Application of Fuzzy Logic for Risk Assessment/ Izplūdušās loģikas pielietojums risku analīzē/ Применение нечеткой логики для анализа рисков

Abstract

Risk assessment is an important task in many areas of human activity: economic, technical, ecological etc. Preliminary data adequacy in risk assessments is carried out on the basis of statistical methods and experts' evaluation on potential losses and probabilities of the event. But in many cases, risk assessment must be carried out under the conditions of lack of initial information or uncertainty of information. For that reason, special risk assessment approaches (methods) are necessary. One of them is the usage of fuzzy logic approach. In this paper, fuzzy logic approach is used to manage this uncertainty in information concerning accidental releases of toxic chemicals at chemical plants. This approach can be used by plant risk advisers in Latvia to make right decisions in the situations where chemical releases can harm not only the environment but also human health.

Ensuring Reliability of Control Data in Engineering Systems

“…Inadequacy in systems is mainly due to the incompleteness of the original data, the nebulosity (fuzziness) of the information and the limitations of the class of implemented algorithms [3], [4], [10], [11].…”

“…The minimum amount of the required information to solve a specific task with the specified degree of reliability (global radius of information) can be defined as follows. If we accept that (7) and note 8as a local radius of information, i.e., the least ξ, for which there still exists an element belonging to sets for all that do not differ from f using information N, then the global radius of information may be defined as (9) Then for the exact solution of the problem, i.e., for the case of an unambiguous definition (10) when S[V(N,f)] is unique (one and only one), (11) Thus, the search for an exact solution to a problem reduces to the definition of the minimum amount of information, the presence of which r(N) is converted to zero. However, since the procedures for such a search are often limited to system resources, or too high for additional information, the decision is sought with an error (12) where -the local error in the algorithm (procedures) φ from the class of algorithms (procedures) φ(N) that use the information N, i.e., the least ξ, in which the element φ[N (f)] belongs to for all that cannot be distinguished from f by using information N.…”