The short-term life prediction model of gearbox based on chaotic neural network

2011 ◽  
Author(s):  
Xiao-hui Chen ◽  
Li-ming Cui ◽  
Jun-xing Li
Keyword(s):  
Neural Network ◽  
Prediction Model ◽  
Life Prediction ◽  
Chaotic Neural Network ◽  
Short Term ◽  
Life Prediction Model

Research on Railway Engineering Cost Prediction Model Based on Chaotic Neural Networks and CS

2011 ◽  
Vol 204-210 ◽  
pp. 1291-1294
Author(s):  
Yan Chun Chen
Keyword(s):  
Neural Network ◽  
Prediction Model ◽  
Influence Factors ◽  
Chaotic Neural Network ◽  
Short Term ◽  
Chaotic Neural Networks ◽  
Improve Accuracy ◽  
Railway Engineering ◽  
The Cost ◽  
Engineering Cost

It is always hard to draw on the experience of completed projects to predict engineering cost, and the nonlinear characteristic of the influence factors of engineering cost increases the difficulty of prediction. Less efforts and higher accuracy are the objects pursued by related researchers. In this paper, the Cost Significant theorem is applied to simplify computing and the chaotic neural network is used to improve accuracy. The prediction model is rooted from the nonlinear dynamic chaotic system theory and two techniques employed are phase space reconstruction and chaotic neural network construction. The experiment results indicate that the model is suitable for estimating short-term engineering investment and the prediction accuracy is improved.

Tool Life Prediction Model Based on GA-BP Neural Network

2016 ◽  
Vol 836-837 ◽  
pp. 256-262 ◽  
Author(s):  
Zheng Zhang ◽  
Liang Li ◽  
Wei Zhao
Keyword(s):  
Neural Network ◽  
Prediction Model ◽  
Tool Life ◽  
Bp Neural Network ◽  
Life Prediction ◽  
Affecting Factors ◽  
Tool Selection ◽  
Model Based ◽  
Bp Model ◽  
Life Prediction Model

In order to improve the working efficiency of a manufacturing system, tool life estimation is very essential. In this paper, the dominant factors affecting tool life are analyzed by theoretical analysis. According to the nonlinear relationship between affecting factors and tool life, a tool life prediction model based on BP neural network, which is optimized by genetic algorithm (GA), is built up. 15 network patterns are trained to get the best network structure. The accuracy of GA-BP model is verified through computing and compared with the standard BP model. The results show that GA-BP model prediction value is exactly closed to the expected value of tool life and the prediction accuracy can be improved more than 5% compared than the standard BP model. The model is proved to be accuracy and it can be used as an effective method of tool selection decision.

scholarly journals Life Prediction Model of Mineral Admixture Cement Based-Materials under Early Age CO2-Erosion

Coatings ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 413
Author(s):  
Saisai Wang ◽  
Jian Chen ◽  
Xiaodong Wen
Keyword(s):  
Prediction Model ◽  
Life Prediction ◽  
Experimental Tests ◽  
Mineral Admixture ◽  
Model Parameters ◽  
Influence Coefficient ◽  
Test Pieces ◽  
Cement Based Materials ◽  
Particle Group ◽  
Life Prediction Model

Most of the existing models of structural life prediction in early carbonized environment are based on accelerated erosion after standard 28 days of cement-based materials, while cement-based materials in actual engineering are often exposed to air too early. These result in large predictions of the life expectancy of mineral-admixture cement-based materials under early CO2-erosion and affecting the safe use of structures. To this end, different types of mineral doped cement-based material test pieces are formed, and early CO2-erosion experimental tests are carried out. On the basis of the analysis of the existing model, the influence coefficient of CO2-erosion of the mineral admixture Km is introduced, the relevant function is given, and the life prediction model of the mineral admixture cement-based material under the early CO2-erosion is established and the model parameters are determined by using the particle group algorithm (PSO). It has good engineering applicability and guiding significance.

scholarly journals Prediction Model of Weekly Retail Price for Eggs Based on Chaotic Neural Network

2013 ◽  
Vol 12 (12) ◽  
pp. 2292-2299 ◽  
Author(s):  
Zhe-min LI ◽  
Li-guo CUI ◽  
Shi-wei XU ◽  
Ling-yun WENG ◽  
Xiao-xia DONG ◽  
...  
Keyword(s):  
Neural Network ◽  
Prediction Model ◽  
Retail Price ◽  
Chaotic Neural Network

The construction of the life prediction model of 1N and 4N monopropellant thrusters

2013 ◽  
Author(s):  
Go Fujii ◽  
Daisuke Goto ◽  
Hideshi Kagawa ◽  
Shingo Murayama ◽  
Kenichi Kajiwara ◽  
...  
Keyword(s):  
Prediction Model ◽  
Life Prediction ◽  
Life Prediction Model
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