An Improved Hybrid Genetic Algorithm with a New Local Search Procedure by Wen Wan, Jeffrey B. Birch

“…One important challenge of a hybrid genetic algorithm (HGA) (also called memetic algorithm) is the tradeoff between global and local searching (LS) as it is the case that the cost of an LS can be rather high. …”
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An intelligent comprehensive scoring approach based on improved differential evolution algorithm by WANG Rongsheng, WANG Xiaogang, LONG Yixuan, LYU Yisheng, YUAN Zhiming

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An intelligent comprehensive scoring approach based on improved differential evolution algorithm by WANG Rongsheng, WANG Xiaogang, LONG Yixuan, LYU Yisheng, YUAN Zhiming

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Insulator Defect Detection Algorithm Based on Improved YOLOv11n by Junmei Zhao, Shangxiao Miao, Rui Kang, Longkun Cao, Liping Zhang, Yifeng Ren

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Enhancing analogy-based software cost estimation using Grey Wolf Optimization algorithm by Taghi Javdani Gandomani, Maedeh Dashti, Sadegh Ansaripour, Hazura Zulzalil

“…Among the software estimation methods, analogy-based estimation (ABE) is one of the most popular ones. Although this method has been customized in recent years with the help of optimization algorithms to achieve better results, the use of more powerful optimization algorithms can be effective in achieving better results in software size estimation. …”
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An improved deep learning model for soybean future price prediction with hybrid data preprocessing strategy by Dingya CHEN, Hui LIU, Yanfei LI, Zhu DUAN

“…Finally, the high frequency component is decomposed secondarily using variational mode decomposition optimized by beluga whale optimization algorithm. In the deep learning prediction stage, a deep extreme learning machine optimized by the sparrow search algorithm was used to obtain the prediction results of all subseries and reconstructs them to obtain the final soybean future price prediction results. …”
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Research of a spam filter based on improved naive Bayes algorithm by 曹翠玲, 王媛媛, 袁野, 赵国冬

“…In spam filtering filed,naive Bayes algorithm is one of the most popular algorithm,a modified using support vector machine(SVM)of the native Bayes algorithm :SVM-NB was proposed.Firstly,SVM constructs an optimal separating hyperplane for training set in the sample space at the junction two types of collection,Secondly,according to its similarities and differences between the neighboring class mark for each sample to reduce the sample space also increase the independence of classes of each samples.Finally,using naive Bayesian classification algorithm for mails.The simulation results show that the algorithm reduces the sample space complexity,get the optimal classification feature subset fast,improve the classification speed and accuracy of spam filtering effectively.…”
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An Improved Spectral Clustering Community Detection Algorithm Based on Probability Matrix by Shuxia Ren, Shubo Zhang, Tao Wu

“…The similarity graphs of most spectral clustering algorithms carry lots of wrong community information. …”
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YOLOGX: an improved forest fire detection algorithm based on YOLOv8 by Caixiong Li, Yue Du, Xing Zhang, Peng Wu

“…Finally, the proposed Focal-SIoU loss function replaces the original loss function, effectively reducing directional errors by combining angle, distance, shape, and IoU losses, thus optimizing the model training process. YOLOGX was evaluated on the D-Fire dataset, achieving a mAP@0.5 of 80.92% and a detection speed of 115 FPS, surpassing most existing classical detection algorithms and specialized fire detection models. …”
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Research on Day-Ahead Optimal Scheduling of Wind–PV–Thermal–Pumped Storage Based on the Improved Multi-Objective Jellyfish Search Algorithm by Yunfei Hu, Kefei Zhang, Sheng Liu, Zhong Wang

“…It is assessed using the improved multi-objective jellyfish search (IMOJS) algorithm, and its effectiveness is demonstrated through comparison with a fixed-speed pumped storage (FS-PS) system. …”
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Optimizing Rural MG’s Performance: A Scenario-Based Approach Using an Improved Multi-Objective Crow Search Algorithm Considering Uncertainty by Mohammad Hossein Taabodi, Taher Niknam, Seyed Mohammad Sharifhosseini, Habib Asadi Aghajari, Seyyed Mohammad Bornapour, Ehsan Sheybani, Giti Javidi

