DEPENDENCE OF DIELECTRIC PERMITTIVITY OF FOREST FUND BY CLIMATIC FACTORS IN RADIO FREQUENCY MONITORING

Abstract

Relevance. It is planned to elaborate new systems for forest monitoring to fulfill the priority tasks determined by the Government of the Russian Federation. In this connection, the most effective terrestrial radio frequency monitoring system was proposed in the paper. For the design of the system, the values of the most important parameter- complex dielectric permittivity of forest environment (CDPFE) -  are needed. Determining of this value with a wide range of climatic conditions is an extremely difficult task to fulfill. Traditional methods are inefficient in this case. Consequently, lack of a method to assess the necessary parameter of forest environment did not make it possible to design a new monitoring system and to solve the priority task. This situation predetermined the purpose of the research, which consisted in developing of a method for obtaining the functional dependence of the CDPFE on climatic factors. Tasks. To achieve the goal, the following tasks were solved: 1) grounding of the fuzzy functions implements; 2) elaboration of the rule data base of  fuzzy products; 3) choice of the method of fuzzy inference; 4) implementation of fuzzy inference and reduction to clarity with obtaining the resulting functional dependence. Methodology. The methods of  fuzzy modeling was used, the choice of the methods is justified by the specifics of the initial data on climatic factors - temperature and humidity of environment. They are characterized by uncertainty, inadequacy, inaccuracy and other indicators that take into account different types of fuzziness.  Mathematically, such  problem can be formalized on the basis of the apparatus of fuzzy modeling only. Decision. A meaningful statement of the problem involved the formalization of heuristic rules that model the CDPFE, depending on the combination of the influencing parameters. To bring the task to fuzziness, the corresponding linguistic variables are substantiated. For a fuzzy conclusion, the Mamdani method is chosen, and the reduction to clarity is carried out using the center of gravity method. Synthesis of the fuzzy model is carried out by means of MatLab. Discussion. The resulting function is mathematically correct, and the comparison of the calculated data with the known experimental data shows  sufficient adequacy to the real conditions. Conclusion. The proposed function of CDPFE can be recommended for the design of radio frequency systems for forest monitoring.