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An intelligent water affair management method and system based on deep learning

A technology of water management and deep learning, applied in the field of water management, can solve the problems of high cost and low efficiency of risk identification

Active Publication Date: 2019-06-21
TERMINUSBEIJING TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In view of this, the purpose of this application is to propose a smart water management method and system based on deep learning, improve the level of water management risk identification, and solve the technical problems of low efficiency and high cost of risk identification in the current water management process

Method used

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  • An intelligent water affair management method and system based on deep learning
  • An intelligent water affair management method and system based on deep learning
  • An intelligent water affair management method and system based on deep learning

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Embodiment Construction

[0051] The application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain related inventions, not to limit the invention. It should also be noted that, for the convenience of description, only the parts related to the related invention are shown in the drawings.

[0052] It should be noted that, in the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and embodiments.

[0053] figure 1 A flow chart showing a method for intelligent water management based on deep learning according to an embodiment of the present invention. Such as figure 1 As shown, the smart water management method based on deep learning includes:

[0054] Step S11, constructing...

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Abstract

The embodiment of the invention provides an intelligent water affair management method and system based on deep learning. The method comprises the following steps: constructing a water affair management feature set through existing water affair management data; Constructing a deep learning network based on the water affair management feature set; Collecting real-time water affair data, importing the real-time water affair data into the deep learning network, and predicting a water affair management risk; And performing water affair management according to the water affair management risk. According to the intelligent water affair management method and system based on deep learning, by combining the water affair management practice method and the deep learning characteristics, the water affair management efficiency is improved, and the labor amount of water affair management personnel is reduced.

Description

technical field [0001] This application relates to the field of water management, in particular to a method and system for intelligent water management based on deep learning. Background technique [0002] Smart water is an important part of smart city construction, aiming to improve water management and service levels and provide better support for urban development. Smart water business takes water supply business as the core, covering the management of raw water, water supply, secondary water supply and sewage treatment. Smart water service uses geographic information service as the basic platform and business process as the core to build a water service business system to realize the intelligence of daily production and management. However, at present, the artificial intervention rate of smart water affairs is high, and the risk identification ability is weak, which requires a lot of manpower and material resources for trivial risk discovery, which seriously affects the...

Claims

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Application Information

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IPC IPC(8): G06Q10/06G06Q50/06G06K9/62
Inventor 鲍敏
Owner TERMINUSBEIJING TECH CO LTD
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