Dissertation > Excellent graduate degree dissertation topics show

Researches on the Method of RBF Networks and SVR Modeling Based on Spatial Adjacency

Author: FuXiaoNing
Tutor: ZhaoYongJun
School: China University of Petroleum
Course: Cartography and Geographic Information Engineering
Keywords: RBF network Support Vector Regression Spatial information analysis Information Fusion
CLC: TP183
Type: Master's thesis
Year: 2008
Downloads: 52
Quote: 0
Read: Download Dissertation

Abstract


With the constant improvement of the various means of access to information , spatial information analysis facing increasingly complex objects, and vast amounts of information , some of the traditional means of spatial analysis can not meet the GIS and Geo-Information Science mass information processing requirements , which makes artificial neural networks, support vector machines and other intelligent computing technology to its full use of the advantages of computer intelligence to play an increasingly important role in research in the field of Earth Sciences . Integrated spatial information analysis , the intelligent computing different theoretical approaches such as all kinds of information fusion technology trends is irreversible . This paper, spatial information analysis and intelligent calculation technology mutual integration as a starting point , based on the relationship between space and space knowledge , the use of traditional RBF network and SVR basic principle and algorithm , according to the features of spatial data , the RBF network based on spatial adjacency relationship with SVR Construction modeling methods , mainly the following results : (1 ) the establishment of a variety of a variety of intelligent model based on the adjacency relationship the RBF - IF , RBF - HF1 / 2 , RBF -OF and LS - SVR -IF , LS - SVR - HF1 / 2 , LS - SVR -OF model , and the crime rate of the 49 regions of the District of Columbia , Ohio , United States to analyze an example ; (2 ) through repeated comparison analysis, the application of a variety of predicted Performance results evaluation of the mutual integration of spatial information analysis and intelligent computing technology is feasible ; (3) through the comparative analysis of the traditional RBF network with traditional SVR model and RBF - HF1 and LS - SVR - HF1 model proved SVR generalization RBF network has certain advantages relative to ability ; (4) paper in the SVR model applied least squares support vector regression model to simplify the learning algorithm , mentioning the RBF - HF1 high learning speed . Finally, based on the adjacency relationship between RBF network and SVR modeling as the main object , object-oriented programming , Visual C environment , combined with the powerful scientific computing and visualization capabilities of MATLAB software , the preparation of the RBF network based on the adjacency relationship and SVR modeling method module , and use it for example , to achieve the desired effect .

Related Dissertations

  1. Tongue Feature Extraction and Research of Fusion Classification,TP391.41
  2. Multi-Sensor Information Fusion and Its Applications on Wearable Computer,TP202
  3. Research on NO-reference Image Quality Assessment Based on HVS,TP391.41
  4. Study on the Technique of Information Fusionapplied to Enbedded Driver Fatigue Detection,TP368.12
  5. Based on Neural Network Model of Hot-rolling,TP183
  6. Application of Rough Set and Flex in Mid-long Term Runoff Forecasting,P338
  7. Research and Implementation of the Key Technologies for Multimeida Sensor Terminal,TP212.9
  8. Cooperative Optimization Scheduling with Application to Multi-Reservoir System During Non-Flood Period,TV697.11
  9. Research on Wide Area Backup Protection Based on Centralized Decision-making,TM774
  10. Underwater Manipulator information fusion and operations planning studies,TP241
  11. Intelligent algorithms based carbon fiber spinning process monitoring and optimization,TQ342.742
  12. Based on information fusion safety assessment of genetically modified foods,TS201.6
  13. Support Vector Regression in chemical pesticides QSAR Application,S48
  14. Information Fusion Based on Multi- wheeled mobile robot navigation technology,TP242
  15. Based on Bayesian Networks motor fault diagnosis method,TM307.1
  16. For the manufacture of non-standard working hours fixed Research,F425
  17. Multiscale information fusion algorithm,TP202
  18. Based on Information Fusion Fault Diagnosis of Analog Circuits,TN710
  19. Multi-sensor Information Fusion Methods for Integrated Identification of Friend or Foe Based on Evidential Networks,TP202
  20. Study on Freeway Automatic Incident Detection Algorithm Based on Information Fusion,U491
  21. Applied Research of Multi-sensor Information Fusion Technology in the Virtual Chinese Medicine Bone-setting Manipulation,R274

CLC: > Industrial Technology > Automation technology,computer technology > Automated basic theory > Artificial intelligence theory > Artificial Neural Networks and Computing
© 2012 www.DissertationTopic.Net  Mobile