Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

Back propagation (BP) neural network landslide forecasting method based on optimized input layer

A BP neural network, input layer technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problems of one-sided narrowness, low disaster prediction accuracy, etc., achieving good universality and generalization, and complex structure. Effect

Inactive Publication Date: 2013-06-05
NANXINDA IMAGING TECH ENG SUZHOU CO LTD
View PDF0 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Even the existing method of using BP neural network to predict landslides has low disaster prediction accuracy due to its narrow selection of the input layer.

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
  • Back propagation (BP) neural network landslide forecasting method based on optimized input layer
  • Back propagation (BP) neural network landslide forecasting method based on optimized input layer
  • Back propagation (BP) neural network landslide forecasting method based on optimized input layer

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0017] The present invention will be described in detail below with reference to the accompanying drawings and in combination with embodiments.

[0018] refer to figure 1 , figure 2 As shown, the method for predicting landslide based on the BP neural network of the optimized input layer includes the following steps,

[0019] Step 1) The collection of relevant parameters of the landslide in the input layer; use Preprocess the raw data so that the input data falls between 0 and 1;

[0020] Step 2) BP neural network training operation; assume that the initial input values ​​are x 1 ,x 2 ,x 3 ... x n , the weight between the input node and the hidden layer node is , the weight between the hidden layer node and the output node is , the threshold in the hidden layer is , the threshold in the output layer is ,use with Input and output of computing nodes

[0021] with;

[0022] Step 3) Judging whether the re...

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 back propagation (BP) neural network landslide forecasting method based on an optimized input layer. The BP neural network landslide forecasting method includes steps: (1) related parameters of landslide of the input layer are collected; (2) BP neural network training is performed; (3) whether requirements are met is judged, the known expected value is t, errors are calculated according to an error formula of an output node, sample training is completed if the requirements are met, otherwise Vij theta i is firstly adjusted and then Wij theta j is adjusted according to the error reducing principle, and the corrected value is used for training until the requirements are met; and (4) after sample training is completed, the initialized forecasting sample value is input, and the forecasting value can be obtained. The BP neural network is adopted so that the BP neural network landslide forecasting method is simple to operate, strong in learning ability and good in adaptability.

Description

technical field [0001] The invention relates to the field of natural disaster monitoring and forecasting, in particular to a method for forecasting landslides based on a BP neural network of an optimized input layer. Background technique [0002] At present, the methods for landslide risk prediction can be divided into three categories: qualitative evaluation, quantitative evaluation, and uncertainty analysis. Qualitative evaluation methods include historical analysis and engineering geological analogy. Quantitative evaluation methods include rigid body limit equilibrium method and stress-strain analysis method. Among them, the stress-strain analysis method can be divided into: continuous medium mechanics method and discontinuous medium mechanics method. Uncertain analysis methods include reliability method, fuzzy method, gray system theory, cluster analysis, genetic algorithm and so on. [0003] The first two types of methods above all need to give a certain model for ca...

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 Applications(China)
IPC IPC(8): G06F19/00
Inventor 柯福阳周伟吴锷炳李亚云
Owner NANXINDA IMAGING TECH ENG SUZHOU CO LTD
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
Eureka Blog
Learn More
PatSnap group products