Multi-State System in human reliability analysis
Application of mathematical model of Multi-State System for human reliability analysis is considered in the paper. This paper describes new method for estimation of changes of more than one component states and they influence to Multi-State System reliability by Dynamic Reliability Indices. The Multi-State System failure is considered depending on decrease of some system component efficiency and the Multi-State System repair is declared depending on replacement of some failed components. The mathematical approach of Logical Differential Calculus is used for analysis of the Multi-State System reliability change that is caused by modifications of some system components states.
Fuzzy Classifier Based on Fuzzy Decision Tree
A popular method for making a fuzzy decision tree for classification is Fuzzy ID3 algorithm. We introduce a new approach that uses cumulative information estimations of initial data. Based on these estimations we propose a new greedy version of fuzzy ID3 algorithm to be used to generate understandable fuzzy classification rules. The goal is to find a sequence of rules that causes near minimal classification costs.
Dynamic reliability indices for k-out-of-n multi-state system
A multi-state system k-out-of-n is one of basic models in reliability analysis. In this system, k is the minimum number of n components that must work for the system to work and both the system and its components can have more than two states. A structure function declares relation between system and component states uniquely. New algorithm for reliability analysis of the k-out-of-n multi-state system is proposed in this paper. We use two tools for examine this system: (a) structure function for the system description; (b) direct partial logic derivatives for analysis this system. New algorithm for reliability analysis of the multi-state system k-out-of-n is allowed to calculate the probabi…