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Water quality data abnormity early warning method based on multi-dimensional data distribution density

A multi-dimensional data, distribution density technology, applied in the direction of electrical digital data processing, special data processing applications, water testing, etc., can solve the problems of high false alarm rate, lack, low detection rate, etc., to achieve high abnormal detection rate, The effect of low false positive rate

Pending Publication Date: 2021-12-10
北京金水永利科技有限公司
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Problems solved by technology

[0004] The detection rate obtained by a single water quality index monitoring technology is low and the false alarm rate is high, and the two (or pairwise combination) water quality index monitoring technology can only monitor

Method used

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  • Water quality data abnormity early warning method based on multi-dimensional data distribution density
  • Water quality data abnormity early warning method based on multi-dimensional data distribution density
  • Water quality data abnormity early warning method based on multi-dimensional data distribution density

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Embodiment 1

[0046] Such as figure 1 As shown, Embodiment 1 of the present application provides a method for early warning of abnormal water quality data based on multidimensional data distribution density, including:

[0047] Step 110, collect multi-dimensional water quality index data points, and map the multi-dimensional water quality index data points to a two-dimensional coordinate system based on a nonlinear dimensionality reduction algorithm to obtain two-dimensional water quality data points;

[0048] Such as figure 2 As shown in , the multi-dimensional water quality index data points are mapped to the two-dimensional coordinate system, which specifically includes the following sub-steps:

[0049] Step 210, collect the original high-dimensional water quality data point set A={A at a certain moment 1 ,A 2 ,…A n}, set the two-dimensional mapping point set B={B 1 ,B 2 ,...B n};

[0050] Step 220, calculate the original high-dimensional water quality data point A i 、A j The ...

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Abstract

The invention discloses a water quality data abnormity early warning method based on multi-dimensional data distribution density. The method comprises the following steps: collecting multi-dimensional water quality index data points, and mapping the multi-dimensional water quality index data points into a two-dimensional coordinate system based on a nonlinear dimension reduction algorithm to obtain two-dimensional water quality data points; calculating a local abnormal factor of the two-dimensional space water quality data distribution by using a local abnormal factor algorithm according to the two-dimensional water quality data points; and determining water quality abnormal points according to the local abnormal factors. The problems of low single-factor early warning detection rate and high false alarm rate are solved, high-dimensional water quality index data point visualization is realized, change abnormity of data distribution can be visually known, high-dimensional water quality data abnormal points can be accurately calculated, and the method has higher abnormity detection rate and lower false alarm rate.

Description

technical field [0001] The invention relates to the field of early warning of abnormal water quality, in particular to a method for early warning of abnormal water quality data based on multidimensional data distribution density. Background technique [0002] Abnormal water quality detection is an important part of the water pollution early warning system. It can detect pollutant leakage or human poisoning accidents in a timely and effective manner, and provide early warning information and auxiliary treatment methods. It is of great significance to ensure the safety of the water system and improve the rapid emergency response capability. . [0003] Most of the existing water quality monitoring methods judge whether the water quality is abnormal only based on whether a single water quality index exceeds the standard, or judge whether the water quality is abnormal by monitoring the change trend of two (or a combination of two) water quality indicators with high data correlati...

Claims

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Application Information

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IPC IPC(8): G06F30/20G01N33/18G06F119/02
CPCG06F30/20G01N33/18G06F2119/02
Inventor 王正安新国董雅欠邹志强
Owner 北京金水永利科技有限公司