An Improved Robust Filtering Recursive Algorithm for Stochastic Uncertain Vehicle INS/OD Systems With Anomalous Measurements by Shuang Pan, Chao Wang, Chunlei Zhang, Linping Feng

“…The main contributions of this study can be summarized as: 1) Incremental odometer measurement model is proposed for INS/OD integrated navigation system to solve the problem of calculation of abnormal odometer information. 2) Robust filter recursive algorithm for stochastic uncertain system with outlier measurements caused by vehicle’s slipping and skidding is proposed to improve the robustness of the INS/OD integrated navigation system. …”
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Classification and recognition method of dangerous behaviors of electric power operators based on improved OpenPose algorithm by Ningtao Liu, Jie Du, Shiliang Chang, Ke Zheng, Ji Xiao, Jiaming Zhang, Shishun Tan

“…Abstract To achieve intelligent identification of dangerous behaviors of electric power workers in complex environment, a classification and identification method based on improved OpenPose algorithm is proposed. The GSP-Darknet network is used to enhance the extraction of key points of small bones, and the missing joint coordinates are filled in by the average values of adjacent frames. …”
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Improved Cluster Intelligent and Complex Optimization Algorithm for Power Equipment CAD-Assisted Intelligent Operation and Maintenance by Yinguan Song, Yu Zou, Yifeng Su, Ming Wang, Zhenjun Xie, Henglong Chen, Zhongqing Sang

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Improved Slime-Mould-Algorithm with Fitness Distance Balance-based Guiding Mechanism for Global Optimization Problems by Enes Cengiz, Mehmet Fatih Işık, Hamdi Kahraman, Cemal Yılmaz, Çağrı Suiçmez

“…In this study, the performance of Slime-Mould-Algorithm (SMA), a current Meta-Heuristic Search algorithm, is improved. …”
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Research on Pedestrian Avoidance Behavior for School Section Based on Improved BP Neural Network and XGboost Algorithm by Guiliang Lu, Mingwei Liu

“…We independently apply three predictive models: the traditional BP (Backpropagation) neural network, an improved GA-BP(genetic algorithm–backpropagation) neural network, and the XGBoost (Extreme Gradient Boosting) ensemble learning method. …”
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Optimization of longitudinal impedance protection for hybrid cascaded HVDC transmission under improved Bhattacharyya distance algorithm by WANG Shuzheng, LI Peilin, YANG Junwei, ZHANG Jinhua, SHI Yuan, LIU Kangli

“…To enhance the robustness of longitudinal protection in LCC-MMC hybrid cascaded HVDC transmission systems, a longitudinal protection scheme of HVDC transmission based on longitudinal impedance and improved Bhattacharyya distance algorithm was proposed. …”
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An Optimization Algorithm for Forward-Scatter Radar Network Node Deployment Based on BFGS and Improved NSGA-II by Yuqing Zheng, Xiaofeng Ai, Zhiming Xu, Jing Wu, Feng Zhao

“…Finally, an improved Non-dominated Sorting Genetic Algorithm II (NSGA-II) was proposed to derive the deployment schemes. …”
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Optimizing Artificial Neural Network Learning Using Improved Reinforcement Learning in Artificial Bee Colony Algorithm by Taninnuch Lamjiak, Booncharoen Sirinaovakul, Siriwan Kornthongnimit, Jumpol Polvichai, Aysha Sohail

“…To overcome this challenge, this study introduces an improved optimization approach, the improvement of reinforcement learning in the artificial bee colony (improved R-ABC) algorithm, to enhance the optimization process for ANNs. …”
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Feature selection using a multi-strategy improved parrot optimization algorithm in software defect prediction by Qi Fei, Guisheng Yin, Zhian Sun

“…Secondly, to mitigate the adverse impact of irrelevant features on model performance in traditional software defect prediction methods, this study introduces a binary multi-strategy enhanced Parrot Optimization algorithm (BMEPO) for optimizing feature selection. …”
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A Novel Dataset and Detection Method for Unmanned Aerial Vehicles Using an Improved YOLOv9 Algorithm by Depeng Gao, Jianlin Tang, Hongqi Li, Bingshu Wang, Jianlin Qiu, Shuxi Chen, Xiangxiang Mei

“…This dataset can be used in model training to help detectors distinguish UAVs from these nontarget objects and thereby improve their anti-interference capabilities. …”
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An Improved Parametric Polar Format Algorithm for Missile-Borne SAR Imaging With a Dive and Curve Trajectory by Zirui Xi, Zhichao Meng, Guanyong Wang, Lei Zhang, Xinshuo Wang, Jingyue Lu

