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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Machine learning models for predicting interaction affinity energy between human serum proteins and hemodialysis membrane materials by Simin Nazari, Amira Abdelrasoul

“…The application of machine learning in predicting affinity energy holds significant promise for researchers and professionals in hemodialysis. These models, by enabling early interventions in hemodialysis membranes, could enhance patient safety and optimize the care of hemodialysis patients.…”
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Bayesian optimization with Optuna for enhanced soil nutrient prediction: a comparative study with genetic algorithm and particle swarm optimization by Bamidele A. Dada, Nnamdi I. Nwulu, Seun O. Olukanmi

“…The investigation confirms that Optuna-optimized models are at least 13 % more precise than GA and PSO models. …”
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Research on Wellbore Trajectory Optimization and Drilling Control Based on the TD3 Algorithm by Haipeng Gu, Yang Wu, Xiaowei Li, Zhaokai Hou

“…After reinforcement learning training, the trajectory offset is significantly reduced, and the accuracy is greatly improved. This research shows that the TD3 algorithm is superior to the multi-objective optimization algorithm in optimizing key parameters, such as well deviation, kickoff point (KOP), and trajectory length, especially in well deviation and KOP optimization. …”
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Multiobjective Optimization Method for Polymer Injection Molding Based on a Genetic Algorithm by Zhijun Yuan, Hui Wang, Xuebing Wei, Kui Yan, Cheng Gao

“…The optimal combination of the impact parameters is determined using a multiobjective genetic algorithm. …”
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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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Exploring Evolutionary Algorithms for Optimal Power Flow: A Comprehensive Review and Analysis by Harish Pulluri, Vedik Basetti, B. Srikanth Goud, CH. Naga Sai Kalyan

“…It has been more than five decades since optimum power flow (OPF) emerged as one of the most famous and frequently used nonlinear optimization problems in power systems. …”
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Commercial Vehicle Ride Comfort Optimization Based on Intelligent Algorithms and Nonlinear Damping by Shuilong He, Keren Chen, Enyong Xu, Wei Wang, Zhansi Jiang

“…To improve the reliability of ride comfort optimization and analysis, a ride comfort optimization method based on nonlinear damping and intelligent algorithms is proposed. …”
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Light-GBM based minority oversampling model using biomedical data analysis for breast cancer classification by Mukesh Soni, Mohammed Wasim Bhatt, Paul Ofori-Amanfo

“…In the Sparrow Search Algorithm (SSA), piecewise linear chaotic map (PWLCM), novel inertia weights, and a new longitudinal-lateral crossover algorithm are introduced for improvement, followed by the application of the improved SSA algorithm for automatic parameter optimization of Light-GBM. …”
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Microservice Workflow Scheduling with a Resource Configuration Model Under Deadline and Reliability Constraints by Wenzheng Li, Xiaoping Li, Long Chen, Mingjing Wang

“…Experiments on four scientific workflow datasets show that the proposed approach achieves an average cost reduction of 44.59% compared to existing reliability scheduling algorithms, with improvements of 26.63% in the worst case and 73.72% in the best case.…”
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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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Node optimization coverage method under link model in passive monitoring system of three-dimensional wireless sensor network by Zhanjun Hao, Nanjiang Qu, Xiaochao Dang, Jiaojiao Hou

“…In the process of optimal coverage, the traditional genetic algorithm and particle swarm optimization algorithm are introduced and improved. …”
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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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Smoothing Strategies Combined with ARIMA and Neural Networks to Improve the Forecasting of Traffic Accidents by Lida Barba, Nibaldo Rodríguez, Cecilia Montt

“…Two smoothing strategies combined with autoregressive integrated moving average (ARIMA) and autoregressive neural networks (ANNs) models to improve the forecasting of time series are presented. …”
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Optimization of the Naive Bayes Algorithm with SMOTETomek Combination for Imbalance Class Fraud Detection by Arief Tri Arsanto, Arif Faizin, Moch lutfi, Zulfatun Nikmatus Saadah

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Research on Performance Predictive Model and Parameter Optimization of Pneumatic Drum Seed Metering Device Based on Backpropagation Neural Network by Yilong Pan, Yaxin Yu, Junwei Zhou, Wenbing Qin, Qiang Wang, Yinghao Wang

“…The MOPSO algorithm uses the BPNN predictive model as a fitness function to search for the optimal solution for three types of seeds, and the optimized results were verified through bench experiments. …”
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Influence of soil parameters on dynamic compaction: numerical analysis and predictive modeling using GA-optimized BP neural networks by Yu Zhang, Xueshui Chen, Huakang Ge, Zhigang Guo, Xu Li

“…Orthogonal experimental design and single factor analysis were used to quantify the influence of each parameter on the compaction volume. In order to improve the prediction accuracy, this paper introduces genetic algorithm (GA) to optimize the BP neural network model, constructs a multi-factor dynamic compaction prediction model, and compares it with the traditional BP model. …”
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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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Algorithm on joint optimization of power allocation and slot allocation in satellite communication systems by Han HAN, Ying LI, Xu DONG, Xiao-bo GUO, Qin-fei HUANG

“…An algorithm to jointly optimize the power allocation and the slot allocation in order to improve the utilization efficiency of the limited resources on the satellite was proposed.The basic principles of the mutual compensation and mutual independence between these two resources are explored to pave the way for joint optimization.Considering the differences about each station’s channel condition and capacity requirement,a state-combination model for optimally allocating the resources is setted up,so as to adapt the multi-resource usage pattern with each earth station.Targeting at the energy efficiency,an iterative dual optimization algorithm is proposed,and the final optimal policy for resource allocation with low complexity is obtained.With the simulation and analysis,the proposed joint optimization is verified to perform better than the non-joint ones in the perspective of the energy efficiency,especially when the frequency resource (the carrier number) is less.…”
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Prediction and optimization of robot processing technology based on neural network and genetic algorithm by Fusen WU

“…This model can clearly reveal the role of various grinding process parameters in machining and reflect their importance in improving machining efficiency and material removal rate. …”
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