Regulation of technology has been a hot issue in the financial field in recent years.Traditional financial regulation is constructed by a centralized account system,which relies on ex-ante regulation.Embedded supervis...Regulation of technology has been a hot issue in the financial field in recent years.Traditional financial regulation is constructed by a centralized account system,which relies on ex-ante regulation.Embedded supervision,which relies on regulation during and after the matter,operates in a decentralized and trusted environment and has the characteristics of high efficiency,transparency,and safety.It provides a breakthrough to solve the lag of traditional financial supervision.This paper clarifies the concepts and theoretical basis of embedded supervision,constructs the embedded supervision model with a lag,and analyzes the feasibility of embedded supervision with a lag.This research can promote scientific exploration and method innovations in the domestic finance field,enrich China’s financial discipline system,and provide decision-making references for practical financial supervision innovation.展开更多
Locally linear embedding(LLE)algorithm has a distinct deficiency in practical application.It requires users to select the neighborhood parameter,k,which denotes the number of nearest neighbors.A new adaptive method is...Locally linear embedding(LLE)algorithm has a distinct deficiency in practical application.It requires users to select the neighborhood parameter,k,which denotes the number of nearest neighbors.A new adaptive method is presented based on supervised LLE in this article.A similarity measure is formed by utilizing the Fisher projection distance,and then it is used as a threshold to select k.Different samples will produce different k adaptively according to the density of the data distribution.The method is applied to classify plant leaves.The experimental results show that the average classification rate of this new method is up to 92.4%,which is much better than the results from the traditional LLE and supervised LLE.展开更多
文摘Regulation of technology has been a hot issue in the financial field in recent years.Traditional financial regulation is constructed by a centralized account system,which relies on ex-ante regulation.Embedded supervision,which relies on regulation during and after the matter,operates in a decentralized and trusted environment and has the characteristics of high efficiency,transparency,and safety.It provides a breakthrough to solve the lag of traditional financial supervision.This paper clarifies the concepts and theoretical basis of embedded supervision,constructs the embedded supervision model with a lag,and analyzes the feasibility of embedded supervision with a lag.This research can promote scientific exploration and method innovations in the domestic finance field,enrich China’s financial discipline system,and provide decision-making references for practical financial supervision innovation.
基金This study was financially supported by the National Natural Science Foundation of China(61172127)the Research Fund for the Doctoral Program of Higher Education(KJQN1114)+2 种基金Anhui Provincial Natural Science Foundation(1308085QC58)the 211 Project Youth Scientific Research Fund of Anhui UniversityProvincial Natural Science Foundation of Anhui Universities(KJ2013A026)。
文摘Locally linear embedding(LLE)algorithm has a distinct deficiency in practical application.It requires users to select the neighborhood parameter,k,which denotes the number of nearest neighbors.A new adaptive method is presented based on supervised LLE in this article.A similarity measure is formed by utilizing the Fisher projection distance,and then it is used as a threshold to select k.Different samples will produce different k adaptively according to the density of the data distribution.The method is applied to classify plant leaves.The experimental results show that the average classification rate of this new method is up to 92.4%,which is much better than the results from the traditional LLE and supervised LLE.
