Conference on Computer Graphics, Artificial Intelligence, and Data Processing最新文献_第9页

A path planning method for unmanned surface vehicles based on Riemannian geometry 基于黎曼几何的无人水面车辆路径规划方法

Conference on Computer Graphics, Artificial Intelligence, and Data Processing Pub Date : 2023-05-23 DOI: 10.1117/12.2674514

Jiping Yan, Baoan Li, Zilong Lu

引用次数: 0

Multi-objective parameter optimization of distributed hydrological models based on data-poor watersheds 基于数据贫乏流域的分布式水文模型多目标参数优化

Conference on Computer Graphics, Artificial Intelligence, and Data Processing Pub Date : 2023-05-23 DOI: 10.1117/12.2674764

Ke Xu, Kun Yang

{"title":"Multi-objective parameter optimization of distributed hydrological models based on data-poor watersheds","authors":"Ke Xu, Kun Yang","doi":"10.1117/12.2674764","DOIUrl":"https://doi.org/10.1117/12.2674764","url":null,"abstract":"The distributed hydrological model's high-resolution representation of watershed heterogeneity is especially suitable for hydrological simulation in watersheds with small areas, and the hydrological model needs to use flow observation data for parameter calibration to obtain adapted parameters, but the lack of observation basins is the core problem we face in China, where there are few hydrological stations and they are concentrated in important rivers. This work attempts to optimize the parameters of the distributed hydrological model using limited flow observation data in a small watershed where flow observation is relatively scarce and to explore the value of combining multiple sources of data to optimize the parameters of the distributed hydrological model. Based on the combination of meteorological observations and remote sensing data collected, a distributed hydrological model is constructed based on the WetSpa model for the Jianshan River basin, and a multi-objective genetic algorithm NSGA-II is applied to rate the model to predict the simulated basin runoff process. The results show that the hydrological model optimized by multi-objective parameters has good adaptability in the study area, and the simulation has certain accuracy, which can provide basic support for the simulation of the water environment in the basin and also provide a reference for hydrological simulation.","PeriodicalId":286364,"journal":{"name":"Conference on Computer Graphics, Artificial Intelligence, and Data Processing","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116668382","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}

引用次数: 0

Finite element analysis of the Golden Gate Bridge 金门大桥有限元分析

Conference on Computer Graphics, Artificial Intelligence, and Data Processing Pub Date : 2023-05-23 DOI: 10.1117/12.2674963

Zixuan Wang, Runchen Zhu, Junyi Gao, Junran Jiang

引用次数: 0

Video detection method of pointer instrument based on improved FCOS 基于改进FCOS的指针式仪表视频检测方法

Conference on Computer Graphics, Artificial Intelligence, and Data Processing Pub Date : 2023-05-23 DOI: 10.1117/12.2674694

X. Chen, Pengfei Zhang, Wei Xu, Yongjuan Chang, Mingshuo Liu, Zhenyuan Zhao

引用次数: 0

Jadeite origin recognition based on ensemble learning 基于集成学习的翡翠产地识别

Conference on Computer Graphics, Artificial Intelligence, and Data Processing Pub Date : 2023-05-23 DOI: 10.1117/12.2674543

Lingling Wang, Jiahai Tu, Yuan Li, Mingyi Li

{"title":"Jadeite origin recognition based on ensemble learning","authors":"Lingling Wang, Jiahai Tu, Yuan Li, Mingyi Li","doi":"10.1117/12.2674543","DOIUrl":"https://doi.org/10.1117/12.2674543","url":null,"abstract":"Most of the jade on the market now comes from Myanmar, Guatemala, and a few from Russia. The gemological properties of jadeite from different producing areas are consistent. However, in the middle-end jade market, under the same quality, the prices of Guatemalan jade and Russian jade are generally lower than those of Myanmar jade, so some illegal merchants will use Guatemalan jade to impersonate Myanmar jade. Due to the continuous improvement of jade counterfeiting technology, traditional identification methods can no longer meet the demand. In order to protect the rights and interests of consumers need to establish a rapid and effective jade origin traceability method. In this paper, through the (LA-ICP-MS) trace element dataset and the method based on weighted extreme learning machine, AdaBoost and incremental learning fusion, the jadeite discrimination model of different producing areas is established to realize the intelligent discrimination of jadeite producing areas. The recognition accuracy of integrated learning algorithm is more than 80%. Compared with the basic extreme learning machine and weighted extreme learning machine, it can be found that the classification accuracy of integrated learning algorithm is higher and more stable.","PeriodicalId":286364,"journal":{"name":"Conference on Computer Graphics, Artificial Intelligence, and Data Processing","volume":"1996 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125570233","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}

引用次数: 0

Research on employment quality of Wuhan Business University based on AHP and BP neural network 基于AHP和BP神经网络的武汉工商大学就业质量研究

Conference on Computer Graphics, Artificial Intelligence, and Data Processing Pub Date : 2023-05-23 DOI: 10.1117/12.2674659

Quan-feng Wang

引用次数: 0

Prediction method of electronic contract performance risk based on decision tree model 基于决策树模型的电子合同履约风险预测方法

Conference on Computer Graphics, Artificial Intelligence, and Data Processing Pub Date : 2023-05-23 DOI: 10.1117/12.2674621

Hui Xiang, Yanhe Lu, Jing Zhang, Hongyu Wang, Junying Wu

{"title":"Prediction method of electronic contract performance risk based on decision tree model","authors":"Hui Xiang, Yanhe Lu, Jing Zhang, Hongyu Wang, Junying Wu","doi":"10.1117/12.2674621","DOIUrl":"https://doi.org/10.1117/12.2674621","url":null,"abstract":"In the internet environment, an electronic contract is a necessary transaction condition for business cooperation between enterprises. To avoid the risk factors in enterprise electronic contracts and promote the smooth progress of business cooperation, this paper researches the prediction method of enterprise electronic contract performance risk based on the decision tree model. On the basis of the decision tree model, the key nodes are pruned, and then the validity parameters are combined to complete the collection and analysis of enterprise electronic contract risk data. According to the distribution characteristics of risk factors, the performance reliability conditions are improved. The prediction of electronic contract performance risk is realized by solving the value range of prediction parameters. The experimental results indicate that under the decision tree model, the maximum accuracy of risk vector extraction in the process of electronic contract performance reaches 97.5%, which has outstanding application value in avoiding risk factors and promoting business cooperation between enterprises.","PeriodicalId":286364,"journal":{"name":"Conference on Computer Graphics, Artificial Intelligence, and Data Processing","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121043787","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}

引用次数: 0

A SlowFast behavior recognition algorithm incorporating motion saliency 结合运动显著性的慢速行为识别算法

Conference on Computer Graphics, Artificial Intelligence, and Data Processing Pub Date : 2023-05-23 DOI: 10.1117/12.2674969

Xin Zhang, Yantao Zhu, Li-Juan Deng, Long Qi, Zhang Tao, Jiali Hu

引用次数: 0

Research on evaluation of equipment support capability of land aviation brigade based on FAHP 基于FAHP的陆航旅装备保障能力评价研究

Conference on Computer Graphics, Artificial Intelligence, and Data Processing Pub Date : 2023-05-23 DOI: 10.1117/12.2674713

Huining Gu, Yaolong Zhang, Hong-li Jia, Xianmin Shi

引用次数: 0

Overcome STSF phenomenon in catastrophic forgetting 克服灾难性遗忘中的STSF现象

Conference on Computer Graphics, Artificial Intelligence, and Data Processing Pub Date : 2023-05-23 DOI: 10.1117/12.2674765

Yifan Chang, Qifan Zhao

引用次数: 0