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Water quality prediction method for mineral spring
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A technology for water quality prediction and mineral springs, which can be used in prediction, general water supply conservation, data processing applications, etc., and can solve the problems that the accuracy needs to be improved.
Inactive Publication Date: 2018-02-09
黑龙江省科学院火山与矿泉研究所 +2
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[0003] The present invention solves the problem that the accuracy of mineral water quality prediction by the existing gray prediction model needs to be improved
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specific Embodiment approach 1
[0056] Specific implementation mode one: combine figure 1 To describe this embodiment,
[0057] A water quality prediction method for mineral springs, comprising the following steps:
[0058] Step 1. Extract the historical data of the mineral spring as the original sequence X=[x(1), x(2),...,x(n)]; where x(1), x(2),..., x(n) are respectively It is the original data of the calendar year or the past month, and n represents the total number of data;
[0059] Step 2. Establish a gray-scale theoretical prediction model:
[0060] Step 2.1, performing sliding average processing on the original data;
[0061] Moving average of data at both ends: x (0) (1)=[3x(1)+x(2)] / 4
[0062] x (0) (n)=[x(n-1)+3x(n)] / 4
[0063] intermediate data moving average x (0) (k)=[x(k-1)+2x(k)+x(k+1)] / 4
[0064] x (0) (1), x (0) (2),...,x (0) (n) are the smoothed data respectively, and the smoothed sample data is X (0) =[x (0) (1), x (0) (2),...,x (0) (n)];
[0065] Generate X (0) 1-AGO seq...
Embodiment
[0104] The present invention can predict various indicators of water quality. In order to illustrate the effect of the present invention, the carbon dioxide content in the south drinking spring of Wudalianchi is taken as an example to illustrate. Simultaneously the present invention can carry out prediction for the data of calendar year or every month, if it is for the data of calendar year, the data of 12 months in each year can be averaged and modeled and predicted, if it is for modeling and predicted by month, it can be The data collected in one month is averaged and then modeled and predicted.
[0105] The following is a modeling forecast based on the data of Wudalianchi South Yinquan over the years
[0106] The carbon dioxide content in the south drinking spring of Wudalianchi, the measured values are as follows
[0107]
[0108] Step 1: Because it is necessary to predict the medium-term development trend of the five-year development, and the measured data has disco...
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Abstract
The invention relates to a water quality prediction method for mineral spring, and relates to a water quality prediction method. The water quality prediction method for mineral spring can solve the problem that the accuracy of water quality prediction for a current gray prediction model needs to be improved. The water quality prediction method for mineral spring includes the steps: extracting thehistorical data of the mineral spring as an original sequence, and based on the original data, establishing a gray level theory prediction model; at the same time, utilizing MATLABsoftware to establish a BP neural network model, setting the number of the first layer (hidden layer) of nerve cells as 3 and the number of the first layer of nerve cells as 1, and based on the original data, training the BP neural network model; and finally taking the analog value of the gray level theory prediction model after correction and the final output value of the neural network as the input values together, establishing a BP neural network model by means of the MATLABsoftware again, and outputting the prediction result, that is, the final result of water quality prediction through grey level-BP neuralnetwork-BP neural network. The water quality prediction method for mineral spring is suitable for water quality prediction.
Description
technical field [0001] The invention relates to a water quality prediction method. Background technique [0002] For the prediction of water quality, water quality simulation at home and abroad has made great progress, but there are still many problems to be further studied. In recent years, the gray system theory founded by Professor Deng Julong has been popularized in China. The GM(1,1) model is a commonly used forecasting model of the gray system theory, and it is also an important content in the application of the gray system theory. It has been widely used in water quality prediction. It solves many water quality prediction problems that are difficult to solve by general methods. The gray system method of water quality prediction is based on water quality monitoring data. The calculation process is simple, the accuracy is high, and the prediction results are reasonable. It conforms to the gray characteristics of the water system. The model has good adaptability, and th...
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