t-s fuzzy neural network indoor air quality assessment system based on improved particle swarm

Abstract

The invention discloses a T-S (Takagi-Sugeno) fuzzy neural network indoor air quality evaluation system based on modified particle swarm; the system comprises an intelligent home control center, an indoor air quality detector, an intelligent home control terminal and a client; the system allows a user to log in to a Web server of the system through a computer or cellphone browser in order to check out indoor air quality parameters; the system has an intelligent control mode and a manual control mode for a user to select; in the intelligent control mode, the system adjusts home appliances intelligently according to a compiled control strategy without manipulation, so that indoor air quality is kept optimal; an algorithm model compiled in a CPU (central processing unit) of the indoor air quality detector refers to the introduction of modified particle swarm algorithm based on T-S fuzzy neural network, and the modified particle swarm optimization has good global optimization and converging properties. The system of the invention can provide detection, evaluation and monitoring for indoor air quality, and the evaluation results are objective, accurate and reliable.

Description

technical field [0001] The invention belongs to indoor air quality evaluation based on smart home, and the evaluation system includes detection, evaluation and monitoring. Background technique [0002] With the continuous deepening of people's understanding of the importance of the indoor environment, indoor air quality has attracted more and more attention. On average, modern people spend 80% to 90% of their time indoors, and at the same time, they inevitably inhale a large amount of indoor air. The traditional indoor air quality evaluation method has the comprehensive index method, which is simple in form and convenient in calculation, but it often cannot highlight the influence of the largest pollutants, and there are often large errors between the measured results and the actual situation. Since indoor air quality is still a fuzzy concept, and there is no unified and authoritative definition so far, some people try to study it with fuzzy mathematics. It is more accurate...

AI Technical Summary

Problems solved by technology

The traditional indoor air quality evaluation method has the comprehensive index method. This method is simple in form and easy to calculate, but it often cannot highlight the influence of the largest pollutants, and there are often large errors between the measured results and the actual situation.

Since indoor air quality is still a fuzzy concept, and there is no unified and authoritative definition so far, some people try to study it with fuzzy mathematics. More accurate response to actual problems, but it is more troublesome to apply to actual situations

[0003] Among the existing measuring instruments, most of them measure one or several kinds of indoor pollutants, and can only provide simple indoor air quality conditions. Purifiers, etc., there is no reliable reference standard, and sometimes the outdoor air quality is worse than indoors. Under such conditions, opening windows will aggravate indoor air pollution

Sometimes the outdoor air quality is not good without opening the windows before going out, and the outdoor air quality may improve after a few hours, but you cannot open the windows for ventilation when you are not at home, which makes it very inconvenient to adjust the indoor air quality

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