Non-Logarithmic Probabilistic Rates of the Object Condition's Uncertainty and the Diagnostic Symptoms’ Informativity

The Combinatorial Diagnostic Entropy and Symptoms' Informativity

“…Conditions might be one-fault or multi-fault ones. into A is crisp, fuzzy, or rough one [2], [18], [35], [36]. If the system is in the condition i e , a value of the symptom r d is denoted in the following manner:…”

“…Most models use binary (good -no-good) conditions and binary (normal -abnormal) symptoms [3], [8], [17]. Better results can be obtained using the qualitative, approximate, and multi-valued models [2], [4], [15], [18], [19]. In [2], it is proved that the length of diagnosis algorithm in the case of multi-valued system conditions and multi-valued symptoms is not larger than the binary algorithm.…”

“…One of the methods of constructing a diagnosis algorithm consists in applying the informationbased analysis [2], [3], [8], [16], [18], [20] - [24], that is, description of the system condition uncertainty and the amount of information delivered by means of individual symptoms and sets thereof.…”

Fault Identifiability Problem – The Multi-Valued Diagnostic Model Approach

“…In this paper information theoretical approach is used to provide a set of diagnostic symptoms necessary for distinguishing faults. It exploits the uncertainty measures of the system condition and amount of information delivered by means of individual symptoms and sets thereof [4,7,8,9].…”