Combined model water level prediction method based on similarity search

A technology of similarity search and combination model, applied in the combined prediction field of BP neural network and support vector machine, can solve the problems of poor adaptability and mastery of professionals, so as to reduce the dimension, reduce the prediction time, and achieve a good prediction effect. Effect

Inactive Publication Date: 2015-11-11
HOHAI UNIV
View PDF2 Cites 16 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The most widely used are hydrological prediction models established for specific watersheds, such as the Xin'anjiang model, e...

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
  • Combined model water level prediction method based on similarity search
  • Combined model water level prediction method based on similarity search
  • Combined model water level prediction method based on similarity search

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0016] Below in conjunction with specific embodiment, further illustrate the present invention, should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention, after having read the present invention, those skilled in the art will understand various equivalent forms of the present invention All modifications fall within the scope defined by the appended claims of the present application.

[0017] Such as figure 1 For the method flow, including the following parts:

[0018] a) Data preprocessing part: mainly includes dealing with vacancy and error data. According to the characteristics of hydrological water level data, vacant data can be divided into four types: data missing for more than 15 consecutive days, missing for 8-15 consecutive days, missing for 4-7 consecutive days, and missing for less than 4 consecutive days. In the first case, the records of the current month are dele...

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 discloses a combined model water level prediction method based on similarity search. Water level of previous days related to a day to be predicted is confirmed to be sequences to be matched by utilizing correlation coefficient. A series of water level time sequences which are not similar to the sequences to be matched are searched from historical data on the basis of similarity search and eliminated from original time sequences and then act as training sets of a prediction model. The method mainly comprises data preprocessing, similarity search and a combined prediction model. Data preprocessing aims at filling gap data and restoring error data. According to similarity search, a series of time sequences which are not similar to the sequences to be matched are eliminated from the historical data of previous years by utilizing dynamic bending distance and the fixed slide window technology. The combined prediction model has two basic models: a BP neural network improved by an LM algorithm and a support vector machine, and proportion of the basic models in current prediction is dynamically adjusted by utilizing the Bayes theorem according to prediction performance of each basic model at the previous moment. The high-precision and real-time requirements required by flood prevention and disaster resistance can be realized.

Description

technical field [0001] The invention relates to a method for predicting water level based on a combined model of similarity search, in particular to the preprocessing of hydrological water level data, the use of similarity search to effectively reduce the dimension of the training set, and the improved BP neural network and support vector based on LM algorithm The invention discloses a machine combination forecasting method, which belongs to the field of information technology. Background technique [0002] With the advancement of the times and the wide application of computers, more and more content is stored on the computer. How to mine useful information from these massive historical data to serve the prediction of the future, and at the same time, it will not be lost in the historical data. Redundancy, vacancies and wrong information interference have become a topic of concern to people. Especially in the field of hydrology, China has a large number of hydrological surv...

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
IPC IPC(8): G06N3/02G06K9/62G01F23/00
Inventor 张鹏程肖艳马辉孙颖桃韩晴曾金伟
Owner HOHAI UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap