Hybrid Swarm Intelligence and Human-Inspired Optimization for Urban Drone Path Planning by Yidao Ji, Qiqi Liu, Cheng Zhou, Zhiji Han, Wei Wu

“…Specifically, competitive and supportive behaviors are mathematically modeled to enhance particle learning strategies and improve global search capabilities in the mid-optimization phase. …”
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Design and Control for Piezoelectric Energy Harvester Based on a Heuristic Optimization Algorithms by Habeeb Jaber Nekad, Diyah Kammel Shary, Oday Alahmad

“…The model output response is improved after adjusting the PID controller in line with optimization algorithms as compared with the conventional PID controller. …”
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Multi-objective optimization and characteristic analysis of contra-rotating fan double-row blades coupling by Xinyu ZHANG, Hua JIANG, Wuqi GONG

“…The sample set data is used to construct a neural network surrogate model, and the weights and thresholds of the neural network are optimized in combination with the genetic algorithm to improve the generalization ability of the surrogate model. …”
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Optimization of Flexible Rotor for Ultrasonic Motor Based on Response Surface and Genetic Algorithm by Bo Chen, Jiyue Yang, Haoyu Tang, Yahang Wu, Haoran Zhang

“…This paper presents an optimization method that combines the Kriging response surface model with a multi-objective genetic algorithm (MOGA). …”
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A Two-Stage Bin Packing Algorithm for Minimizing Machines and Operators in Cyclic Production Systems by Yossi Hadad, Baruch Keren

“…The results of our algorithm led to significant cost savings and improved scheduling performance. …”
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Optimizing Imbalanced Data Classification: Under Sampling Algorithm Strategy with Classification Combination by Nauval Dwi Primadya, Adhitya Nugraha, Sahrul Yudha Fahrezi, Ardytha Luthfiarta

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Joint beam hopping and coverage control optimization algorithm for multibeam satellite system by Guoliang XU, Feng TAN, Yongyi RAN, Feng CHEN

“…To improve the performance of multibeam satellite (MBS) systems, a deep reinforcement learning-based algorithm to jointly optimize the beam hopping and coverage control (BHCC) algorithm for MBS was proposed.Firstly, the resource allocation problem in MBS was transformed to a multi-objective optimization problem with the objective maximizing the system throughput and minimizing the packet loss rate of the MBS.Secondly, the MBS environment was characterized as a multi-dimensional matrix, and the objective problem was modelled as a Markov decision process considering stochastic communication requirements.Finally, the objective problem was solved by combining the powerful feature extraction and learning capabilities of deep reinforcement learning.In addition, a single-intelligence polling multiplexing mechanism was proposed to reduce the search space and convergence difficulty and accelerate the training of BHCC.Compared with the genetic algorithm, the simulation results show that BHCC improves the throughput of MBS and reduces the packet loss rate of the system, greedy algorithm, and random algorithm.Besides, BHCC performs better in different communication scenarios compared with a deep reinforcement learning algorithm, which do not consider the adaptive beam coverage.…”
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Prediction and optimization of robot processing technology based on neural network and genetic algorithm by Fusen WU

“…The optimal process parameter combination determined through genetic algorithm optimization is a radial cutting depth of 2.28 mm, an axial cutting depth of 2.98 mm, a spindle speed of 9 586.65 r/min and a feed rate of 2 207.67 mm/min. …”
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Investigating the Performance of Open-Vocabulary Classification Algorithms for Pathway and Surface Material Detection in Urban Environments by Kauê de Moraes Vestena, Silvana Phillipi Camboim, Maria Antonia Brovelli, Daniel Rodrigues dos Santos

“…Our approach uses large language models (LLMs) to improve the accuracy of classifying different pavement types. …”
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ISOA‐DBN: A New Data‐Driven Method for Studying the Operating Characteristics of Air Conditioners by Mengran Zhou, Qiqi Zhang, Feng Hu, Ling Wang, Guangyao Zhou, Weile Kong, Changzhen Wu, Enhan Cui

“…We aim at solving the problems of scarcity, single type, low accuracy and difficult construction of high‐quality data sets available for air conditioning operation characteristic models at present. This paper proposes a construction method of air conditioning operation characteristic model based on an improved seagull optimization algorithm to optimize deep belief network (ISOA‐DBN). …”
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Aerodynamic Shape Optimization of a Missile Using a Multiobjective Genetic Algorithm by Ahmet Şumnu, İbrahim Halil Güzelbey, Orkun Öğücü

“…Multiobjective Genetic Algorithm (MOGA) was used to optimize missile geometry. …”
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A low-carbon optimization scheduling method of CIES based on PPO algorithm by CHEN Fan, WU Lingxiao, WANG Man, LYU Ganyun, ZHANG Xiaolian

“…The tiered carbon trading mechanism and optimization scheduling model solving algorithm are pivotal for the community integrated energy system (CIES). …”
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Optimizing Deep Learning Algorithms for Effective Chicken Tracking through Image Processing by Saman Abdanan Mehdizadeh, Allan Lincoln Rodrigues Siriani, Danilo Florentino Pereira

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Optimizing Photovoltaic Panel Performance: A Comparative Study of Meta-Heuristic Algorithms by M. Sundar Rajan

“…This paper addresses the parameter estimation of four distinct PV panel models—PV-RTC, PV-PWP 201, PV-STM6 40/36, and PV-STP6 120/36—using a range of meta-heuristic optimization algorithms. …”
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Optimizing firefighting resilience in airports through genetic algorithms and decision-making frameworks by Yulong Zhu, Wei Tian, Xuhong Jia, Quanyi Liu

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Optimization of the Driving Mode Transformation of Hybrid Electric Bus based on Genetic Algorithm by Zhao Lijun, Li Shoucheng, Wei Guangpu, Zhang Hongsheng

“…The hybrid electrical city bus has two power sources to drive vehicle,so the control of vehicle driving mode transformation is become the core of the vehicle control strategy.It not only influences the vehicle fuel economy and emissions,but also influences the driving comfort of the vehicle.An HEV simulation model is built for performance analysis by interlinking of advanced software AVL CRUISE and Matlab/Simulink.By adjusting threshold of the driving mode transformation,the mode can be transformed smoothly.For achieving minimum equivalent fuel consumption,the genetic algorithm（GA）optimization method is applied to get the optima of control parameters which affect the vehicle driving mode transformation in different city bus cycles including Europe and China.The vehicle fuel economy is further improved.…”
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An image processing technique for optimizing industrial defect detection using dehazing algorithms. by Xuanyi Zhao, Xiaohan Dou, Gengpei Zhang

“…The overall performance surpasses CNN and MADNet models, and verification using the improved YOLOv8 model significantly enhances defect detection confidence while greatly reducing missed detections. …”
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Optimization of particle filter tracking algorithm based on weakly supervised attribute learning by Hui Zhang, Dawang Shen

“…Abstract This study proposes an optimization method for particle filter tracking algorithm to solve the issues of low recognition efficiency and poor tracking accuracy faced by existing target tracking algorithms in complex environments. …”
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Optimization and Validation of Wafer Surface Defect Detection Algorithm Based on RT-DETR by Ao Xu, Yanwei Li, Hongbo Xie, Rui Yang, Jianjie Li, Jiaying Wang

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Optimizing piezoelectric actuator placement for enhanced vibration control using genetic algorithms by Shuqing Wang, Huichao Jin, Yu Wang, Junyi Huo, Xudong Liu

“…This study proposes an optimization framework for piezoelectric sensor and actuator configurations in cantilever beams using a genetic algorithm. …”
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