Neuronal Parameter-Measure Model Databases

2015 ◽  
pp. 2063-2063
Keyword(s):  
Measure Model ◽  
Neuronal Parameter

A Theory Model of the Existence Stable Measure for the Industrial Technology Innovation Strategy Alliance

2013 ◽  
Vol 401-403 ◽  
pp. 2193-2198
Author(s):  
Zhan Zhang ◽  
Bo Qin ◽  
Wei Dong Hu
Keyword(s):  
Risk Sharing ◽  
Technology Innovation ◽  
Theory Model ◽  
Innovation Strategy ◽  
Industrial Technology ◽  
Entropy Weight ◽  
Stable Measure ◽  
Measure Model ◽  
Entropy Weight Method ◽  
Questionnaire Method

This paper aims to establish a existence stable measure model. Use Alliance building, partner selection, the benefit and risk sharing, legal guarantee and policy guidance for one class index. Looking for data sources by Delphi method and questionnaire method and using the entropy weight method to Process those data. Through the model application can sum up the developing experience and provide reference for the Industrial technology innovation strategy alliances future development

scholarly journals Synergic Relationship and Synergic Degree between an Information System and Corporate Strategy

2013 ◽  
Vol 13 (Special-Issue) ◽  
pp. 110-121
Author(s):  
Xie Xiang ◽  
Guan Zhongliang ◽  
Wang Xiaoliang ◽  
Liu Jiashi
Keyword(s):  
Information Technology ◽  
Information System ◽  
Core Competence ◽  
Corporate Strategy ◽  
Key Factors ◽  
Measure Model ◽  
Matching Degree ◽  
Is Value

Abstract With the development of information technology, the Information System (IS) has not the characters of rareness and inimitability, so an IS cannot form core competence alone. Forming synergic relationship and keeping higher synergic degree between IS and corporate strategy will help the enterprises acquire competence advantage and realize IS value. This paper analyzes the conditions of forming synergic relationship between an IS and strategy, and points out that the key factors for a synergic degree are the strategy rationality and the matching degree between the IS and strategy. Based on the analysis result and BCG growth share matrix, this paper constructed a synergy degree measure model to evaluate the synergic relationship between the IS and corporate strategy. Finally, a case study is used to verify the feasibility of the model.

scholarly journals ∗-fuzzy measure model for COVID-19 disease

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Abbas Ghaffari ◽  
Reza Saadati
Keyword(s):  
Mathematical Model ◽  
Fuzzy Measure ◽  
Measure Model ◽  
Nikodym Theorem

AbstractWe introduce a mathematical model, namely, ∗-fuzzy measure model for COVID-19 disease and consider some properties of ∗-fuzzy measure such as Lebesque–Radon–Nikodym theorem.

scholarly journals A two measure model of dark energy and dark matter

2012 ◽  
Vol 2012 (11) ◽  
pp. 044-044 ◽  
Author(s):  
Eduardo Guendelman ◽  
Douglas Singleton ◽  
N Yongram
Keyword(s):  
Dark Matter ◽  
Dark Energy ◽  
Measure Model

scholarly journals A novel interestingness measure based on fusion model for association rules mining

2021 ◽  
Vol 336 ◽  
pp. 05009
Author(s):  
Junrui Yang ◽  
Lin Xu
Keyword(s):  
Association Rules ◽  
Negative Association ◽  
Fusion Model ◽  
Interestingness Measures ◽  
Association Rules Mining ◽  
Interestingness Measure ◽  
Advantages And Disadvantages ◽  
Measure Model ◽  
Negative Association Rules ◽  
The Difference

Aiming at the shortcomings of the traditional "support-confidence" association rules mining framework and the problems of mining negative association rules, the concept of interestingness measure is introduced. Analyzed the advantages and disadvantages of some commonly used interestingness measures at present, and combined the cosine measure on the basis of the interestingness measure model based on the difference idea, and proposed a new interestingness measure model. The interestingness measure can effectively express the relationship between the antecedent and the subsequent part of the rule. According to this model, an association rules mining algorithm based on the interestingness measure fusion model is proposed to improve the accuracy of mining. Experiments show that the algorithm has better performance and can effectively help mining positive and negative association rules.

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