Dissertation > Excellent graduate degree dissertation topics show

The Study on the Analysis and Estimated Model of Mining Surface Deformation Based on Chaotic Support Vector Machine Algorithm

Author: WuYongKang
Tutor: LiuWenSheng
School: Liaoning Technical University
Course: Geodesy and Survey Engineering
Keywords: Mining subsidence time series phase space reconstruction Lyapunov index support vector machine
CLC: TD325
Type: Master's thesis
Year: 2011
Downloads: 44
Quote: 0
Read: Download Dissertation

Abstract


If the underground working scope achieves a certain scale, the mining subsidence will affect the scope of the development from the rock mass to the surface, causing ground movement and deformation. The ground movement and deformation can bring a series of primary disasters and secondary disasters. Due to the production and the life of the human are mostly carried out at the surface, so the ground movement and deformation relatively large impact on human. Ground movement and deformation of the system is a complex system, in its constant evolution, it exchanges with the outside material, energy and information, showing a strong non-linear characteristic, so this paper mainly studies on the analysis and the forecast of the gob ground movement and deformation based on the chaos support vector machines algorithm.In this paper, it has summarized and classified the analysis and prediction models, which are the analysis and prediction deterministic models, the analysis and prediction Statistical models and the analysis and prediction Mixed models. It has conducted the research to the model of the gob ground movement and deformation forecast. Then it realized the chaos system’s forecast procedure, mainly includes the delay time the selection, the inserting dimension selection, the chaos characteristic quantity computation, forecast based on the GA-SVR algorithm and forecast based on the biggest Lyapunov index and so on. The procedure is verified by typical Lorenz chaotic system. The confirmation result indicated that the procedure may apply in characteristic distinction and forecast of the other chaos system.Then it has studied the discrimination method of the system chaotic characteristics. System chaotic characteristics determine the geometry usually through a single invariant, this paper combines qualitative and quantitative approach to distinguish chaotic, that qualitative discrimination Methods power spectrum analysis method, quantitative method of identification selected GP and the correlation dimension algorithm small data sets method for calculating the maximum Lyapunov index method. It has applied support vector return algorithm to the ground movement and deformation time series forecast using genetic algorithm to obtain the three parameters of the accuracy of support vector machine model, the average absolute error of support vector machine prediction as fitness function, namely nuclear function type and parameter value, loss function type and parameter value, penalty parameter value. Finally it had applied the model to the project. The forecasting result indicated that comparing to estimate model which based on the biggest Lyapunov exponential method, estimate model which based on the chaos GA-SVR algorithm is more suitable to the small sampled data and it has very good pan-ability.

Related Dissertations

  1. Research on Automatic Detection Algorithm for Substructure Distress of Highway Pavement Based on SVM,U418.6
  2. Research on Autamatic Music Structrue Analysis,TN912.3
  3. Research on Transductive Support Vector Machine and Its Application in Image Retrieval,TP391.41
  4. Fault Diagnosis Method Based on Support Vector Machine,TP18
  5. Process Support Vector Machine and Its Application to Satellite Thermal Equilibrium Temperature Prediction,TP183
  6. Research for Infrared Image Target Identification and Tracking Technology,TP391.41
  7. Study on the Road Condition Monitoring Based on Vehicular 3D Acceleration Sensor,TP274
  8. Crop Evapotranspiration Study on Evolution Rule and Forecast Model in Chaoyang Area,S161.4
  9. Research of Diagnosing Cucumber Diseases Based on Hyperspectral Imaging,S436.421
  10. Research on Whispered Speaker Identification in Channel Mismatch Conditions,TN912.34
  11. Scholar Resume Automatic Generation Based on Text Mining,TP391.1
  12. Research on Intrusion Detection Based on Feature Selection,TP393.08
  13. Based on Data Mining Technologies in Urban Water Supply Analysis and Decision,F299.24;F224
  14. The Research on Intrusion Detection System Based on Machine Learning,TP393.08
  15. The New Privacy Preserving Algorithms for Linear Programming and SVMS,O221.1
  16. Dimensionality Reduction Methods for Gene Expression Data Base on SVM,TP181
  17. Prediction of Binding Affinity of Human Transporter Associated with Antigen Processing,R392.1
  18. Study on Applications of Soft Sensor in Chloromethane Recovery,TQ222.214
  19. Research of Fault Diagnosis Method of Analog Circuit Based on Improved Support Vector Machines,TN710
  20. Time Series PS-InSAR Using Small Data Set and Its Application to Surface Subsidence,P642.26
  21. The Forecast Methods of Mining Risk of the Coal Resources Affected by Dynamic Disaster,TD713

CLC: > Industrial Technology > Mining Engineering > Mine the pressure and support > Rock pressure and rock movement > Rock movement
© 2012 www.DissertationTopic.Net  Mobile