KEYWORDS: Monte Carlo methods, Mathematical optimization, Statistical methods, Information theory, Correlation coefficients, Statistical analysis, Information science, Silicon, Nonlinear dynamics, Matrices
The measurement and extraction of relevant information among variables belongs to the research scope of information theory. In the index evaluation system, there is a common correlation among index variables. The weighted summation method is generally used for the evaluation of indexes, and the relevant information among indexes will be repeatedly calculated, resulting in a large evaluation result. Therefore, this paper proposes a calculation optimization method for measuring and extracting relevant information between index variables. By studying the index correlation types, this paper defines the staple existence forms of relevant information, uses the more applicable global sensitivity algorithm to estimate the amount of relevant information, combing with the weight method to extract and reduce the amount of relevant information from relatively unimportant indexes, to realize the correction of index evaluation results. Based on the university journals cited statistics to verify the method mentioned in this paper, the results show that this method can effectively correct the index evaluation results.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.