Self-Tuning Parameters of the Proposed Fuzzy Immune Integral Controller to Improve the Performance of the Standard P&O-MPPT Strategy by Ramazan Ayaz

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Optimization Method of Generation Rights Transaction Mechanism for Power System Accommodation Improvement by Haoliang XU, Panrun JIN, Jiheng JIANG, Zongxiang LU, Ying QIAO

“…The simulation results validate the effectiveness of the proposed algorithm in quick optimization and efficiency evaluation in monthly and annual scale.…”
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Exponential Improvements in the Simulation of Lattice Gauge Theories Using Near-Optimal Techniques by Mason L. Rhodes, Michael Kreshchuk, Shivesh Pathak

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Camera Calibration Optimization Algorithm Based on Nutcracker Optimization Algorithm by Lei Li, Zelong Xiao, Taiyang Hu

“…This article proposes a camera calibration optimization algorithm based on the Starling-Inspired Strategy optimization algorithm, which improves calibration accuracy and stability by combining chaotic mapping and sine cosine optimization strategies. …”
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Prediction of the 180 day functional outcomes in aneurysmal subarachnoid hemorrhage using an optimized XGBoost model by Weichong Zhou, Xingfu Liao, Hui Shi, Mingfeng Wang, Yunchong Xiao, Xilu Yu, Yilong Wu, YanYi Liu, Yin Peng, Hai Su

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Frequency minimum inertia calculation of complex power systems based on an improved simulated annealing algorithm by Qiang Zhang, Qi Jia, Tingqi Zhang, Hui Zeng, Chao Wang, Wansong Liu

“…Then, based on the whole process of frequency response, we construct a power system minimum inertia assessment model taking into account the virtual inertia of new energy sources, and introduce an improved simulated annealing algorithm to solve the problem; the results validate the accuracy of the method through the IEEE-14 node model; the discussion section points out that this method provides a feasible solution for the inertia situational awareness of power system, which is helpful for the optimization of the operation, and also proposes that in the future we can take into account more uncertainties to improve the model and algorithm and to enhance the practicability and adaptability of this method. …”
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Research on Monthly Runoff Forecast in Dry Seasons Based on GEO-RVM Model by ZHANG Yajie, CUI Dongwen

“…To improve the accuracy of monthly runoff forecasts during dry seasons,this study proposes a forecasting method that combines the golden eagle optimization (GEO) algorithm and the relevance vector machine (RVM).On the basis of the runoff data of 67 a from a hydrological station in Yunnan Province,the monthly runoff with good correlation before the forecast month is selected as the influencing factor of forecasts,and the influencing factor is reduced in dimension by principal component analysis (PCA).The kernel width factor and hyperparameters of RVM are optimized by the GEO algorithm,and the GEO-RVM model is built to forecast the monthly runoff of the station during the dry season from November to April of the following year.Moreover,the forecast results are compared with those of the GEO-based support vector machine (SVM) model (GEO-SVM).The results demonstrate that the average relative errors of the GEO-RVM model for the monthly runoff forecasts from November to April of the following year are 8.59%,7.34%,5.97%,6.07%,5.99%,and 5.04%,respectively,which means the accuracy is better than that of the GEO-SVM model.The GEO algorithm can effectively optimize the kernel width factor and hyperparameters of RVM,and the GEO-RVM model has better forecast accuracy,which can be used for monthly runoff forecasting during dry seasons.…”
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The Optimization of Supply–Demand Balance Dispatching and Economic Benefit Improvement in a Multi-Energy Virtual Power Plant within the Jiangxi Power Market by Tang Xinfa, Wang Jingjing, Wang Yonghua, Wan Youwei

“…The results demonstrate that the proposed scheduling optimization method significantly improves economic benefits while ensuring grid stability. …”
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Improving Airport Flight Prediction System Based on Optimized Regression Vector Machine Algorithm by Baraa Yousif Salman, Jaber Parchami

“…In this research, the optimized support vector regression (SVR) algorithm has been used to improve the accuracy of air delay prediction. …”
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Multi-Search Strategy-based Improved Water Flow Optimizer Algorithm for Cluster Analysis by Prateek Thakral, Yugal Kumar

“…Hence, this work presents an improved water flow optimizer (IWFO) algorithm for cluster analysis that can address the issues of traditional and heuristic algorithms. …”
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Detection of litchi fruit maturity states based on unmanned aerial vehicle remote sensing and improved YOLOv8 model by Changjiang Liang, Changjiang Liang, Dandan Liu, Dandan Liu, Weiyi Ge, Weiyi Ge, Wenzhong Huang, Wenzhong Huang, Yubin Lan, Yubin Lan, Yubin Lan, Yongbing Long, Yongbing Long, Yongbing Long, Yongbing Long

“…The improved model demonstrated robust performance in different application scenarios. …”
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Short-Term Power Load Forecasting Method based on Glowworm Swarm Optimization Algorithm by Haihong FAN

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Multi-step Prediction of Monthly Sediment Concentration Based on WPT-ARO-DBN/WPT-EPO-DBN Model by GAO Xuemei, CUI Dongwen

