Paper Title:
Research on Transition State of Battlefield Situation Based on Rough Sets Bayesian Net
  Abstract

To solve the problem of lacking of inferential evidence which exists in state transition of battlefield situation of Bayesian net, the methodology of state transition of battlefield situation based on rough sets and Bayesian net is proposed. Furthermore, the method of getting causal intensity based on decision table to calculate the confidence degree of corresponding battlefield situation node is researched, and the confidence degree is modified by non-redundant attribute value. Finally, the state transition of battlefield situation based on Bayesian net inference is discussed in detail. And a case study of anti-air operation is given to verify the correctness and validity of the proposed method.

  Info
Periodical
Advanced Materials Research (Volumes 271-273)
Edited by
Junqiao Xiong
Pages
501-506
DOI
10.4028/www.scientific.net/AMR.271-273.501
Citation
Z. Ding, Q. D. Zheng, "Research on Transition State of Battlefield Situation Based on Rough Sets Bayesian Net", Advanced Materials Research, Vols. 271-273, pp. 501-506, 2011
Online since
July 2011
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: San Tong Zhang
Abstract:A method for solving the fault diagnosis problem of air brake system based on probabilistic approach is presented. The fault diagnosis model...
629
Authors: Zhao Wei Wang, Jian Zhou
Abstract:Aiming at the difficulty of Bayses Network construction, the C_BN (Bayesian networks for quality problem case) decomposition path and level...
678
Authors: Yan Feng Tang, Hui Juan Feng, Sen Wang
Chapter 8: System Modeling and Simulation
Abstract:With the development of science and technology, the quality of the product is better and better. Consequently, in the time-ended life tests,...
4747
Authors: Cui Fang Zheng, Long Jiang, Li Qing Jiang, Zhi Jie Wu
Chapter 5: Information Processing and Computational Science
Abstract:Data mining techniques give us a feasible method to deal with great amount of data, which is generated during the software developing. Many...
738
Authors: Yan Feng Zhang, Ting Ting Li
Chapter 3: Data Acquisition and Data Processing, Computational Techniques
Abstract:C4.5, Bayesian network and Sequential Minimal Optimization (SMO) are three typical classification algorithms in data mining. Using...
963