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Method for predicting industrial sewage inflow based on ARIMA model

A technology for industrial sewage and water inflow, applied in forecasting, CAD numerical modeling, energy industry, etc., can solve problems such as large fluctuation range, uncontrollable influent load, and strong mutation

Inactive Publication Date: 2018-09-21
广东省广业检验检测集团有限公司
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Problems solved by technology

Different from other industrial production processes, the influent load of sewage treatment plants is generally not adjustable, and its mutation is strong and the fluctuation range is large. Especially under the influence of rainfall, it has a strong impact on the biochemical treatment system

Method used

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  • Method for predicting industrial sewage inflow based on ARIMA model
  • Method for predicting industrial sewage inflow based on ARIMA model
  • Method for predicting industrial sewage inflow based on ARIMA model

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Embodiment

[0072] Such as figure 1 As shown, a prediction method of industrial sewage inflow based on ARIMA model includes the following steps:

[0073] S1. Considering that the main influencing factor of the water inflow is the sudden discharge of industrial sewage or natural precipitation, the reason why these data cannot be obtained at present is that the water inflow is only based on the characteristics of the data sequence itself, so the sewage inflow itself is selected as the input variable; the sewage is obtained The original time series data of water inflow, and conduct data quality analysis to check whether there are dirty data and data that cannot be directly analyzed in the original time series data;

[0074] The dirty data includes missing values, outliers, and data containing special characters; the outliers are initially judged by using a univariate scatter diagram, and then the outliers are checked using the statistical 3σ method;

[0075] In this embodiment, data feature...

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Abstract

The invention discloses a method for predicting industrial sewage inflow based on an ARIMA model. The method comprises the following steps: analyzing initial time series data to meet a requirement onARIMA model establishment; preprocessing abnormal data by eliminating, filling and the like; removing data noise through moving average filtering; by a unit root testing method, performing ADF testingon the stability of a time series; analyzing and verifying the non-randomness through an autocorrelation coefficient; preliminarily determinating an autoregressive and moving average order of the ARIMA (p, d, q) model, and then performing order determination on the model through combination with an AIC information criterion; optimizing model parameters by a least squares method; finally, testinga residual and evaluating a simulation result to determine a final prediction model. Acquired sewage inflow data are determined, and the obtained prediction model is used for predicting test data, andan output of the model is a prediction result of the sewage inflow. By the method, the model is succinct, the fitting effect of the prediction model is very good, and the precision is high.

Description

technical field [0001] The invention relates to the technical field of prediction of sewage inflow in a sewage treatment plant, in particular to a method for predicting the inflow of industrial sewage based on an ARIMA model. Background technique [0002] With the continuous improvement of the degree of industrialization and the increase of population, the discharge of industrial sewage is increasing rapidly, which has a huge impact on the environment. Countries all over the world have invested a lot of money in the research of industrial sewage treatment technology and developed many new technologies. And new technology has played a huge role in improving the water environment. At present, the sewage treatment plants that all countries are vigorously building are recognized as an effective way to solve the current situation of water pollution. It requires a good investigation and prediction of the water quality and quantity of the newly built plant area, in order to select...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/26G06F17/50
CPCG06Q10/04G06Q50/26G06F30/20G06F2111/10Y02P80/10
Inventor 陈新泉薛菲李继庚洪蒙纳江伦
Owner 广东省广业检验检测集团有限公司
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