“…A new optimization method, namely the Improved Multi-Objective Crow Search Algorithm (IMOCSA), is proposed to solve the problem models. …”
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Safety Status Prediction Model of Transmission Tower Based on Improved Coati Optimization-Based Support Vector Machine by Xinxi Gong, Yaozhong Zhu, Yanhai Wang, Enyang Li, Yuhao Zhang, Zilong Zhang

“…This paper presents a safety state prediction model for transmission towers utilizing improved coati optimization-based SVM (ICOA-SVM). Initially, we optimize the coati optimization algorithm (COA) through inverse refraction learning and Levy flight strategy. …”
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Novel Gaussian-Decrement-Based Particle Swarm Optimization with Time-Varying Parameters for Economic Dispatch in Renewable-Integrated Microgrids by Yuan Wang, Wangjia Lu, Wenjun Du, Changyin Dong

“…Background: To address the uncertainties of renewable energy power generation, the disorderly charging characteristics of electric vehicles, and the high electricity cost of the power grid in expressway service areas, a method of economic dispatch optimization based on the improved particle swarm optimization algorithm is proposed in this study. …”
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Residual Life Prediction of Proton Exchange Membrane Fuel Cell Based on Improved ESN by Tiejiang YUAN, Rongsheng LI, Jiandong KANG, Huaguang YAN

“…Aiming at the problem that the current residual effective life prediction (RUL) technique for proton exchange membrane fuel cells (PEMFCs) has poor prediction effect in the medium and long term, a residual life prediction method based on the Improved Gray Wolf Optimization algorithm (IGWO) and Echo State Network (ESN) is proposed, in which the voltage of the electric stack is firstly selected as a health indicator, and the PEMFC dataset is processed by using convolutional smoothing filtering method to carry out data Smoothing and normalization are used to effectively reduce the interference of outliers on the subsequent model training. …”
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Two-layer optimization model of distribution network line loss considering the uncertainty of new energy access by Xiping Ma, Xiping Ma, Xiaoyang Dong, Haitao Xiao, Yaxin Li, Rui Xu, Kai Wei, Juanjuan Cai, Juan Wei

“…Both layers are solved using the Improved Whale Optimization algorithm (IWOA). Then, the IEEE-33 node distribution system was taken as a simulation example to verify the effectiveness and superiority of the proposed model and algorithm.…”
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Vortex-Induced Vibration Performance Prediction of Double-Deck Steel Truss Bridge Based on Improved Machine Learning Algorithm by Yang Yang, Huiwen Hou, Gang Yao, Bo Wu

“…For the prediction of VIV parameters, the Random Forest model is the most effective. The RMSE values of the improved optimal algorithm are 0.017, 0.026, and 0.295, and the R² values are 0.9421, 0.8875, and 0.9462. …”
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COMQ: A Backpropagation-Free Algorithm for Post-Training Quantization by Aozhong Zhang, Zi Yang, Naigang Wang, Yingyong Qi, Jack Xin, Xin Li, Penghang Yin

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Two-Layer Optimal Scheduling and Economic Analysis of Composite Energy Storage with Thermal Power Deep Regulation Considering Uncertainty of Source and Load by Chao Xing, Jiajie Xiao, Xinze Xi, Jingtao Li, Peiqiang Li, Shipeng Zhang

“…The upper layer takes pumped storage as the optimization goal to improve net load fluctuation and the optimal peak load benefit; the lower layer takes the system’s total peak load cost as the optimization goal and obtains a day-before scheduling plan for the energy storage system, using an improved gray wolf algorithm to process it. …”
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Optimization method of time of use electricity price considering losses in distributed photovoltaic access distribution network by Tianshou Li, Qing Xu, Weiwu Li, Xinying Wang, Zhengying Liu

“…And refer to the basic requirements for electricity pricing in the distribution network, set a series of constraints for optimizing electricity prices. Applying an improved imperialist competition algorithm this paper integrates Tent chaotic reverse learning to solve a multi-objective optimization model and obtain an optimized time of use electricity pricing plan. …”
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An Application of Quasi Newton Algorithm and Improvement of Sliding Surface for Robot Control by Chi-Ngon Nguyen, Thanh Tung Pham

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