Water resource bearing capacity evaluation method

Abstract

The invention discloses a water resource bearing capacity evaluation method. The method comprises the following six steps of: firstly, determining an evaluation index weight by utilizing an information entropy principle; secondly, constructing a set pair model of an evaluation region and water resource bearing capacity evolution, introducing a concept of contact numbers, and contacting the identical discrepancy contrary of the set pair model; thirdly, based on an evaluation index system, calculating the contact numbers of each layer respectively from the bottom to the top, obtaining the contact number of the last layer in turn by combining a weight vector, and analogizing one by one by obtain the contact numbers of the overall system; fourthly, determining the values of the contact numbers of the systems at each level and a principal value of an n-component contact number by utilizing an equipartition principle; fifthly, equally dividing an interval [-1,1] into n levels by utilizing the equipartition principle according to the concept of the contact numbers to obtain n level intervals; and finally, comparing the values of the contact numbers of each level in the fourth step and the n level intervals divided equally in the fifth step, and analyzing the average mu is positioned in which interval, wherein the level corresponding to the interval in which the average mu is positioned is the evaluation level of the water resource bearing capacity.

Description

(1) Technical field [0001] The invention relates to a method for evaluating water resources, in particular to a method for evaluating the carrying capacity of water resources. It belongs to the field of artificial intelligence evaluation. (2) Background technology [0002] The size of water resources carrying capacity varies with the stages, goals and conditions of water resources development. It is not only an important aspect of hydrological cycle and water resources research, but also closely related to economic and social development and the coupling research of environmental systems. It can be seen that the evaluation of water resources carrying capacity must involve many factors such as resources, economy, environment and population, so there is a lot of uncertain information. In order to solve the influence of uncertain information and many interrelationships in water resources carrying capacity, protect the safety of water resources and maintain the sustainable deve...

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Problems solved by technology

Among them, the fuzzy comprehensive evaluation method, a seemingly reasonable calculation process, has subjective arbitrariness in the determination of the membership degree, and a large amount of useful information is lost; the gray correlation analysis method has the disadvantages that the evaluation value tends to be uniform and the resolution is not high. ; The theoretical modeling process of artificial neural network belongs to the black box method; the multi-objective decision-ideal point method, due to the difficulty in solving the multi-objective programming problem, it is difficult to fully consider the uncertain factors of the system

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