Using fuzzy inference to plan capital repairs and reconstruction of public buildings

Introduction. The article analyzes the determinants that condition the incorporation of public buildings into capital repair and reconstruction plans (CRR plan). These include the technical condition of a facility, specified in an expert opinion and identified on the basis of the survey results, the duration of effective operation, determined in accordance with guideline values, the work performance time, the availability of the engineering and transport infrastructure, and other factors. Materials and methods. The co-authors formulated fuzzy inference rules and compiled a table of expert opinions issued on their basis. To implement the fuzzy inference procedure, the co-authors applied the Mamdani algorithm, the min-conjunction for aggregating indicators, the max-disjunction for accumulating conclusions, and the centre of gravity method to ensure defuzzification. The Editor of Fuzzy Output Systems of the MatLab package is used to implement the proposed fuzzy inference pattern. The Saati hierarchy method is used to design membership functions (FP). The analysis of literature sources did not identify any works in which fuzzy logic methods or fuzzy inference rules were used to plan the CRR of public buildings. Results. Membership functions for all factors and the final indicator on the selected scale, corresponding to the Harrington desirability function in the range of values [0; 100], are designed. The results of the implementation of the proposed fuzzy inference system in the MatLab environment are presented in the form of graphs and numerical values of all input linguistic variables. Conclusions. Fuzzy inference allows to obtain the numerical value of the integral repair potential that underlies an informed decision about the incorporation of a facility into the CRR plan. The strength of the approach is the modifiability and expandability of the rule base in practical work. The proposed planning tool allows to consider a combination of principal factors, cut costs, reduce the time frame and improve the public building repair quality.