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Residential water consumption prediction method based on MIC-XGBoost algorithm

A prediction method and water consumption technology, applied in the field of smart water affairs, can solve the problems of low prediction accuracy and achieve the effect of reducing audit pressure

Pending Publication Date: 2022-07-26
遥相科技发展(北京)有限公司
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The present invention provides a method, device, and computer-readable storage medium for predicting residential water consumption based on the MIC-XGBoost algorithm. Its main purpose is to solve the problem of low prediction accuracy in predicting residential water consumption solely relying on the XGBoost algorithm.

Method used

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  • Residential water consumption prediction method based on MIC-XGBoost algorithm
  • Residential water consumption prediction method based on MIC-XGBoost algorithm
  • Residential water consumption prediction method based on MIC-XGBoost algorithm

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Embodiment 1

[0089] refer to figure 1 As shown, it is a schematic flowchart of a method for predicting residential water consumption based on the MIC-XGBoost algorithm provided by an embodiment of the present invention. In this embodiment, the method for predicting residential water consumption based on the MIC-XGBoost algorithm includes:

[0090] S1. Obtain a historical water consumption record, in which the water consumption of each month is sequentially extracted, and the influencing factor values ​​of different water consumption influencing factors corresponding to each month are obtained.

[0091] Interpretably, the historical water consumption record may be the monthly water consumption record of each household in the past year. The water influence factors include: temperature influence factors, seasonal influence factors, holiday influence factors, and the like. The influence factor value refers to the quantitative value corresponding to different water use influence factors, for ...

Embodiment 2

[0180] like Figure 4 The figure is a functional block diagram of a residential water consumption prediction device based on the MIC-XGBoost algorithm provided by an embodiment of the present invention, which can implement the residential water consumption prediction method based on the MIC-XGBoost algorithm in Embodiment 1.

[0181] The residential water consumption prediction device 100 based on the MIC-XGBoost algorithm of the present invention can be installed in electronic equipment. According to the realized functions, the residential water consumption prediction device 100 based on the MIC-XGBoost algorithm may include a water consumption-influencing factor numerical correspondence table building module 101, a target influencing factor acquiring module 102, an original XGBoost algorithm model training module 103, and a current month Water consumption prediction module 104 . The modules in the present invention can also be called units, which refer to a series of comput...

Embodiment 3

[0188] like Figure 5 As shown, it is a schematic structural diagram of an electronic device for implementing a method for predicting residential water consumption based on the MIC-XGBoost algorithm provided by an embodiment of the present invention.

[0189] The electronic device 1 may include a processor 10, a memory 11, a bus 12 and a communication interface 13, and may also include a computer program stored in the memory 11 and running on the processor 10, such as based on MIC-XGBoost Algorithmic residential water consumption forecasting procedure.

[0190] Wherein, the memory 11 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, mobile hard disk, multimedia card, card-type memory (for example: SD or DX memory, etc.), magnetic memory, magnetic disk, CD etc. The memory 11 may be an internal storage unit of the electronic device 1 in some embodiments, such as a mobile hard disk of the electronic device 1 . In othe...

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Abstract

The invention relates to the field of intelligent water affairs, and discloses a residential water consumption prediction method based on an MIC-XGBoost algorithm, and the method comprises the steps: obtaining influence factor values and water consumption of each month, constructing a water consumption-influence factor value corresponding table of water consumption influence factors, and employing a maximum information coefficient algorithm to obtain a water consumption-influence factor value corresponding table of the water consumption influence factors; calculating a target influence factor which has the maximum influence on the water consumption, training the original XGBoost algorithm model according to the water consumption and the influence factor numerical value of each month to obtain a target XGBoost algorithm model, and predicting the water consumption by utilizing the target XGBoost algorithm model according to the influence factor numerical value of the current month to obtain the predicted water consumption of the current month. The invention further provides a resident water consumption prediction device based on the MIC-XGBoost algorithm, electronic equipment and a computer readable storage medium. According to the method, the problem that the prediction accuracy is low when the water consumption of residents is predicted by only depending on the XGBoost algorithm can be solved.

Description

technical field [0001] The invention relates to the field of smart water affairs, in particular to a method, device, electronic device and computer-readable storage medium for predicting residential water consumption based on the MIC-XGBoost algorithm. Background technique [0002] With the construction of urban intelligence, the prediction of residential water consumption has become an important means of reviewing residential water consumption. [0003] Due to the shortcomings of traditional meter reading, which is prone to errors and has a large workload, electronic meter reading has gradually replaced traditional meter reading. Electronic meter reading improves the efficiency of meter reading, but it still brings great pressure to the auditors. Currently, there is a water consumption prediction method based on XGBoost, which can filter the audit data and obtain abnormal record data, but only rely on the XGBoost algorithm. To predict residential water consumption, there i...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06G06N20/20G06N5/00
CPCG06Q10/04G06Q50/06G06N20/20G06N5/01
Inventor 李佳贾小娥
Owner 遥相科技发展(北京)有限公司
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