Intelligent Decision Model Based on Optimized Simulated Annealing Algorithm

DOI

10.2991/icsma-16.2016.135How to use a DOI?

Keywords

decision-theoretic; rough set model; simulated annealing algorithm;cost function

Abstract

Rough set theory can be applied to rule induction.The rough set theory approximates a concept by three regions, namely, the positive,boundary and negative regions.Because of making decision by rough set constructing model, cost of the decision should be considered, we will propose an optimized simulated annealing algorithm(OSAA),which is an optimized algorithm for a minimum cost attribute reduction. A heuristic approach combined with the coarse-grained parallel algorithm are proposed to solve the problem of optimization DTRS.Experiments designed for the optimization simulated annealing algorithm and adaptive learning method are in comparing with the running time and decision-making cost. The optimization representation can bring some new insights into the research on decision-theoretic rough set model.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Hui Xia
PY  - 2016/12
DA  - 2016/12
TI  - Intelligent Decision Model Based on Optimized Simulated Annealing Algorithm
BT  - Proceedings of the 2016 4th International Conference on Sensors, Mechatronics and Automation (ICSMA 2016)
PB  - Atlantis Press
SP  - 776
EP  - 779
SN  - 1951-6851
UR  - https://doi.org/10.2991/icsma-16.2016.135
DO  - 10.2991/icsma-16.2016.135
ID  - Xia2016/12
ER  -