Unlock instant, AI-driven research and patent intelligence for your innovation.

Water depth prediction method and system based on time series

A technology of time series and forecasting method, which is applied in the survey of open-air water sources, measuring the depth of open-air water sources, measuring devices, etc., and can solve the problem of non-overlapping positions of water depth measurement points

Active Publication Date: 2019-10-08
SHANGHAI JIAOTONG UNIV
View PDF2 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The system proposed by the present invention solves the problem that the positions of the sounding measurement points do not overlap, and uses the mature time series method to predict the water depth simply and effectively

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Water depth prediction method and system based on time series
  • Water depth prediction method and system based on time series
  • Water depth prediction method and system based on time series

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0031] The present invention will be described in detail below in conjunction with specific embodiments. The following examples will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0032] Modern forecasting systems generally predict future values ​​by analyzing historical data and various influencing factors. The present invention discards factors such as hydrology, sediment conditions, and meteorology that are difficult to quantify and estimate, and focuses on analyzing historical data of water depth values. Usually the water depth measurement points given by the measurement unit are changed each time, so the present invention first maps the measurement points in different period...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention provides a water depth prediction method and system based on time sequence. At first, a water depth point, which has been measured for many times, is projected to a same position through a proper method, and then subsequent calculation is performed. According to the measured values of a same position in different periods, the future water depth value of the position can be predicted through a weighted average method in time sequence and gradient descent of machine learning. The provided method solves the problem that the positions of multi-time measured data provided by a water depth measuring unit are not overlapped. On the basis of the distance relationships between measured points, the measured points are projected to a same position, then subsequent calculation is carried out, and the future water depth is simply and effectively predicted through a time sequence method.

Description

technical field [0001] The present invention relates to the field of water depth prediction, in particular to a time series-based water depth prediction method and system. In particular, it relates to a water depth prediction method based on time series realized by means of related algorithms in the field of machine learning. Background technique [0002] The main function of the prediction method based on time series and machine learning is to have an accurate or approximate judgment on the future development direction of the situation in advance, and to make preparations or countermeasures in advance to create huge benefits or reduce losses caused by risks. The time series-based forecasting method is an indispensable technology in the era of modern Internet information explosion. If the information hidden behind a large amount of data can be extracted, the benefits obtained will be huge. This type of forecasting method has been widely used in e-commerce, financial industr...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G01C13/00
CPCG01C13/008Y02A90/30
Inventor 曹健罗文斌童志华朱鹏宇刘卫平周树高钱诗友祁明良卢虹宇刘涛屈斌蔡相芸
Owner SHANGHAI JIAOTONG UNIV