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A water supply pipe burst time prediction method and device based on a neural network

A neural network and time prediction technology, applied in the field of artificial intelligence, can solve problems such as large number of iterations, slow network convergence speed, network instability, etc., and achieve the effect of reasonable use of resources, fast convergence speed, and short training time

Pending Publication Date: 2019-04-02
FOSHAN UNIVERSITY
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AI Technical Summary

Problems solved by technology

The existing BP network neural system has serious defects, such as many iterations, slow network convergence, unstable network, easy to fall into local minimum, etc.

Method used

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  • A water supply pipe burst time prediction method and device based on a neural network
  • A water supply pipe burst time prediction method and device based on a neural network
  • A water supply pipe burst time prediction method and device based on a neural network

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Embodiment Construction

[0045] The concept, specific structure and technical effects of the present disclosure will be clearly and completely described below in conjunction with the embodiments and drawings, so as to fully understand the purpose, scheme and effect of the present disclosure. 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.

[0046] Such as figure 1 Shown is a flow chart of a neural network-based water supply pipe burst time prediction method according to the present disclosure, combined belowfigure 1 A method for predicting burst time of a water supply pipe based on a neural network according to an embodiment of the present disclosure will be described.

[0047] This disclosure proposes a neural network-based method for predicting the burst time of a water supply pipe, which specifically includes the following steps:

[0048] Step 1, read the data set;

[0049] Step 2,...

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Abstract

The invention discloses a water supply pipe burst time prediction method and device based on a neural network, which relates to the technical field of artificial intelligence, solves the influence ofthe environment on damage of a water supply pipeline by taking the environment where the water supply pipeline is located as an attribute and using the improved BP neural network algorithm and the least square method model, greatly optimizes the defects of the BP neural network algorithm, and has the advantages of a Gaussian Newton method and a gradient method. According to the present invention,the BP neural network model is optimized, so that the network has higher convergence speed and shorter training time, the operation speed is accelerated, and the water supply pipeline rupture time canbe obtained more efficiently and quickly. Resources are reasonably utilized, waste is avoided, unnecessary damage to residents and the society is avoided, after the breaking time of the water supplypipeline is known, the water supply pipeline can be replaced before being broken, and management by municipal staff is facilitated.

Description

technical field [0001] The present disclosure relates to the technical field of artificial intelligence, in particular to a neural network-based method and device for predicting burst time of a water supply pipe. Background technique [0002] In recent years, more and more pipe bursts have occurred in water supply and distribution pipelines in cities all over the country, seriously affecting people's daily life and industrial production. Due to the frequent occurrence of water supply pipeline burst accidents, the existing technology can only predict the service life of the material of the water supply pipeline, and cannot predict the impact of the environment on the water supply pipeline, but the impact of the environment on the water supply pipeline in real life is also It cannot be ignored that the environment in which the water supply pipeline is located may cause the water supply pipeline to be damaged or ruptured in advance, making it unusable. If the damaged water supp...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06Q10/04G06N3/08
CPCG06N3/08G06Q10/04G06F18/214
Inventor 姜春涛冯樱杨志鹄于辉黄颖欣黄钢忠吴志炜侯菁菁
Owner FOSHAN UNIVERSITY
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