首页|An SVM-Based Prediction Method for Solving SAT Problems
An SVM-Based Prediction Method for Solving SAT Problems
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万方数据
维普
We show how Support vector machines (SVM) can be applied to the Satisfiability (SAT) problem and how their prediction results can be naturally applied to both incomplete and complete SAT solvers. SVM is used for the classification of the variables in the SAT problem and the classification results are the assignment of the variables. And we also present empirical results of applying SVM to instances of the SAT problem from the Center for Discrete Mathematics and Theoretical Computer Science (DIMACS) archive and compare them against the results of other incomplete and complete algorithms for the SAT problem.
Support vector machinesSatisfiabilityComplete algorithmsIncomplete algorithms
HUANG Shaobin、LI Ya、LI Yanmei
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College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China
Manuscript Received June 12,2016;Accepted Feb.13,2017
NETL
NSTL
万方数据
维普
