Sea-Battlefield Situation Assessment Based on Improved Decision Tree

Yong Tao Yu; Ying Ding

doi:10.4028/www.scientific.net/AMM.574.639

Paper Titles

Effect of Axial Grooves on Eddy Current Loss within Giant Magnetostrictive Material (GMM) Rod
p.615

Airport Taxiway Head-On Conflict Prediction and Avoidance in A-SMGCS
p.621

The Modification of Digital Current Following Control Approach of Buck DC-DC Converter
p.628

Research on the Designing and Checking Method for Electric Actuator Used on Supersonic Speed Target Cruise Missile
p.633

Sea-Battlefield Situation Assessment Based on Improved Decision Tree
p.639

Embedded Software Formalization Testing Method and its Application in Missile-Borne Software
p.646

A Method of Rendezvous and Docking Based on the 6-DOF Parallel Mechanism in Subsea Environment
p.651

A Method for Computing Logarithms of K-Circulant Matrices
p.661

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 574Sea-Battlefield Situation Assessment Based on...

Sea-Battlefield Situation Assessment Based on Improved Decision Tree

Abstract:

How to efficiently evaluate the dynamic changing sea-battlefield is the key of command decision. According to research sea-battlefield situation assessment based on improved decision tree algorithm based on derived attributes. First is based on the decision tree algorithm to establish the sea-battlefield situation assessment initial decision tree. Second are dynamically generated derivative branches set based on derived attributes. Once again, it can be grafting and pruning derivative branches to form the sea-battlefield situation assessment derived decision tree model. Finally, it may use a derived dynamically decision tree model assess sea-battlefield in different time slices.

You might also be interested in these eBooks

Recent Research on Mechanical Engineering, Mechatronics and Automation

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volume 574)

Pages:

639-645

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.574.639

Citation:

Cite this paper

Online since:

July 2014

Authors:

Yong Tao Yu*, Ying Ding

Keywords:

Decision Tree Algorithm, Sea-Battlefield, Situation Assessment

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] Marvin S Cohen, Bryan B Thompson, Leonard Adelman. , et al. training critical thinking for the battlefield volume 1: basis in cognitive theory and research [M]. Now York: Cognitive Technologies, (2000).

Google Scholar

[2] HINMAN M L. Some computational approaches for situation assessment and impact assessment[C]/Proceedings of the 5th International Conference on Information Fusion. New York, USA, 2002: 687-693.

DOI: 10.1109/icif.2002.1021221

Google Scholar

[3] Zkim Le. Fuzzy relation compositions and pattern recognitions. Inf Sci, 1996, 89: 107-130.

Google Scholar

[4] Saaty T L. The analysis hierarchy process [J]. Management Science, 1986, 32(7), 15-19.

Google Scholar

[5] Fried M A, Brodeley C E. Decision Tree Classification of Land Cover from Remotely Sensed Data [J]. Remote Sens. Environ, 1997, 61: 399-409.

DOI: 10.1016/s0034-4257(97)00049-7

Google Scholar

[6] Wei Fan, E. Greengrass, J. McCloskey, et al. Effective estimation of posterior probabilities: Explaining the accuracy of randomized decision tree approaches[C], In Fifth IEEE International Conference on Data Mining, 2005. IEEE, pages 154–161.

DOI: 10.1109/icdm.2005.54

Google Scholar

[7] Quinlan J R Inductìón of decision trees [J]. Machine Learning. 1986, l (l): 81–106.

Google Scholar

[8] Murthy S K. Kasif S, Salzberg S. A system for induction of oblique decision trees.

Google Scholar

[1] Journal of Artificial Intelligence Research, 1994. 2: 1-32.

Google Scholar