Inversion of electric field component Ex in the SOTEM method based on the improved particle swarm optimization algorithm by Jifeng ZHANG, Changjian CHEN, Yuteng LI, Xiran YOU, Ziben MA

“…The performance of the improved PSO algorithm was verified using the typical three-, five-, and seven-layered geoelectric models constructed in this study.Results and ConclusionsThe results of this study indicate that for the five- and seven-layered geoelectric models, the damped least squares method yielded average inversion errors of 0.34% and 4.68%, respectively, while the improved PSO algorithm yielded average inversion errors of 0.21% and 0.87%, respectively. …”
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Multi-UAV Delivery Path Optimization Based on Fuzzy C-Means Clustering Algorithm Based on Annealing Genetic Algorithm and Improved Hopfield Neural Network by Song Liu, Di Liu, Meilong Le

“…This study develops an MTSP model for multi-UAV delivery optimization from a central hub, proposing a hybrid algorithm that integrates genetic simulated annealing-enhanced clustering with an improved Hopfield neural network to minimize the total flight distance. …”
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An Improved Crayfish Algorithm-Based Neural Network Method for Modeling Microstrip Patch Antennas by Shao-Long Cao, Yu Shao, Yang Wang, Ju Tan, Jie Zhang

“…This paper proposes an improved crayfish optimization algorithm (ICOA) to optimize the initial weights and biases of the neural network, aiming to enhance both convergence accuracy and speed. …”
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Coupled Optimization of UAV Cluster Path Optimization and Task Assignment on a Mobile Platform by Gaohua Fu, Yexin Song, Yanjie Wu

“…Combining the UAV turning angle, minimum direct flight trajectory and other flight characteristics, the path optimization model on the 3D raster map is established with the objectives of shortest flight time and minimum UAV destruction, and the optimal path between the vertices of each mission is derived by using an improved Gray Wolf Optimization algorithm. …”
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Coevolutionary Algorithm with Bayes Theorem for Constrained Multiobjective Optimization by Shaoyu Zhao, Heming Jia, Yongchao Li, Qian Shi

“…Previous studies have demonstrated that multi-swarm optimization models exhibit robust performance in CMOPs; however, their high computational resource demands can hinder convergence efficiency. …”
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Revolutionizing proton exchange membrane fuel cell modeling through hybrid aquila optimizer and arithmetic algorithm optimization by Manish Kumar Singla, S. A. Muhammed Ali, Ramesh Kumar, Pradeep Jangir, Mohammad Khishe, G. Gulothungan, Haitham A. Mahmoud

“…Abstract Parameter identification in a Proton Exchange Membrane Fuel Cell (PEMFC) entails the application of optimization algorithms to ascertain the optimal unknown variables essential for crafting an accurate model that predicts fuel-cell performance. …”
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AUV path planning method based on improved sparrow search algorithm by Lijun TANG, Yunxia FAN, Xingyu ZHOU, Qian SUN

“…ObjectiveTo address the challenges of complex underwater environments, particularly the uncertainties in ocean currents, this study proposes an improved sparrow search algorithm (ISSA) for autonomous underwater vehicles (AUVs) path planning. …”
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Hybrid DE-EM Algorithm for Gaussian Mixture Model-Based Wireless Channel Multipath Clustering by Yupeng Li, Jianhua Zhang, Ruisi He, Lei Tian, Hewen Wei

“…In the GMM field, the expectation-maximization (EM) algorithm is usually utilized to estimate the model parameters. …”
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New Maps of Lunar Surface Oxide Abundances and Mg# Using an Optimized Ensemble Learning Algorithm by Chaofa Bian, Kefei Zhang, Yunzhao Wu, Suqin Wu, Yu Lu, Yabo Duan, Huajing Wu, Zhenxing Zhao, Wei Wu

“…In this study, multisource data, specifically KAGUYA multiband imager (MI) data and Diviner Christiansen feature (CF) products, referred to as MI-CF, combined with an ensemble learning algorithm optimized by improved particle swarm optimization (IPSO), were utilized to produce new maps of six oxides (FeO, TiO₂, Al₂O₃, CaO, MgO, and SiO₂) and Mg# at a resolution of 59 m/pixel within the Moon's 65° N/S range. …”
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Recognition algorithm of piano playing music notes based on improved hidden Markov model by Ziwei Wang

