Application Of Fuzzy Mathematics Methods To Processing Geometric Parameters Of Degradation Of Building Structures

The aim of research is formalization of the expert experience, which is used in processing geometric parameters of building structure degradation, using fuzzy mathematics. Materials that are used to specify fuzzy models are contained in expert assessments and scientific and technical reports on the technical condition of buildings. The information contained in the reports and assessments is presented in text form and is accompanied by a large number of photographs and diagrams. Model specification methods, based on the analysis of such information on the technical state of structures with damages and defects of various types, primarily lead to difficulties associated with the presentation of knowledge and require the formalization of expert knowledge and experience in the form of fuzzy rules. Approbation and adaptation of the rules is carried out in the process of further research taking into account the influence of random loads and fields. The scientific novelty of the work is expanding of the knowledge base due to the geometric parameters of structural degradation, on the basis of which a fuzzy conclusion about their technical state in the systems of fuzzy product rules at different stages of the object's life cycle is realized. The results of the work are presented in the form of a formalized description of the geometric parameters of degradation. The knowledge presented in the work is intended for the development of technical documentation that is used at the pre-project stage of building reconstruction, but the gained experience is the source of information on the basis of which a constructive solution is selected in the design process of analogical objects. In addition, the knowledge gained from the analysis of expert assessments of the state of various designs is necessary for development of automated expert evaluation processing systems. The use of such evaluation systems will significantly reduce the risks of the human factor associated with the errors in the specification of models for predicting the processes of structural failure at various stages of ensuring the reliability and safety of buildings

Adaptation of Fuzzy Inference System to Solve Assessment Problems of Technical Condition of Construction Objects

The main task, the solution of which the work is focused on, is the automation of the fuzzy inference system, which is one of the subsystems of the system for assessing the technical condition of construction objects. The proposed assessment system is assigned to services that specialize in conducting construction and technical examinations. The process of conducting examinations in this area is accompanied by uncertainties of a different nature, and the production activities of specialists are often based on heuristics. That is why, the object of research are models and tools that can function in fuzzy conditions. To automate expert activities in the field of assessing the influence of external factors on the technical condition of compacted urban areas, a specialized assessment system has been designed based on knowledge and an artificial neuro-fuzzy network of the Takagi-Sugeno-Kang category. The use of neuro-fuzzy models for fuzzy inference makes it possible to automate the process of obtaining logical conclusions from input according to fuzzy rules specified by experts. At the same time, settings for membership functions can be carried out using artificial neural networks. The Takagi-Sugeno-Kang fuzzy neural network is designed to solve this problem. The feasibility of using this model to solve the problem of assessing the technical condition of construction objects with damage is justified by its ability to solve the problem of fuzzy classification. The second main criterion for choosing this model is the ability to set the rules by the input function, since under the conditions of compacted urban development, the factors affecting the external environment on the technical condition of objects are complex non-linear. The principle of adaptation of the fuzzy inference system is shown by the example of fuzzification of environmental influences caused by vibrations of a different nature. The studies carried out in the work, unlike the previous ones, expand the knowledge base of the system by presenting information about the real state of the environment in which the construction objects operate. It is expected that the use of the Takagi-Sugeno-Kang artificial neural network will significantly reduce the influence of the human factor on the performance of construction and technical examinations performed under conditions of compositional uncertainty. The practical significance of the work is to reduce the timing and increase the reliability of the assessment of the technical condition of construction objects with damage of a different natur