ALGORITHMS OF IDENTIFICATION AND ELIMINATION OF MISTAKES IN KNOWLEDGE BASES OF EXPERT DIAGNOSTIC SYSTEMS
Authors:   Voronezh State Technical University, Voronezh, Russia, Barkalov Sergey A. , Belousov Vadim E. ,   Voronezh State Technical University, Voronezh, Russia, Prosolupov Oleg A. ,   Voronezh State Technical University, Voronezh, Russia
Published: February 2025

In this work diagnostic systems which on the functions are intended for the help to the user in permission of the following problem situation are considered: it is required to determine by a set of values of the private signs describing a condition of an object of a research. what properties this object has. Such tasks can arise, for example, in medical diagnostics (on a set of the symptoms describing a condition of the patient, the doctor has to take out the conclusion about the nature of a disease); in technical diagnostics (the reason of failure or breakage is determined by a number of indicators of work of a system); in geology (on the basis of data of geological exploration to draw a conclusion on existence of mineral deposits), etc. Unfortunately, for the solution of similar tasks use of methods of machine learning or deep machine learning therefore the only exit is use of expert mechanisms is not always possible. The research objective consists in forming of the knowledge base for the solution of problems of diagnostics which have to comprise decisive rules of the skilled experts allowing to build classification of all possible conditions of an object in previously structured problem area which classes are subsets of the states having the same property. Research methods. Methods of binary classification, the theory of counts are applied to the solution of problems of forming of the consistent knowledge base. When proofreading in classification of states there is no possibility of unambiguous carrying out necessary changes in classification of earlier identified states as elimination of mistakes cannot be carried out separately for each class. In this case to each state only one class of accessory therefore possible addition of a class of accessory to some states results in need of an exception of the accessory classes which are earlier appointed by it that is reached by use of the directed counts has to be appointed. Results. For holding poll of the specialist investigating the electroencephalogram initially all variety of possible states which are described by values of signs was created. In total, the quantity of similar states is equal to 216. After obtaining the expert opinion it was offered to it to estimate degree of probability of existence of a disease or its symptoms in this state, using terms “strong”, “average” and “weak” degrees of probability. It meant for the doctor that he was faced by a standard task of diagnosis. As a result of use of the rational procedure of poll during which the most informative state was provided it was succeeded to carry out classification of possible states for a short span and to receive answers to all questions. In total about 40 questions were asked. By means of a system, results of classification were reduced in the uniform knowledge base which included numbers of states, classes of accessory (diagnoses) and numbers of degree of probability for each of them. Such representation of knowledge takes place to be in a look because each state can be described by a feature set which have unambiguous compliance to its number. Thus, thanks to such data structure in the knowledge base of a system it is possible to calculate number from the knowledge base on set of symptoms of the patient and to define his diagnosis. Conclusion. To receive exhaustive and not contradictory set of rules which will be based on simple and clear actions from experts it is necessary to apply the offered approach to the solution of a problem of expert classification. In a diagnostic system the gained knowledge easily unites in the knowledge base which saves resources of memory and quickly finds a solution. Undoubtedly, the fact that the acquired classifications can be provided in a form of products, traditional for expert systems. As showed the experience of use of a diagnostic system offered by us a way of data structure, has higher performance in comparison with traditional.