Artificial neural network algorithm based indoor environment negative feedback adjustment system

Abstract

The invention discloses an artificial neural network algorithm based indoor environment negative feedback adjustment system. The artificial neural network algorithm based indoor environment negative feedback adjustment system comprises a data processing platform, an intelligent control system, an indoor environment monitoring system, a human thermal sensation feedback system and a basic item parameter input system; and the data processing platform is connected with the intelligent control system. according to the artificial neural network algorithm based indoor environment negative feedback adjustment system provided by the invention, each weight matrix is obtained after environment parameters and human hot sensation feedback values are subjected to feedback calculation through a model, and a scheme of improving the human comfort evaluation indexes is provided after the intelligent control system processes the weight matrixes, and correction values of indoor environment parameters areobtained through data processing; the artificial neural network algorithm based indoor environment negative feedback adjustment system can monitor the indoor environment wholly, can realize feedback automatic adjustment, has a learning function and can obtain the optimal indoor environment parameters automatically based on different environments.

Description

technical field [0001] The invention relates to the technical field of indoor environment negative feedback adjustment systems, in particular to an indoor environment negative feedback adjustment system based on an artificial neural network algorithm. Background technique [0002] With the development of economy and technology, people in our country pay more and more attention to their own living environment, forcing people to put forward higher requirements for the current environment, which is also a requirement for the indoor environment. According to statistics, most people spend more than 70% of their time indoors, so the quality of the indoor environment directly affects the comfort and health of the people in the room. At present, the indoor environment is mainly based on traditional monitoring, including temperature, humidity, and carbon dioxide concentration detection. "Green Building Evaluation Standards" GB / T 50378-2014, aimed at rooms with high density of people...

AI Technical Summary

Problems solved by technology

[0004] In order to solve the problem that the existing feedback adjustment system is relatively single, the adjustment mode is fixed and cannot be adjusted, there is no self-learning function, and there are limitations in use, the purpose of the present invention is to provide an indoor environment negative feedback adjustment system based on artificial neural network algorithm, To solve the problems raised in the above-mentioned background technology

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