Research on Combined Forecasting Model for Logistic Material Demand Based on BP Neural Network and Grey System Theory

2016 ◽  
Vol 31 (4) ◽  
Keyword(s):  
Neural Network ◽  
System Theory ◽  
Bp Neural Network ◽  
Grey System Theory ◽  
Forecasting Model ◽  
Grey System ◽  
Combined Forecasting

Study on Deformation Prediction of Landslide Based on Grey Theory and BP Neural Network

2012 ◽  
Vol 204-208 ◽  
pp. 520-525 ◽  
Author(s):  
Rong Yu Li ◽  
Yong Fen Ruan ◽  
Shi Sheng Li ◽  
Yong Hong Wu
Keyword(s):  
Neural Network ◽  
System Theory ◽  
Bp Neural Network ◽  
Theory Model ◽  
Grey System Theory ◽  
Practical Significance ◽  
Grey Theory ◽  
Grey System ◽  
Engineering Project ◽  
Landslide Deformation

The stability of the landslide can be effectively evaluated and predicted by predicting the future development of landslide deformation according to the actual deformation of the landslide. Therefore, the accuracy of the prediction regarding the landslide deformation determines the validity of the landslide stability assessment. The GM (1.1) model in the grey system theory, uses displacement time series to establish the grey differential equation. By solving the equation, we can obtain a time response function, which can then be used to predict the landslide deformation. The BP neural network is a used for training and exercising on the deformed samples. After the error meets the requirement, we can then use the trained model to predict the landslide deformation. This paper use both grey system theory model and BP neural network model to predict Jinlong ditch application field landslide deformation.The prediction results are compared and analyzed to test the accuracy of these two predictions. Finding a more accurate prediction method for application in actual engineering project has practical significance.

Study on the second grey relational grade and its properties

Kybernetes ◽  
2010 ◽  
Vol 39 (8) ◽  
pp. 1330-1335 ◽  
Author(s):  
Yan Ma
Keyword(s):  
System Theory ◽  
Design Methodology ◽  
Grey System Theory ◽  
Forecasting Model ◽  
Grey System ◽  
Content Type ◽  
Grey Forecasting ◽  
Grey Relational Grade ◽  
Grey Relational ◽  
Practical Implications

PurposeThe purpose of this paper is to propose a second relational grade based on the general grey relational grade and analyze several of its properties.Design/methodology/approachGrey system theory. The paper proposes and studies second grey relational grade, establishes second grey relational formula, and studies several characteristics of second grey relational formula.FindingsProposing a second relational grade proved it could solve the problem of the parallelism partly and weaken relativity of space position.Research limitations/implicationsUntil now, the problem of the consistency could not be solved, nor could the problem of the effect which keeps the sequence the same.Practical implicationsThe precision of the grey forecasting model could be strengthened if used in the forecasting model.Originality/valueThe general relational grade only thinks over the relation between two sequences but does not involve the relation in one sequence. The second relational grade considers these two, so if the forecasting model is established with it, the model should be more exact.

Improved BP Neural Network Model Applied in Settlement Analysis

2014 ◽  
Vol 580-583 ◽  
pp. 2848-2852
Author(s):  
Liang Bo Gao
Keyword(s):  
Neural Network ◽  
System Theory ◽  
Bp Neural Network ◽  
Forecasting Model ◽  
Construction Engineering ◽  
Gray System Theory ◽  
Gray System ◽  
Subway Construction ◽  
Bp Neural Network Model ◽  
Settlement Analysis

According to the settlement and deformation of pavement in subway construction, the paper improved on the basis of gray system theory and BP neural network forecasting model. The method is adapted to modified residual prediction model to predict with engineering examples. It provides decision-making basis for construction engineering and monitoring.

Sign in / Sign up

Export Citation Format

Share Document