CASIA OpenIR
(本次检索基于用户作品认领结果)

浏览/检索结果: 共5条,第1-5条 帮助

限定条件            
已选(0)清除 条数/页:   排序方式:
Forecasting horticultural products price using ARIMA model and neural network based on a large-scale data set collected by Web crawler 期刊论文
IEEE Transactions on Computational Social Systems, 2019, 卷号: 6, 期号: 3, 页码: 547-553
作者:  Weng, Yuchen;  Wang, Xiujuan;  Kang, Mengzhen;  Hua, Jing;  Wang, Fei-yue
浏览  |  Adobe PDF(1374Kb)  |  收藏  |  浏览/下载:408/194  |  提交时间:2020/06/08
Web crawler  cucumber  agricultural CPSS framework  ARIMA model  neural network  price forecasting  
A Novel Blockchain Oracle Implementation Scheme Based on Application Specific Knowledge Engines 会议论文
, Zhengzhou, China, Nov. 6-7, 2019
作者:  Wang, Shuai;  Lu, Hao;  Sun, Xingkai;  Yuan, Yong;  Wang, Feiyue
浏览  |  Adobe PDF(1166Kb)  |  收藏  |  浏览/下载:339/112  |  提交时间:2019/11/12
Moving from mass customization to social manufacturing: a footwear industry case study 期刊论文
INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING, 2019, 卷号: 32, 期号: 2, 页码: 194-205
作者:  Shang, Xiuqin;  Shen, Zhen;  Xiong, Gang;  Wang, Fei-Yue;  Liu, Sheng;  Nyberg, Timo R.;  Wu, Huaiyu;  Guo, Chao
浏览  |  Adobe PDF(2349Kb)  |  收藏  |  浏览/下载:504/129  |  提交时间:2019/07/12
Collaborative manufacturing  mass customisation  optimisation SM resources  
Parallel Vehicular Networks: A CPSS-Based Approach via Multimodal Big Data in IoV 期刊论文
IEEE INTERNET OF THINGS JOURNAL, 2019, 卷号: 6, 期号: 1, 页码: 1079-1089
作者:  Han, Shuangshuang;  Wang, Xiao;  Zhang, Jun Jason;  Cao, Dongpu;  Wang, Fei-Yue
浏览  |  Adobe PDF(1880Kb)  |  收藏  |  浏览/下载:437/76  |  提交时间:2019/07/12
Cyber-social-physical system (CPSS)  Internet of Vehicles (IoV)  parallel system  social networks  
Pattern Sensitive Prediction of Traffic Flow Based on Generative Adversarial Framework 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2019, 卷号: 20, 期号: 6, 页码: 2395-2400
作者:  Lin, Yilun;  Dai, Xingyuan;  Li, Li;  Wang, Fei-Yue
浏览  |  Adobe PDF(623Kb)  |  收藏  |  浏览/下载:374/162  |  提交时间:2019/05/07
Traflic flow prediction  deep learning  generative adversarial network