Improved AC-GA based data association method for multi-target tracking by YUAN Dong-hui1, LIU Da-you1, SHEN Shi-qun1

“…An AC-GADA（ant colony-genetic algorithm data association） algorithm was proposed to deal with the data as-sociation problem for multi-target tracking.This algorithm designed difference pheromone for each ant and improved global pheromone increment model,and combined crossover and mutation strategy with fitness of population model in or-der to improve rate of convergence and avoid the appearance of local extremum.The comparison with ACDA（ant colony data association） and JPAD（joint pobabilistic data association） proved its efficiency and superiority.…”
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Improving SLICES crystal representation through CHGNet integration and parameter tuning by Bizhu Zhang, Kedeng Wu, Chang Zhang, Hang Xiao, Liangliang Zhu

“…To bridge this gap, we present an enhanced approach to the simplified line-input crystal-encoding system (SLICES) representation by incorporating the Crystal Hamiltonian Graph Neural Network (CHGNet) machine learning force field model. Comprehensive evaluations across multiple datasets (MP-20, MP21-40, and MOF) using different neighbor recognition algorithms (EconNN and CrystalNN) show that our approach outperforms the original in reconstructing structures with fewer than 20 atoms per unit cell, achieving up to a 1.34% improvement in reconstruction rate (from 92.55% to 93.89%). …”
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An Improved Unscented Kalman Filter Applied to Positioning and Navigation of Autonomous Underwater Vehicles by Jinchao Zhao, Ya Zhang, Shizhong Li, Jiaxuan Wang, Lingling Fang, Luoyin Ning, Jinghao Feng, Jianwu Zhang

“…The results indicate that, compared with the UKF algorithm and the ARUKF, the improved algorithm reduces attitude angle errors by 45%, speed errors by 44%, and three-dimensional position errors by 47%. …”
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An Improved Symbiosis Particle Swarm Optimization for Solving Economic Load Dispatch Problem by Jianxia Zhang, Jianxin Zhang, Feng Zhang, Minglu Chi, Linbin Wan

“…At last, the economic load dispatch problem could be optimized by the proposed improved symbiosis particle swarm optimization algorithm. …”
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Driving Strategy Using an Improved Ant Colony System for Energy-Efficient Train by Chengda Yang, Kun Miao, Jieyuan Wang

“…To solve this model efficiently, an improved ant colony system algorithm with the difference edges (ACSd) is proposed, which takes the heuristic effect of the difference between the best solutions of two adjacent iterations, i.e., “the difference edges,” into account. …”
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Environmental and Economic Dispatching of Fire-Wind Combined System Based on Improved MOPSO by Li Rongshuai, Du Ruiqi, Lu Yi, Jiang Shan

“…Then, an improved multi-objective particle swarm optimization algorithm, LRMOPSO, is proposed by combining multi-objective particle swarm optimization algorithm, Levy flight jamming strategy and reverse learning strategy. …”
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Research on Path Planning of Agricultural UAV Based on Improved Deep Reinforcement Learning by Haitao Fu, Zheng Li, Weijian Zhang, Yuxuan Feng, Li Zhu, Xu Fang, Jian Li

“…Through simulation experiments, the BL-DQN algorithm achieved a 41.68% improvement in coverage compared with the traditional DQN algorithm. …”
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YOLO-APDM: Improved YOLOv8 for Road Target Detection in Infrared Images by Song Ling, Xianggong Hong, Yongchao Liu

“…Replacing YOLOv8’s C2f module with C2f-DCNv3 increases the network’s ability to focus on the target region while lowering the amount of model parameters. The MSCA mechanism is added after the backbone’s SPPF module to improve the model’s detection performance by directing the network’s detection resources to the major road target detection zone. …”
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An Improved Method for Single Tree Trunk Extraction Based on LiDAR Data by Jisheng Xia, Sunjie Ma, Guize Luan, Pinliang Dong, Rong Geng, Fuyan Zou, Junzhou Yin, Zhifang Zhao

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An Improved Crop Disease Identification Method Based on Lightweight Convolutional Neural Network by Tingzhong Wang, Honghao Xu, Yudong Hai, Yutian Cui, Ziyuan Chen

