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Prediction method, device and equipment for water consumption

A prediction method and water consumption technology, applied in the field of data processing, can solve the problems of poor adaptability and large error in prediction results, and achieve the effect of high accuracy and strong prediction adaptability.

Pending Publication Date: 2020-02-04
杭州鲁尔物联科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Big error in prediction results and poor adaptability

Method used

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  • Prediction method, device and equipment for water consumption
  • Prediction method, device and equipment for water consumption
  • Prediction method, device and equipment for water consumption

Examples

Experimental program
Comparison scheme
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Embodiment 1

[0027] figure 1 It is a flow chart of a method for forecasting water consumption provided by Embodiment 1 of the present invention. This embodiment is applicable to the situation of forecasting water consumption. The method can be executed by a water consumption forecasting device or system. The device can pass implemented in software and / or hardware, such as figure 1 As shown, the method specifically includes the following steps:

[0028] Step 110, acquiring historical water consumption data of the target area.

[0029] Wherein, the target area refers to the area used to predict the water consumption, which may be a certain city or other designated areas. The historical water consumption data includes water consumption data or water consumption of the target area for a period of time before the current moment that needs to be predicted. Historical water use data can also include information such as date and time.

[0030] Further, the historical water consumption data of ...

Embodiment 2

[0052] figure 2 It is a flow chart of a method for predicting water consumption provided by Embodiment 2 of the present invention. This embodiment is a further refinement of the previous embodiment, such as figure 2 As shown, the method includes the following steps:

[0053] Step 210, acquiring historical water consumption data of the target area.

[0054] Step 220, according to the change rule of the historical water use data over time, divide the historical water use data into industrial water use data and domestic water use data.

[0055] Step 230, respectively determine the impact factors of the industrial water data and the domestic water data, and acquire the values ​​of the impact factors.

[0056] Step 240, performing normalization processing on the industrial water data and domestic water data to obtain normalized industrial water data and normalized domestic water data.

[0057] Wherein, normalization refers to normalizing the value of each water consumption dat...

Embodiment 3

[0098] image 3 It is a schematic diagram of a water consumption forecasting device provided in Embodiment 3 of the present invention, as image 3 As shown, the device includes: a historical information acquisition module 310 , an information division module 320 , a neural network model establishment module 330 and a water consumption prediction module 340 .

[0099] Among them, the historical information acquisition module 310 is used to obtain the historical water use data of the target area; the information division module 320 is used to divide the historical water use data into industrial water use data and domestic water use data according to the change rule of the historical water use data over time ; The neural network model building module 330 is used to establish the industrial water prediction neural network model and the domestic water prediction neural network model respectively according to the industrial water data and the domestic water data; the water consumpti...

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Abstract

The invention discloses a method, a device and equipment for predicting water consumption. The water consumption prediction method comprises the following steps: acquiring historical water consumptiondata of a target area; dividing the historical water consumption data into industrial water consumption data and domestic water consumption data according to the change rule of the historical water consumption data along with time; respectively establishing an industrial water prediction neural network model and a domestic water prediction neural network model according to the industrial water data and the domestic water data; and predicting the water consumption of the target area according to the industrial water prediction neural network model and the domestic water prediction neural network model. According to the technical scheme of the embodiment of the invention, the historical water consumption data and the change rule thereof are divided into the industrial water and the domesticwater firstly, and then different convolutional neural network models are established respectively to predict the water consumption, so that the automatic prediction of the water consumption is realized, and the prediction result is strong in adaptability and high in precision.

Description

technical field [0001] The embodiments of the present invention relate to the technical field of data processing, and in particular to a method, device and equipment for predicting water consumption. Background technique [0002] Urban and rural water consumption forecasting can analyze the water consumption for a period of time in the future, and now plays an increasingly important guiding role in water resource planning, water management, and scientific scheduling of water supply systems. Therefore, it is an important work to realize the sustainable utilization of water resources to study the technology and method of urban water consumption forecasting. [0003] Most of the existing urban and rural tap water consumption scale predictions are based on the "Urban Water Supply Engineering Planning Specification" GB50282-98 and the "Rural Water Supply Design Specification" CECS82:96, which is determined by multiplying the per capita comprehensive water consumption index by the...

Claims

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Application Information

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IPC IPC(8): G06Q10/06G06Q10/04G06Q50/06G06N3/02
CPCG06Q10/06315G06Q10/04G06Q50/06G06N3/02
Inventor 杨承奂董梅胡辉宋杰
Owner 杭州鲁尔物联科技有限公司
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