Dissertation > Excellent graduate degree dissertation topics show

Based on the RBFNN coal and gas outburst prediction research

Author: HeZhenWu
Tutor: ChenLiChao
School: Taiyuan University of Science and Technology
Course: Applied Computer Technology
Keywords: Coal and gas outburst Prediction of outburst RBFNN Clustering analysis Grey relational analysis
CLC: TD713
Type: Master's thesis
Year: 2011
Downloads: 35
Quote: 0
Read: Download Dissertation

Abstract


Coal and gas outburst is a complex dynamic phenomenon in the underground coal mine. Coal and gas outburst disaster not only caused heavy casualties, but also damaged the mine very severely, is recognized as a serious threat to mine’s safety and production of a natural disaster. Currently, coal and gas outburst is still the world’s major coal-producing countries solved the problems, and the realization of coal and gas outburst forecast quickly and accurately is an urgent requirement for safety in coal mines. Now there are many coal and gas outburst prediction methods at home and abroad, but mostly used by a single factor. However, the occurrence of coal and gas outburst mechanism is extremely complex, and has many affecting factors which are mostly in a complex nonlinear state. And so far the study has not yet been reached consensus. In recent years, many researchers try to use artificial neural network model to predict coal and gas outburst. Due to the defects and deficiencies in its structure, the predicted effects and results are not very satisfactory.The current prediction models mostly built by BPNN have some disadvantages. In view of the problems existing in the prediction models of coal and gas outburst based on BPNN, and in order to get a fast convergence and more accurate prediction before the outburst accidents, the RBFNN model is built to predict it. The kernel k-means clustering algorithm, which is universal for the samples, is used to determine the central value of the basis function. Its width and its weight are optimized and adjusted by the gradient descent adaptive algorithm and the recursive least square algorithm respectively. And then, the hybrid algorithm and the model are verified with the measured data of coal and gas outburst in China. The simulation results show that the method in the paper has better forecasting accuracy and superior convergence rate than the BPNN and the improved RBFNN based on the classical k-means clustering algorithm, and indicate the practicability and the efficiency of the new model. Then, the each affecting factor’s correlation is calculated by the grey relational analysis model in this paper, and use the correlation as the old predicting model’s input weights. Finally, the new simulation results show that the input-weighted model has higher prediction accuracy, better classification ability and more representation, and provides a good theoretical support for the prediction study on the coal and gas outburst.

Related Dissertations

  1. Research on Peer-to-Peer Traffic Identification Algorithm Based on Cluster Analysis,TP393.02
  2. Evaluation of Photosynthetic Efficiancy of Seedlings of the Hybrid Progenies （F1） in Peach,S662.1
  3. The Load Research and Comprehensive Evaluation on the Agricultural Non-Point Source Pollution in Nantong,X592
  4. Analysis of Attributes of Quality and Soil Factors on Style of Fen-flavor Flue-cured Tobacco in Qujing District,S572
  5. Study on Photosynthetic Characteristics of Peach Based on Heterosis of Assimilation Capacity,S662.1
  6. Shao River Basin agricultural non-point source water pollutants total allocation expert system,X52
  7. Automotive Manufacturing Corporate Social Responsibility Financial Evaluation of Gray,F426.471
  8. The Study of Monitoring and Control Technologies of Blasting Vibration in Urban Shallow Large-Span Tunnel,U455.6
  9. The Dynamic Response Analysis of Cement Concrete Pavement with Function Layer,U416.216
  10. Optimizing and Setting the Post Based on Business Process Strategic Transformation of Port Logistics Company,F259.27;F224
  11. The Research on Medication Laws of Arthralgia Syndrome in Medicalcase Prescription Based on Clustering Analysis and Association Rules,R255.6
  12. MATLAB-based Groundwater Environmental Quality Evaluation,X824
  13. The Analysis of the Influence of Industrial Structure on Environment Quality in "Chang-Zhu-Tan" Group,X321;F224
  14. Research on Gas Occurrence and Emission of Sanjiazi Coal Mine,TD712
  15. Based on BP neural network , coal and gas outburst risk prediction,TD713
  16. Research on the Sensitive Index and Critical Value about Prediction of Coal and Gas Outburst in Daning Coal,TD713
  17. Coal and gas outburst after the catastrophic damage and failure,TD713
  18. Evaluation of Independent-Sales B2C Fashion Website Usability Based on Customer’s Perspective,F724.6
  19. Yunnan Copper Titanium implementation of circular economy in the process of production safety impact analysis,F426.32
  20. Hebei Ecological Garden City Evaluation System and Applied Research,TU986
  21. Fuzzy Comprehensive Evaluation of Safety of Vehicle Operation Based on Grey Relative Analysis,U491.31

CLC: > Industrial Technology > Mining Engineering > Mine safety and labor protection > Mine atmosphere > Coal (rock) and gas outburst prevention and treatment
© 2012 www.DissertationTopic.Net  Mobile