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Marine humidity prediction method, system and device and storage medium

A forecasting method and humidity technology, applied in forecasting, neural learning methods, biological neural network models, etc., can solve the problems of complicated calculation, poor forecasting accuracy of key meteorological parameters in energy consumption simulation, inconvenient use, etc., to improve forecasting speed and forecasting. The effect of precision, strong regional generality, and practicality

Active Publication Date: 2021-11-16
XI'AN UNIVERSITY OF ARCHITECTURE AND TECHNOLOGY
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Problems solved by technology

[0004] In order to solve the problems existing in the prior art, the present invention provides a marine humidity prediction method, system, device and storage medium, which integrates interpolation and secondary gray-scale correlation neural network, so as to solve the inconvenient use and troublesome calculation of common interpolation methods. The problem of poor prediction accuracy of key meteorological parameters in individual energy consumption simulations

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  • Marine humidity prediction method, system and device and storage medium
  • Marine humidity prediction method, system and device and storage medium
  • Marine humidity prediction method, system and device and storage medium

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[0044] The first aspect of the embodiments of the present invention provides a method for predicting ocean humidity that integrates interpolation and secondary gray-scale correlation neural network, including the steps of: acquiring humidity-related meteorological factor data; inputting humidity-related meteorological factor data into a preset FIDGRA-IPSO-BP ocean humidity prediction model; FIDGRA-IPSO-BP ocean humidity prediction model outputs ocean humidity prediction data. Specifically, such as figure 2 As shown, the method of establishing the FIDGRA-IPSO-BP ocean humidity prediction model is as follows:

[0045] Step 1. Normalize the original meteorological data, generate a comparison sequence from the data of other meteorological influencing factors (such as temperature, dew point temperature, atmospheric pressure, wind speed, etc.), generate a reference sequence from the humidity data, and use GRA to find and predict each meteorological moment The elements have similar...

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Abstract

The invention discloses a marine humidity prediction method, system and device and a storage medium, and the method comprises the steps: employing a BP neural network algorithm as a basic prediction algorithm for the filling demand of the intermittent loss of marine meteorological data and the change characteristics of the meteorological data, and based on the current situation and characteristics of the marine meteorological data, and proposing an improved particle swarm optimization BP neural network algorithm integrating interpolation and secondary gray correlation analysis to predict hourly humidity. The problem that the marine humidity hourly prediction is difficult to realize due to lack of marine meteorological data is solved, and the prediction speed and the prediction precision of the BP neural network on the humidity data are improved to a great extent by adopting a secondary gray correlation analysis algorithm.

Description

technical field [0001] The invention belongs to an ocean humidity prediction method, and in particular relates to an ocean humidity prediction method, system, device and storage medium based on fusion interpolation and secondary gray level correlation neural network. Background technique [0002] Heating and air-conditioning energy consumption are the main components of energy consumption of various civil buildings, and meteorological parameters are the basis for building energy-saving design and HVAC system operation. Using simulation software to conduct dynamic building energy consumption simulation to calculate, predict, evaluate and optimize building energy consumption and indoor environment comfort has become an increasingly common research method in the process of building energy-saving design, and the reliability of the simulation results is largely Depends on the availability of high-quality hourly meteorological data to describe local weather conditions. [0003] I...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06N3/08G06N3/04G06N3/02G06N3/00G06F16/29
CPCG06Q10/04G06N3/006G06N3/02G06N3/084G06F16/29G06N3/048Y02A90/10
Inventor 闫秀英吉星星刘大龙高嘉仪
Owner XI'AN UNIVERSITY OF ARCHITECTURE AND TECHNOLOGY