposed to achieve two objectives.One is to minimize the number of activating physical machines and network elements to reduce the energy consumption,and the other is to minimize the maximum link utilization to improve the network performance.This scheme is able to reduce the energy consumption caused by physical servers and network equipment while optimizing the network performance,making a trade off between energy efficiency and network performance.A novel two-stage heuristic algorithm for a solution was designed.Firstly,the hierarchical clustering algorithm based on minimum cut and best fit algorithm was used to optimize energy efficiency,and then,local search algorithm was used to minimize the maximum link utilization.The simulations show that this solution achieves good results.…”
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An Effective QoS-Aware Hybrid Optimization Approach for Workflow Scheduling in Cloud Computing by Min Cui, Yipeng Wang

“…Furthermore, an improved Whale Optimization Algorithm (WOA) based on Lévy flight is proposed. …”
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An Improved Galerkin Framework for Solving Unsteady High-Reynolds Navier–Stokes Equations by Jinlin Tang, Qiang Ma

“…This error indicator guides an AMR algorithm that combines longest-edge bisection with local Delaunay re-triangulation, ensuring optimal mesh adaptation to complex flow features such as boundary layers and vortices. …”
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How Gait Nonlinearities in Individuals Without Known Pathology Describe Metabolic Cost During Walking Using Artificial Neural Network and Multiple Linear Regression by Arash Mohammadzadeh Gonabadi, Farahnaz Fallahtafti, Judith M. Burnfield

“…This study uses Artificial Neural Networks (ANNs) and multiple linear regression (MLR) models to explore the relationship between gait dynamics and the metabolic cost. Six nonlinear metrics—Lyapunov Exponents based on Rosenstein’s algorithm (LyER), Detrended Fluctuation Analysis (DFA), the Approximate Entropy (ApEn), the correlation dimension (CD), the Sample Entropy (SpEn), and Lyapunov Exponents based on Wolf’s algorithm (LyEW)—were utilized to predict the metabolic cost during walking. …”
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An optimization method of multiscale storage tank target detection introducing an attention mechanism by Wenjia Sun, Chunchun Hu, Nianxue Luo, Qiansheng Zhao

“…Finally, the EIOU loss function is employed instead of the CIOU loss function in the original model to improve the algorithm’s accuracy and speed. Experimental results show that the optimized model significantly improves the detection effect on small targets compared with the original YOLOv5 model. …”
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A Modified Social Spider Optimization for Economic Dispatch with Valve-Point Effects by Wenqiang Yang, Tingli Cheng, Yuanjun Guo, Zhile Yang, Wei Feng

“…An improved social spider optimization algorithm, namely, ISSO, is proposed in this paper to solve the ED problem with valve-point effects. …”
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Improvement of Energy Indicators of Asynchronous Motor under the Conditions of Asymmetric Voltage Supply by Boyko A.A., Besarab A.N., Sokolov Y.A., Shapa L.N.

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Technique on Vehicle Damage Assessment After Collisions Using Optical Radar Technology and Iterative Closest Point Algorithm by Shih-Lin Lin, Yi-Hsuan Chen

“…The contributions of this study lie in integrating LiDAR technology with advanced point cloud processing algorithms and a deep learning optimization model for vehicle damage assessment, demonstrating high precision and cost-effectiveness. …”
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Dynamic economic emission dispatch of combined heat and power system based on multi-objective differential evolution algorithm. by Tao Dong

“…The improved multi-objective differential evolution algorithm optimized the fuel cost as low as $2300590 and the pollution emission as low as 200285 kg. …”
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Research on Adaptive Planning of Three-Dimensional Trajectory for Uncrewed Aerial Vehicle Inspection Based on Nonlinear Weibull Algorithm by Zhuang Liu, Ning Yang, Jiaxing Fu, Huanqing Cai, Xuebei Wei

“…Meanwhile, this study constructs a path planning model for inspection UAVs and designs a weighted objective function considering total path length, flight altitude, flight turning angle, and threat model, thereby transforming path planning in three-dimensional space into a constrained multi-objective optimization problem. The results show that under flight environments with varying complexity of obstacle and threat region distribution, compared with the Particle Swarm Optimization algorithm (PSO), Butterfly Optimization Algorithm (BOA), and Reptile Search Algorithm (RSA), NWFRSA can effectively reduce the path cost (by 4.53%–34.47%), contributing to improved.…”
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