“…Accurate multi-step sediment concentration prediction is of significance for regional soil erosion control,flood control and disaster reduction.To improve the multi-step prediction accuracy of sediment concentration and the prediction performance of the deep belief network (DBN),this paper proposes a multi-step prediction model of monthly sediment concentration by combining the artificial rabbit optimization (ARO) algorithm,eagle habitat optimization (EPO) algorithm,and DBN based on wavelet packet transform (WPT).The model is validated using time series data of monthly sediment concentration from Longtan Station in Yunnan Province.Firstly,WPT is employed to decompose the time series data of the monthly sediment concentration of the case in three layers,and eight more regular subsequence components are obtained.Secondly,the principles of ARO and EPO algorithms are introduced,and hyperparameters such as the neuron number in the hidden layer of DBN are optimized by ARO and EPO.Meanwhile,WPT-ARO-DBN and WPT-EPO-DBN prediction models are built,and WPT-PSO (particle swarm optimization)-DBN and WPT-DBN are constructed for comparative analysis.Finally,four models are adopted to predict each subsequence component,and the predicted values are superimposed to obtain the multi-step prediction results of the final monthly sediment concentration.The results are as follows.① WPT-ARO-DBN and WPT-EPO-DBN models have satisfactory prediction effects on the monthly sediment concentration of the case from one step ahead to four steps ahead.This yields sound prediction results for five steps ahead.The prediction effect for six steps ahead and seven steps ahead is average,and the prediction accuracy for eight steps ahead is poor and cannot meet the prediction accuracy requirements.② The multi-step prediction performance of WPT-ARO-DBN and WPT-EPO-DBN models is superior to WPT-PSO-DBN models and far superior to WPT-DBN models,with higher prediction accuracy,better generalization ability,and larger prediction step size.③ ARO and EPO can effectively optimize DBN hyperparameters,improve DBN prediction performance,and have better optimization effects than PSO.Additionally,WPT-ARO-DBN and WPT-EPO-DBN models can give full play to the advantages of WPT,new swarm intelligence algorithms and the DBN network and improve the multi-step prediction accuracy of monthly sediment concentration,and the prediction accuracy decreases with the increasing prediction steps.…”
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Bus frequency optimization in a large-scale multi-modal transportation system: integrating 3D-MFD and dynamic traffic assignment by Kai Yuan, Dandan Cui, Jiancheng Long

“…A surrogate model-based algorithm is used to solve the bi-level programming problem.…”
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Modification of the WaldBoost algorithm to improve the efficiency of solving pattern recognition problems in real-time by A. N. Chesalin, S. Ya. Grodzenskiy, M. Yu. Nilov, A. N. Agafonov

“…The efficiency of the proposed algorithm is shown by specific examples. The results are confirmed by statistical modeling on several data sets. …”
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Electrical Fault Diagnosis Method for Tunneling Equipment Based on Fault Simulation and Optimized Particle Swarm Algorithm by Huan Zou, Xueping Zhang, Xin Wang, Yu Li

“…To address the challenges of scarce training data and poor adaptability to dynamic working conditions in electrical fault diagnosis for tunneling equipment, this study proposes an intelligent diagnosis model based on fault simulation and Improved Particle Swarm Optimization (IPSO). …”
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Improved MobileVit deep learning algorithm based on thermal images to identify the water state in cotton by Kaijun Jin, Jihong Zhang, Ningning Liu, Miao Li, Zhanli Ma, Zhenhua Wang, Jinzhu Zhang, Feihu Yin

“…This study introduces a method for identifying the moisture state of cotton using an enhanced MobileVit deep learning algorithm. This approach incorporates the Efficient Channel Attention (ECA) mechanism into the Fusion component of the MobileVit model, optimizes the first convolution in the Fusion component by replacing it with Depthwise Separable Convolution (DsConv), and substitutes the Local representation with the MobileOne block. …”
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Intelligent decision-making for mine airflow on demand based on the improved artificial bee colony algorithm by ZHANG Lang, LEI Shuang, LI Wei, LIU Yanqing

“…To address the issue of slow convergence speed in solving the unconstrained optimization mathematical model of mine airflow control using existing metaheuristic algorithms, an intelligent decision-making method for mine airflow on demand based on an improved Artificial Bee Colony (ABC) algorithm was proposed. …”
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Optimization of dynamic parameters of straddle monorail vehicle to improve pantograph-catenary contact quality by ZHANG Yuejun, YANG Zhen, DU Zixue, WEN Xiaoxia, XU Zhouzhou

“…In order to reduce the abrasion on the sliding block, a sensitivity analysis method was used in this paper to analyze the influence degree of vehicle dynamics parameters on the coupling force of pantograph and catenary based on the dynamic simulation analysis model of "vehicle-pantograph-catenary" system. The average value of the pantograph-catenary contact force was considered as the optimization objective, and dynamics parameters of the vehicle were optimized by non-dominated sorting genetic algorithm (NSGA-II). …”
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Optimization configuration method of integrated energy system for reliability improvement of distribution network by SHI Mingming, MIAO Huiyu, GUO Jiahao, JIANG Yunlong, XIAO Xiaolong

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