Papers by Keyword: Cross Entropy

Paper TitlePage

Authors: Ilanthenral Kandasamy, Florentin Smarandache
Abstract: Double Refined Indeterminacy Neutrosophic Set (DRINS) is an inclusive case of the refined neutrosophic set, defined by Smarandache (2013), which provides the additional possibility to represent with sensitivity and accuracy the uncertain, imprecise, incomplete, and inconsistent information which are available in real world. More precision is provided in handling indeterminacy; by classifying indeterminacy (I) into two, based on membership; as indeterminacy leaning towards truth membership (IT) and indeterminacy leaning towards false membership (IF). This kind of classification of indeterminacy is not feasible with the existing Single Valued Neutrosophic Set (SVNS), but it is a particular case of the refined neutrosophic set (where each T, I, F can be refined into T1, T2, ...; I1, I2, ...; F1, F2, ...). DRINS is better equipped at dealing indeterminate and inconsistent information, with more accuracy than SVNS, which fuzzy sets and Intuitionistic Fuzzy Sets (IFS) are incapable of. Based on the cross entropy of neutrosophic sets, the cross entropy of DRINSs, known as Double Refined Indeterminacy neutrosophic cross entropy, is proposed in this paper. This proposed cross entropy is used for a multicriteria decision-making problem, where the criteria values for alternatives are considered under a DRINS environment. Similarly, an indeterminacy based cross entropy using DRINS is also proposed. The double valued neutrosophic weighted cross entropy and indeterminacy based cross entropy between the ideal alternative and an alternative is obtained and utilized to rank the alternatives corresponding to the cross entropy values. The most desirable one(s) in decision making process is selected. An illustrative example is provided to demonstrate the application of the proposed method. A brief comparison of the proposed method with the existing methods is carried out.
129
Authors: Yi Zhang, Gang Wang, Ping Rong Lin
Abstract: With the scale and complexity of software increasing, people's awareness of software quality assurance has gradually strengthened. How to carry out the test, test scheme optimization selection and how to improve the testing efficiency become the reality problems in software engineering. Using the test coverage of the multidimensional metric, the effectiveness of comprehensive test coverage, test coverage rate of satisfaction and test efficiency as the optimization test scheme selection, use of multiple attribute decision making lifting scheme selection algorithm to measure the optimal test program, ameliorate the severity of the past subjective experience dependent, so as to provide guidance for reasonable, effective and scientific test. The optimization of comprehensive test coverage scheme is applied to the Markov model of software testing; software testing with the average cost minimization as objective, using the cross entropy method the optimal coverage testing section to optimize the test process.
1336
Showing 1 to 2 of 2 Paper Titles