“…Due to the 2-D spatial variability of the range model during the missile-borne synthetic aperture radar (SAR) flight along a dive and curve trajectory, the accuracy of traditional algorithms is limited. …”
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Research on safety evaluation and weather routing optimization of ship based on roll dynamics and improved A* algorithm by Zilong Guo, Mei Hong, Yongchui Zhang, Jian Shi, Longxia Qian, Hanlin Li

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Improved Black-Winged Kite Algorithm with Multi-Strategy Optimization for Identifying <i>Dendrobium huoshanense</i> by Chaochuan Jia, Ting Yang, Maosheng Fu, Yu Liu, Xiancun Zhou, Zhendong Huang, Fang Wang, Wenxia Li

“…An improved black-winged kite algorithm with multiple strategies (BKAIM) is proposed in this paper to address two critical limitations in the original black-winged kite optimization algorithm (BKA): the restricted search capability caused by the low-quality initial population and the reduced population diversity resulting from blind following behavior during the migration phase. …”
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Leather Defect Detection Based on Improved YOLOv8 Model by Zirui Peng, Chen Zhang, Wei Wei

“…Experimental results demonstrate that the improved algorithm achieves an improvement of 1.39% in mAP50 and reduces the number of parameters and GFLOPs by 9.3% and 7.41%, respectively, as compared to the original YOLOv8 model. …”
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An intelligent object detection and classification framework for assisting visually challenged persons using deep learning and improved crow search optimization by Alaa O. Khadidos, Ayman Yafoz

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An Improved 2D Pose Estimation Algorithm for Extracting Phenotypic Parameters of Tomato Plants in Complex Backgrounds by Yawen Cheng, Ni Ren, Anqi Hu, Lingli Zhou, Chao Qi, Shuo Zhang, Qian Wu

“…We enhanced a novel heatmap-free method, YOLOv8s-pose, by integrating the Convolutional Block Attention Module (CBAM) and Content-Aware ReAssembly of FEatures (CARAFE), to develop an improved YOLOv8s-pose (IYOLOv8s-pose) model, which efficiently focuses on salient image features with minimal parameter overhead while achieving a superior recognition performance in complex backgrounds. …”
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Improved MViTv2-T model for insulator defect detection by Fuhong Meng, Guowu Yuan, Hao Zhou, Hao Wu, Yi Ma

“…The new model utilizes the sore penalty mechanism (SPM) cluster non-maximum suppression (NMS) algorithm instead of the batched non-maximum suppression (NMS) algorithm from the original model. …”
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Improved Artificial Bee Colony Optimization Underwater Localization Algorithm by Logistic Chaos Mapping and Differential Evolution by Jiaxing CHEN, Yang LIU, Xiaoqian LIU, Zhihua LIU

“…The artificial bee colony algorithm offers a novel approach to improving the accuracy of underwater node localization. …”
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TBESO-BP: an improved regression model for predicting subclinical mastitis by Kexin Han, Yongqiang Dai, Huan Liu, Junjie Hu, Leilei Liu, Zhihui Wang, Liping Wei

“…The TBESO algorithm notably enhances the efficacy of the BP neural network in regression prediction, ensuring elevated computational efficiency and practicality post-improvement.…”
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Influence maximization algorithm based on social network by Xuan WANG, Yu ZHANG, Junfeng ZHOU, Ziyang CHEN

“…The influence maximization (IM) problem asks for a group of seed users in a social network under a given propagation model, so that the information spread is maximized through these users.Existing algorithms have two main problems.Firstly, these algorithms were difficult to be applied in large-scale social networks due to limited expected influence and high time complexity.Secondly, these algorithms were limited to specific propagation models and could only solve the IM problem under a single type of social network.When they were used in different types of networks, the effect was poor.In this regard, an efficient algorithm (MTIM) based on two classic propagation models and reverse influence sampling (RIS) was proposed.To verify the effectiveness of MTIM, experiments were conducted to compare MTIM with greedy algorithms such as IMM, TIM and PMC, and heuristic algorithms such as OneHop and Degree Discount on four real social networks.The results show that MTIM can return a <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML"> <mrow><mo>(</mo> <mrow> <mn>1</mn><mo>−</mo><mfrac> <mn>1</mn> <mtext>e</mtext> </mfrac> <mo>−</mo><mi>ε</mi></mrow> <mo>)</mo></mrow></math></inline-formula> approximate solution, effectively expand the expected influence and significantly improve the efficiency.…”
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