There exist many panel data decision problems in real life,and they take on obvious structural similarities and lag effects among decision objects or indicators,which are difficult to solve effectively based on tradit...There exist many panel data decision problems in real life,and they take on obvious structural similarities and lag effects among decision objects or indicators,which are difficult to solve effectively based on traditional panel data analysis methods.To deal with these problems,considering the structural characteristics of panel data and lag effect,from multiple structural dimensions such as scale volume,development trend,and volatility,we exploit grey incidence analysis and panel data to establish an indicator-type grey structural incidence analysis model,and utilize it to analyze and identify factors influencing technological innovation of industrial enterprises.The results show that the proposed method fully considers the structural characteristics of panel data and lag effect,and it can deal with panel data decision problems and provide a new methodological support for the grey incidence analysis.展开更多
Abstract Key distribution patterns （KDPs） are finite incidence structures satisfying a certain property which makes them widely used in minimizing the key storage and ensuring the security of communication between u...Abstract Key distribution patterns （KDPs） are finite incidence structures satisfying a certain property which makes them widely used in minimizing the key storage and ensuring the security of communication between users in a large network. We construct a new KDP using t-design and combine two ω-KDPs to give new （ω- 1）-KDPs, which provide secure communication in a large network and minimize the amount of key storage.展开更多
基金partially funded by the National Natural Science Foundation of China(Nos.71503103 and 72372059)National Social Science Foundation of China(Nos.19FGLB031 and 22AJL002)+7 种基金National Statistical Science Research Program of China(No.2024LZ015)Outstanding Youth in Social Sciences of Jiangsu ProvinceQinglan Project of Jiangsu Province,and Engineering Research Center of Integration and Application of Digital Learning Technology,Ministry of Education(No.1321005)Educational Planning Project of Jiangsu Province(No.ZYJN/2024/01)Postgraduate Research&Practice Innovation Program of Jiangsu Province”(No.SJCX241336)Fundamental Research Funds for the Central Universities(Nos.JUSRP622047 and JUSRP321016)Soft Science Foundation of Wuxi City(No.KX-24-A15)and Jiangsu Province Science and Technology Think Tank Program Youth Project(No.JSKX0125058).
文摘There exist many panel data decision problems in real life,and they take on obvious structural similarities and lag effects among decision objects or indicators,which are difficult to solve effectively based on traditional panel data analysis methods.To deal with these problems,considering the structural characteristics of panel data and lag effect,from multiple structural dimensions such as scale volume,development trend,and volatility,we exploit grey incidence analysis and panel data to establish an indicator-type grey structural incidence analysis model,and utilize it to analyze and identify factors influencing technological innovation of industrial enterprises.The results show that the proposed method fully considers the structural characteristics of panel data and lag effect,and it can deal with panel data decision problems and provide a new methodological support for the grey incidence analysis.
基金Acknowledgements This work was supported in part by the National Natural Science Foundation of China （Grant No. 61179026） and the Fundamental Research Funds for the Central Universities （No. 3122016L005）.
文摘Abstract Key distribution patterns （KDPs） are finite incidence structures satisfying a certain property which makes them widely used in minimizing the key storage and ensuring the security of communication between users in a large network. We construct a new KDP using t-design and combine two ω-KDPs to give new （ω- 1）-KDPs, which provide secure communication in a large network and minimize the amount of key storage.
