A Novel Multiobjective Evolutionary Algorithm Based on Regression Analysis by Zhiming Song, Maocai Wang, Guangming Dai, Massimiliano Vasile

“…However, how to utilize the regularity to design multiobjective optimization algorithms has become the research focus. In this paper, based on this regularity, a model-based multiobjective evolutionary algorithm with regression analysis (MMEA-RA) is put forward to solve continuous multiobjective optimization problems with variable linkages. …”
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Economic Structure Analysis Based on Neural Network and Bionic Algorithm by Yanjun Dai, Lin Su

“…In the shallow neuroevolutionary, the improved genetic algorithm (IGA) based on elite heuristic operation and migration strategy and the improved coyote optimization algorithm (ICOA) based on adaptive influence weights are proposed, and the shallow neuroevolutionary method based on IGA and the shallow neuroevolutionary method based on ICOA are applied to the weight space of backpropagation (BP) neural networks. …”
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Visual Multiple-object Tracking Algorithm Based on Motion Consistency by YANG Hailang, LYU Yu, JIANG Guotao, PI Zhichao, LUO Shuo, CHEN Meilin

“…The proposed algorithm reflects an optimized cascade matching strategy, primarily depending on the motion consistency characteristic index developed in this study based on the target motion vector, and incorporating some common cues in object tracking research, such as the appearance model and Mahalanobis distance. …”
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Smoothing Algorithm of Point Cloud Based on Normal Vector Correction by XUE Ping, YAO Juan, ZOU Xue-zhou, WANG Hong-min

“…The presence of outliers and noise points in the cloud data of the reverse engineering data collection directly affects the mult-view’s combination of the data，feature extraction，data reduction and the quality of surface reconstruction. Based on the research of bilateral filtering and trilateration filtering algorithm，this paper presents an algorithm of denoising and smoothing of point cloud data based on normal vector correction. …”
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Error-Index-Based Algorithm for Low-Velocity Impact Localization by Tao Peng, Lilin Cui, Xiufeng Huang, Wenjing Yu, Rongwu Xu

“…To locate the low-velocity impact points in these structures, this study proposes an error-index-based algorithm for impact localization. The time of arrival of an impact-generated A0 Lamb waves was first estimated based on the energy of the signal. …”
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Quality Prediction of Web Services Based on a Covering Algorithm by Ying Jin, Guangming Cui, Yiwen Zhang

“…Thus, developing effective and efficient approaches for predicting the quality values of Web services has become an important research issue. In this paper, we propose UIQPCA, a novel approach for hybrid User and Item-based Quality Prediction with Covering Algorithm. …”
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Architectural animation generation system based on AL-GAN algorithm by Wei Ming, Sun Mingjing

“…To this end, a new AA generation system based on the architecture learning generative adversarial network (AL-GAN) algorithm is proposed, aiming to solve the problems of insufficient detail handling, poor animation continuity, and inefficiency in traditional AA generation. …”
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Beijing Opera Synthesis Based on Straight Algorithm and Deep Learning by XueTing Wang, Cong Jin, Wei Zhao

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Improved SOM algorithm for damage characterization based on visual sensing by Hongtao Zhu, Shuyun Guo

“…To enhance the accuracy and efficiency of concrete damage identification, this research proposes an improved Self-Organizing Map algorithm based on visual sensing. …”
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Inversion of Bubble Size Distribution Based on Whale Optimization Algorithm by Zhenzhong Lu, Ziqi Hu, Lin Ma, Shangtao Huang, Tao Peng, Min Liu, Biao Han, Jiali Liao, Zihao Wang, Yanling Sun

“…A particle size inversion method based on whale optimization algorithm (WOA) is presented. …”
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Abnormal link detection algorithm based on semi-local structure by Haoran SHI, Lixin JI, Shuxin LIU, Gengrun WANG

“…With the research in network science, real networks involved are becoming more and more extensive.Redundant error relationships in complex systems, or behaviors that occur deliberately for unusual purposes, such as wrong clicks on webpages, telecommunication network spying calls, have a significant impact on the analysis work based on network structure.As an important branch of graph anomaly detection, anomalous edge recognition in complex networks aims to identify abnormal edges in network structures caused by human fabrication or data collection errors.Existing methods mainly start from the perspective of structural similarity, and use the connected structure between nodes to evaluate the abnormal degree of edge connection, which easily leads to the decomposition of the network structure, and the detection accuracy is greatly affected by the network type.In response to this problem, a CNSCL algorithm was proposed, which calculated the node importance at the semi-local structure scale, analyzed different types of local structures, and quantified the contribution of edges to the overall network connectivity according to the semi-local centrality in different structures, and quantified the reliability of the edge connection by combining with the difference of node structure similarity.Since the connected edges need to be removed in the calculation process to measure the impact on the overall connectivity of the network, there was a problem that the importance of nodes needed to be repeatedly calculated.Therefore, in the calculation process, the proposed algorithm also designs a dynamic update method to reduce the computational complexity of the algorithm, so that it could be applied to large-scale networks.Compared with the existing methods on 7 real networks with different structural tightness, the experimental results show that the method has higher detection accuracy than the benchmark method under the AUC measure, and under the condition of network sparse or missing, It can still maintain a relatively stable recognition accuracy.…”
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Tennis Assistance Technology Based on Dynamic Time Warping Algorithm by Penggang Wang, Pengpeng Zhang, Guanxi Fan

