Indoor temperature and humidity prediction method and system

Abstract

The invention provides an indoor temperature and humidity prediction method and system. The method comprises the steps of firstly, acquiring the historical sample data of different hot areas, whereinthe historical sample data include the indoor historical temperature data, the indoor historical humidity data, the outdoor historical temperature data, the outdoor historical humidity data and the indoor equipment energy consumption; secondly, building a multi-level basic prediction model about the temperature and the humidity; thirdly, calculating the target order of the multi-order basic prediction model according to the historical sample data to obtain an advanced prediction model with the target order; fourthly, training the advanced prediction model by using the historical sample data toobtain the final target prediction model; and fifthly, carrying out prediction to obtain the target temperature and humidity data according to the current sample data and the target prediction model.With the indoor temperature and humidity prediction method and system, the prediction on the indoor temperature and humidity is realized with the low cost and the accurate results.

Description

technical field [0001] The invention relates to the field of temperature and humidity prediction, in particular to a method and system for predicting indoor temperature and humidity. Background technique [0002] At present, there are a lot of precision instruments and equipment in the laboratory or computer room. Due to the high precision of these instruments and equipment, if the temperature changes in the environment or the humidity is high, the accuracy will decrease. Predict the temperature and humidity of the environment, and then control the temperature and humidity of the environment in advance. [0003] At present, most of the prediction methods for the temperature and humidity values ​​of data centers are developed based on the principles of dynamic heat transfer and air flow, and use purely physical methods to simulate the performance of houses. For this physical modeling method, although a certain accuracy can be guaranteed, it needs to be recalculated for each ...

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Problems solved by technology

For this physical modeling method, although a certain accuracy can be guaranteed, it must be recalculated for each data center, and the modeling process is very complicated

And for actual buildings, since their modeling principle is the detailed modeling of the basic physics and the interaction between the components of the building, there is a specific prediction model for each data center, according to the area of ​​the data center Factors that can affect the temperature and humidity in the data center, such as floor height, building materials, orientation, density of cabinets, and even sunlight intensity at different times, can be used to deduce the changes in temperature and humidity based on thermodynamic and aerodynamic formulas. For these simulators has a very high computational cost

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