Intelligent system for determining the dielectric permeability of the forest environment during radio frequency monitoring

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The global problem of preserving forests from illegal logging, fires, as well as collecting information about the state of the forest fund and forest resources is considered. It is noted that the existing forest monitoring systems do not functionally ensure the implementation of such tasks and, all the more, the whole complex at the same time. To implement the strategic plans for the development of the industry, new, more sophisticated monitoring systems are needed that use the latest advances in information technology. The paper proposes a solution to the problem on the basis of the radio frequency monitoring system of the forest fund of the ground type in the form of a network of radio frequency (RFID) devices. For the design and deployment in the forest of such a network, the value of one of the most important parameters of the forest environment of its complex dielectric permittivity is necessary. It is not possible to do this with traditional statistical ones, therefore the fuzzy modeling method was used and earlier in previous works the main functional dependencies were obtained, which allow to form a generalized intellectual system. Thus, the purpose of these studies was to develop an intelligent system in the form of a neurofibral production network for assessing the complex dielectric permittivity of the forest environment. The methodological basis of the research was the theory of information and signaling, fuzzy modeling. The result of the research is a developed intellectual system for assessing the complex dielectric permittivity of the forest environment and a software implementation of the model in the Simulink environment. Practical application of the results is provided for the design of design parameters and topography in the forest of radio frequency monitoring systems of the forest fund.

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Radio frequency monitoring of the forest fund, complex dielectric permeability of the forest plot, forest parameters, fuzzy conclusion, neuro-fuzzy network, intelligent system

Короткий адрес: https://sciup.org/148314133

IDR: 148314133

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