“…Traditional teaching methods are inefficient and difficult to quantify the correctness of actions. In view of this research, a tennis sports assistance technology based on dynamic time warping algorithm is developed. …”
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ICBoost: An XGBoost-Based Unbiased Transformed Algorithm for Survival Regression by Jingyi Zhang, Shishun Zhao, Yang Xu, Tao Hu

“…We evaluated the performance of the ICBoost algorithm against existing methods using various real and simulated datasets. …”
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Lightweight insulator target detection algorithm based on improved YOLOX by Bing Zeng, Wei Hua, Dezhi Li, Zhihao Zhou, Hao Wan, Yunmin Xie, Tangbing Li, Yucong Chen, Jianglei Li, Shenli Wang, Shixun Fu, Zihan Jin, Wenhua Zhang

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Fitness exercise evaluation system based on improved DTW algorithm by Tinghang Guo, Qianhan Yin, Xinlin Liu, Yue Sun, Zhuanping Qin, Yu Han, Guangda Lu

“…To address these issues, a real-time fitness action recognition and evaluation system is developed based on the lightweight BlazePose model. The system integrates the K Nearest Neighbor (KNN) algorithm for action recognition and classification. …”
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Design and experiment of landslide monitoring algorithm based on MEMS sensor by Di WU, Taiming LIANG, Jing WU, Jianjian WU, Yang YI, Wanpeng LOU

“…MEMS technology was used to monitor the internal displacement of the soil for the test slopes, and the results were compared with the the finite element simulation outputs to evaluate the accuracy and reliability of the algorithm. Results The findings indicate that the MEMS-based soil landslide displacement monitoring achieved a minimum average relative error of 0.09% in the horizontal direction and 0.50% in the vertical direction, demonstrating high accuracy and suitability for practical engineering applications. …”
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Laryngeal cancer diagnosis based on improved YOLOv8 algorithm by Xin Nie, Xueyan Zhang, Di Wang, Yuankun Liu, Lumin Xing, Wenjian Liu

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Review of plant disease image recognition algorithms based on deep learning by Yang Hankun, Zhu Bowei, Zhang Yanmin, Xu Yidong

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Uncertain data analysis algorithm based on fast Gaussian transform by Rong-hua CHI, Yuan CHENG, Su-xia ZHU, Shao-bin HUANG, De-yun CHEN

“…The effect of the uncertainties needs to be taken full advantage during uncertain data clustering.An uncertain data clustering algorithm based on fast Gaussian transform was proposed,to solve the problems about the impact on the accuracy of clustering results and the clustering efficiency caused by the uncertainties,during the construction of uncertain data models and the distance measurement,which existed in the current researches.First,the data model according to the characteristic of the uncertainty distribution was constructed,without the premise of assuming the data distribution.And the similarity between uncertain data objects was measured by combining the two important features of uncertain objects,attribute features and the probability density function representing the characteristic of uncertainty distribution.And then the uncertain data clustering algorithm was proposed.Finally,the experiment results on UCI and real datasets indicate the better efficiency and accuracy of proposed algorithm.…”
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Uncertain data analysis algorithm based on fast Gaussian transform by Rong-hua CHI, Yuan CHENG, Su-xia ZHU, Shao-bin HUANG, De-yun CHEN

“…The effect of the uncertainties needs to be taken full advantage during uncertain data clustering.An uncertain data clustering algorithm based on fast Gaussian transform was proposed,to solve the problems about the impact on the accuracy of clustering results and the clustering efficiency caused by the uncertainties,during the construction of uncertain data models and the distance measurement,which existed in the current researches.First,the data model according to the characteristic of the uncertainty distribution was constructed,without the premise of assuming the data distribution.And the similarity between uncertain data objects was measured by combining the two important features of uncertain objects,attribute features and the probability density function representing the characteristic of uncertainty distribution.And then the uncertain data clustering algorithm was proposed.Finally,the experiment results on UCI and real datasets indicate the better efficiency and accuracy of proposed algorithm.…”
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