“…Then the feature map after each convolution is obtained by using transferred revolution, and the model is adjusted according to the feature map to further improve the effect of model recognition. …”
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An Improved Large Neighborhood Search for Network-Level Airport Slot Allocation Optimization by Qiangzhe Wang, Yuanyuan Ma, Yifan Xu, Zhiyuan Shen, Dan Li

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An Optimized Path Planning Method for Coastal Ships Based on Improved DDPG and DP by Yiquan Du, Xiuguo Zhang, Zhiying Cao, Shaobo Wang, Jiacheng Liang, Fengge Zhang, Jiawei Tang

“…In this paper, an optimized path planning method for coastal ships based on improved Deep Deterministic Policy Gradient (DDPG) and Douglas–Peucker (DP) algorithm is proposed. …”
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An Improved Pose Estimation Method Based on Projection Vector With Noise Error Uncertainty by Jiashan Cui, Changwan Min, Xiangyun Bai, Jiarui Cui

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Big Data Cleaning Based on Improved CLOF and Random Forest for Distribution Networks by Jie Liu, Yijia Cao, Yong Li, Yixiu Guo, Wei Deng

“…Experimental results show that outlier detection is accurate and suitable for any shape and multidimensional power big data. The improved Random Forest imputation algorithm is suitable for all missing forms, with higher imputation accuracy and better model stability. …”
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Evaluation of Airport Runway Blockade Effectiveness Based on Improved Convolutional Neural Network by Cao Longping, Chen Mou, Zhou Tongle

“…In response to the inefficiency and inability to utilize image data inherent in traditional airport runway blockade effectiveness assessment methods, this paper presents an improved convolutional neural network algorithm for assessing the blockade effectiveness of airport runways. …”
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A New Mask R-CNN-Based Method for Improved Landslide Detection by Silvia Ullo, Amrita Mohan, Alessandro Sebastianelli, Shaik Ahamed, Basant Kumar, Ramji Dwivedi, Ganesh R. Sinha

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An Accurate Book Spine Detection Network Based on Improved Oriented R-CNN by Haibo Ma, Chaobo Wang, Ang Li, Aide Xu, Dong Han

“…This allows for a more accurate computation of anchor box aspect ratios that are better aligned with the book spine dataset, enhancing the model’s training performance. We conducted comparison experiments between the proposed model and other state-of-the-art models on the book spine dataset, and the results demonstrate that the proposed approach reaches an mAP of 90.22%, which outperforms the baseline algorithm by 4.47 percentage points. …”
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A spatial bearing fault classification method based on improved APSMOTE-WKMFA by CHEN Chao, YANG Chenhao, XU Haosen, WAN Ouying, HAN Liling

“…Aiming at the problem of poor classification performance of a model for a few classes of fault samples in the case of category imbalance, the spatial bearing fault classification method based on an improved affinity propagation synthetic minority oversampling technique-wavelet kernel marginal Fisher analysis （APSMOTE-WKMFA） was proposed.MethodsFirstly, the geodesic distance was used as the similarity metric for the affinity propagation algorithm, and the synthetic minority oversampling technique （SMOTE） was used to generate samples in the filtered subclusters up to the class balance. …”
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Optimization of Ship Permanent Magnet Synchronous Motor ADRC Based on Improved QPSO by Hongbo Xu, Jundong Zhang, Jiale Liu, Yang Cao, Ao Ma

“…To address the impact of load variations, external environmental changes, and the tuning of the parameters on Permanent Magnet Synchronous Motors (PMSMs) used in ships, this study proposes an Active Disturbance Rejection Control (ADRC) strategy for PMSMs, optimized by the Quantum-behaved Particle Swarm Optimization (QPSO) algorithm. First, based on the PMSM model, the study addresses the limited disturbance rejection capability of the traditional fal function in the Extended State Observer (ESO) of conventional ADRC. …”
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Microgrid Load Forecasting Based on Improved Long Short-Term Memory Network by Qiyue Huang, Yuqing Zheng, Yuxuan Xu

“…In this paper, a load-forecasting algorithm for microgrid based on improved long short-term memory neural network (LSTM) is proposed. …”
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