Applying Data Mining and Machine Learning Techniques to Submarine Intelligence Analysis

Proceedings - 3rd International Conference on Knowledge Discovery and Data Mining, KDD 1997

Volumn , Issue , 1997, Pages 127-130

  Bergsten, Ulla ^a   Schubert, Johan ^a   Svensson, Per ^a  

^a SWEDISH DEFENCE RESEARCH AGENCY   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; DATA MINING; GENETIC ALGORITHMS; LEARNING SYSTEMS; UNCERTAINTY ANALYSIS;

DATA ANALYSIS-METHODS; DATABASE TECHNOLOGY; INTELLIGENCE ANALYSIS; INTERESTING INFORMATION; MACHINE LEARNING TECHNIQUES; SWEDISHS;

SUBMARINES;

EID: 85056517374     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (9)

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3. Andersson, G. 1992. User's Guide to CANTOR. Part II: Graphical Output, Technical Report C 20865-2.7, Försvarets forskningsanstalt, Stockholm.
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5. Schubert, J. 1993. On Nonspecific Evidence. International Journal of Intelligent Systems 8(6):711-725.
6. Bergsten, U.; and Schubert, J. 1993. Dempster's Rule for Evidence Ordered in a Complete Directed Acyclic Graph, International Journal of Approximate Reasoning 9(1):37-73.
7. Shafer, G. 1976. A Mathematical Theory of Evidence. Princeton, N.J.: Princeton University Press.
8. Schubert, J. 1995. Finding a Posterior Domain Probability Distribution by Specifying Nonspecific Evidence, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 3(2): 163-185.
9. Schubert, J. 1996. Specifying Nonspecific Evidence, International Journal of Intelligent Systems 11(8):525-563.