This paper mainly researched the basic principle of support vector machine based on Gaussian kernel function. Aiming at the defects of existing Gaussian kernel function of support vector machine, particle swarm optimization algorithm was used to optimize the penalty factor and Gaussian radial parameters to improve the generalization prediction ability of the support vector machine. Moreover, based on the support vector machine and particle swarm optimization, the rice canopy density prediction model and correlation analysis experiment were established using the rice canopy image data. The experiment shows that the absolute error and relative error of the rice canopy density prediction model based on support vector machine and particle swarm optimization can meet the requirements of real-time control of the feed amount of the combined harvest under normal and back light conditions.
{"title":"The rice canopy density prediction model research based on SVM","authors":"Chen Keyin, Xie Jinzhen","doi":"10.1117/12.2686049","DOIUrl":"https://doi.org/10.1117/12.2686049","url":null,"abstract":"This paper mainly researched the basic principle of support vector machine based on Gaussian kernel function. Aiming at the defects of existing Gaussian kernel function of support vector machine, particle swarm optimization algorithm was used to optimize the penalty factor and Gaussian radial parameters to improve the generalization prediction ability of the support vector machine. Moreover, based on the support vector machine and particle swarm optimization, the rice canopy density prediction model and correlation analysis experiment were established using the rice canopy image data. The experiment shows that the absolute error and relative error of the rice canopy density prediction model based on support vector machine and particle swarm optimization can meet the requirements of real-time control of the feed amount of the combined harvest under normal and back light conditions.","PeriodicalId":324795,"journal":{"name":"3rd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2023)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116766554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Underground buried cables can improve the efficiency of power transmission and utilizing in the urban underground space. The current load capacity is an important parameter in cable design and operation. When the cables are concentrated in the concrete ducts, the mutual heating increases the temperature of the central cable. concrete pipe laying cable is a commonly used method for high voltage cable because of its high reliability, easy maintenance and convenient replacement. In given concrete duct cross sections and corresponding cable arrangements, the finite element method was used to analyze the temperature field distribution of concrete ducts section with different cable arrangements. The influence of buried depth of concrete duct and thermal conductivity of soil on cable current carrying capacity were discussed. Based on the temperature distribution of concrete pipe, the 'thermal-mechanical' coupling model of cable pipe was established by finite element method, and the distribution characteristics of temperature stress and strain were obtained. The research can provide scientific advice for the conduit’s arrangement and structural form optimization of concrete cable ducts.
{"title":"Numerical simulation of 'thermal-mechanical' coupling of underground cable ducts","authors":"Zhang Zheng, Wang Yejiao","doi":"10.1117/12.2686034","DOIUrl":"https://doi.org/10.1117/12.2686034","url":null,"abstract":"Underground buried cables can improve the efficiency of power transmission and utilizing in the urban underground space. The current load capacity is an important parameter in cable design and operation. When the cables are concentrated in the concrete ducts, the mutual heating increases the temperature of the central cable. concrete pipe laying cable is a commonly used method for high voltage cable because of its high reliability, easy maintenance and convenient replacement. In given concrete duct cross sections and corresponding cable arrangements, the finite element method was used to analyze the temperature field distribution of concrete ducts section with different cable arrangements. The influence of buried depth of concrete duct and thermal conductivity of soil on cable current carrying capacity were discussed. Based on the temperature distribution of concrete pipe, the 'thermal-mechanical' coupling model of cable pipe was established by finite element method, and the distribution characteristics of temperature stress and strain were obtained. The research can provide scientific advice for the conduit’s arrangement and structural form optimization of concrete cable ducts.","PeriodicalId":324795,"journal":{"name":"3rd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2023)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114365983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Camera surveillance plays an important role in maintaining the stability and safety of the social and public environment, and there are further requirements for the role of camera surveillance in building a smart city. This paper proposes a convolutional neural network based on the combination of the convolution module and the Transformer module. The network is applied to the tracking of pedestrian targets in infrared surveillance cameras to fill the shortcomings of surveillance cameras in the night environment. In this paper, the local features of the convolution module and the global features of the Transformer are combined into a comprehensive feature map. The feature information is used to solve the problem of less target feature information in infrared images, and the advantages of codec network structure design are used to ensure effective target features. At the same time, considering the embedding and portability of the network model, this paper adopts the method of grouping shared convolution kernels and Transformer nested segmentation in the design of the convolution module and the Transformer module, so as to achieve the purpose of light weight. After several sets of control experiments, the network designed in this paper has a certain improvement in tracking speed and tracking performance, and effectively solves the problem that infrared weak and small targets are not easy to track.
{"title":"Infrared pedestrian tracking network based on convolution model and transformer model fusion","authors":"Zhang Guiqiang, Wang X. Yi, She X. Xing","doi":"10.1117/12.2686716","DOIUrl":"https://doi.org/10.1117/12.2686716","url":null,"abstract":"Camera surveillance plays an important role in maintaining the stability and safety of the social and public environment, and there are further requirements for the role of camera surveillance in building a smart city. This paper proposes a convolutional neural network based on the combination of the convolution module and the Transformer module. The network is applied to the tracking of pedestrian targets in infrared surveillance cameras to fill the shortcomings of surveillance cameras in the night environment. In this paper, the local features of the convolution module and the global features of the Transformer are combined into a comprehensive feature map. The feature information is used to solve the problem of less target feature information in infrared images, and the advantages of codec network structure design are used to ensure effective target features. At the same time, considering the embedding and portability of the network model, this paper adopts the method of grouping shared convolution kernels and Transformer nested segmentation in the design of the convolution module and the Transformer module, so as to achieve the purpose of light weight. After several sets of control experiments, the network designed in this paper has a certain improvement in tracking speed and tracking performance, and effectively solves the problem that infrared weak and small targets are not easy to track.","PeriodicalId":324795,"journal":{"name":"3rd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2023)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116767882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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