“…The recognition process of piano playing music notes is affected by low-frequency components, resulting in suboptimal features that affect recognition accuracy. Therefore, an improved hidden Markov model based recognition algorithm for piano playing music notes is proposed. …”
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Path Planning for Construction Robot Based on the Improved A* Algorithm and Building Information Modeling by Dejiang Wang, Bolong Liu, Haili Jiang, Panpan Liu

“…Finally, the improved A* algorithm is employed to perform path planning within the environment map generated from the BIM model, resulting in the generation of the optimal path. …”
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Diagnosis model for action problems of table tennis beginners based on improved DTW algorithm by Zhiguo Xin

“…To enhance the skills of beginners, a diagnosis model for table tennis beginner movement problems based on sensors and an improved dynamic time-warping algorithm is proposed. …”
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Dual-Resource Scheduling with Improved Forensic-Based Investigation Algorithm in Smart Manufacturing by Yuhang Zeng, Ping Lou, Jianmin Hu, Chuannian Fan, Quan Liu, Jiwei Hu

“…In the first stage, an improved multi-objective FBI algorithm is used to obtain the Pareto front solutions of this model, in which a hybrid real and integer encoding–decoding method is used for exploring the solution space and a fast non-dominated sorting method for improving efficiency. …”
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Energy management strategy for hybrid electric vehicle based on improved PPO algorithm by Chao MA, Tong SUN, Lei CAO, Kun YANG, Wenjing HU

“…In order to improve the economy of power-split hybrid electric vehicle (HEV),a longitudinal dynamics model of the entire HEV vehicle was established,and an energy management strategy (EMS) based on strategy entropy optimization with an improved proximal policy optimization (PPO) algorithm was proposed. …”
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An Optimization Model for Production Scheduling in Parallel Machine Systems by Leting Zu, Wenzhu Liao, Xiaoxia Yang

“…A numerical example is presented to illustrate the computational process, accompanied by an extensive discussion of the results showcasing improved performance. Furthermore, the optimization model developed in this paper can be adapted to tackle the production scheduling problem with modifications tailored for parallel machines.…”
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Improving Temperature Prediction Precision for Aerial Cameras by Correcting Structure and Parameters of Thermal Network Models by Yue Fan, Wei Feng, Zhenxing Ren, Bingqi Liu, Jinying Li

“…This paper introduces a methodology for improving the precision of temperature predictions generated by thermal network models for aerial cameras, which involves correcting the structure and parameters of the thermal network. …”
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Control model of community elderly recreational exercise assistive robot based on improved dense trajectory algorithm by Ruisheng Jiao, Haibin Wang, Juan Luo

“…Specifically, the study deeply refined the control process of a health and exercise assisted robot, and combined action capture to construct a health and exercise assisted robot model. The control model of the health and exercise assisted robot was optimized using an improved dense algorithm. …”
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Improved aquila optimizer for swarm-based solutions to complex engineering problems by Himanshu Sharma, Krishan Arora, Raghav Mahajan, Syed Immamul Ansarullah, Farhan Amin, Hussain AlSalman

“…Firstly, IAO was compared using 23 classical optimization functions. The achieved results demonstrate that the proposed model outperforms various champion algorithms. …”
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Landslide Forecasting Model Based on PCA and Improved CS-RBF by WANG Lianxia, LI Limin, FANG Zihao, REN Ruibin, FU Zhentao, CUI Chengtao

“…Various models including back propagation (BP), RBF, genetic algorithm-RBF (GA-RBF), CS-RBF, and others are compared with the improved CS-RBF model through experimental analysis. …”
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Weakly supervised semantic segmentation and optimization algorithm based on multi-scale feature model by Changzhen XIONG, Hui ZHI

“…In order to improve the accuracy of weakly-supervised semantic segmentation method,a segmentation and optimization algorithm that combines multi-scale feature was proposed.The new algorithm firstly constructs a multi-scale feature model based on transfer learning algorithm.In addition,a new classifier was introduced for category prediction to reduce the failure of segmentation due to the prediction of target class information errors.Then the designed multi-scale model was fused with the original transfer learning model by different weights to enhance the generalization performance of the model.Finally,the predictions class credibility was added to adjust the credibility of the corresponding class of pixels in the segmentation map,avoiding false positive segmentation regions.The proposed algorithm was tested on the challenging VOC 2012 dataset,the mean intersection-over-union is 58.8% on validation dataset and 57.5% on test dataset.It outperforms the original transfer-learning algorithm by 12.9% and 12.3%.And it performs favorably against other segmentation methods using weakly-supervised information based on category labels as well.…”
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