In emergency decision making, it can be difficult for decision-makers (DMs) to identify all possible scenarios due to a lack of information and the evolution of emergency situations. Therefore, this paper presents an ...
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In emergency decision making, it can be difficult for decision-makers (DMs) to identify all possible scenarios due to a lack of information and the evolution of emergency situations. Therefore, this paper presents an incomplete probabilistic linguistic term set (InPLTS), which is a generalized hesitant fuzzy linguistic term set (HFLTS). The InPLTS can more appropriately describe a case in which a DM considers several possible linguistic terms with uncertain probabilities. Furthermore, this work extends the InPLTS to an incomplete probabilistic linguistic preference relation (InPLPR) and proposes a complete algorithm based on an emergency fault tree analysis (EFTA) to estimate missing entries of the InPLPR. The work also investigates the expected consistency, acceptable expected consistency, and consistency-improving methods for the reasonable application of the InPLPR. Then, a consistency-based emergency decision-making method using the InPLPR is proposed to address issues related to a lack of information, uncertainties and dynamic trends. In using this method, DMs can evaluate emergency alternatives of different possible scenarios with the InPLPR, and the impacts of different emergency responses on the evolution of emergencies can also be considered. Finally, the InPLPRs and the abovementioned method are applied to a public health emergency decision-making process to illustrate the advantages of the proposed method. (C) 2019 Elsevier B.V. All rights reserved.
A complete algorithm for attribute reduction in rough set theory based on discernibility matrix was introduced. This algorithm was composed of algorithm1 and algorithm2. algorithm1 is to select those important conditi...
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ISBN:
(纸本)9781424445189
A complete algorithm for attribute reduction in rough set theory based on discernibility matrix was introduced. This algorithm was composed of algorithm1 and algorithm2. algorithm1 is to select those important condition attributes based on attribute frequency function in every iteration. algorithm2 removes redundancy and incompatibility attributes in R found out by algorithm1. The time complexity of the algorithms in the worst case was analyzed and the proof of its completeness was given. algorithm1 and algorithm2 guarantee that the reduction is probable a smallest or smaller one.
The dynamic taint analysis mechanism is used to protect sensitive data in the Android system. But this technique does not detect control flows which can cause an under-tainting problem. This means that some values sho...
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ISBN:
(纸本)9781479932115
The dynamic taint analysis mechanism is used to protect sensitive data in the Android system. But this technique does not detect control flows which can cause an under-tainting problem. This means that some values should be marked as tainted, but are not. The under-tainting problem can be the cause of a failure to detect a leak of sensitive information. To solve this problem, we use a set of formally defined rules that describes the taint propagation. We prove the completeness of these rules. Also, we provide a correct and complete algorithm based on these rules to solve the under-tainting problem.
A complete algorithm for attribute reduction in rough set theory based on discernibility matrix was introduced. This algorithm was composed of algorithm1 and ***1 is to select those important condition attributes base...
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A complete algorithm for attribute reduction in rough set theory based on discernibility matrix was introduced. This algorithm was composed of algorithm1 and ***1 is to select those important condition attributes based on attribute frequency function in every iteration. algorithm2 removes redundancy and incompatibility attributes in R found out by *** time complexity of the algorithms in the worst case was analyzed and the proof of its completeness was given. algorithm1 and algorithm2 guarantee that the reduction is probable a smallest or smaller one.
A complete algorithm for attribute reduction in rough set theory based on discernibility matrix was *** algorithm was composed of algorithm1 and ***1 is to select those important condition attributes based on attribut...
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A complete algorithm for attribute reduction in rough set theory based on discernibility matrix was *** algorithm was composed of algorithm1 and ***1 is to select those important condition attributes based on attribute frequency function in every ***2 removes redundancy and incompatibility attributes in R found out by *** time complexity of the algorithms in the worst case was analyzed and the proof of its completeness was given,algorithm1 and algorithm2 guarantee that the reduction is probable a smallest or smaller one.
In this paper, we present an algorithm of simple exponential growth called COPOMATRIX for determining the copositivity of a real symmetric matrix. The core of this algorithm is a decomposition theorem, which is used t...
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In this paper, we present an algorithm of simple exponential growth called COPOMATRIX for determining the copositivity of a real symmetric matrix. The core of this algorithm is a decomposition theorem, which is used to deal with simplicial subdivision of (T) over cap (-) = {y is an element of Delta(m)vertical bar beta(T)(y) <= 0} on the standard simplex Delta(m), where each component of the vector beta is -1, 0 or 1. (C) 2011 Elsevier Inc. All rights reserved.
The advantages of complete algorithm and incomplete algorithm of the SAT problem are integrated into an algorithm. First, an approximation solution is obtained by an incomplete algorithm, as an initial input of the co...
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The advantages of complete algorithm and incomplete algorithm of the SAT problem are integrated into an algorithm. First, an approximation solution is obtained by an incomplete algorithm, as an initial input of the complete algorithm, which is used to phase decision of branched variable. The algorithm guides the complete algorithm first search the subspace that the approximation solutions lie in, which accelerates the process that the solver find the satisfied solution and provides a new approach for SAT problem. Experimental results show that proposed algorithm improves the decision precision and the efficiency of solver and performs well in many instances.
Minimal attribute reduction plays all important role in both theory and practice, but it has been proved that finding a minimal reduct of a given decision table is a. NP-hard problem. Some scholars have also pointed o...
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ISBN:
(纸本)9783642029615
Minimal attribute reduction plays all important role in both theory and practice, but it has been proved that finding a minimal reduct of a given decision table is a. NP-hard problem. Some scholars have also pointed out that current heuristic algorithms are incomplete for minimal attribute reduction. Based oil the decomposition principles of a discernibility function, a complete algorithm CAMARDF for finding a minimal reduct is put forward in this paper. Since it depends oil logical reasoning, it can be applied for all decision tables after their discernibility functions constructed reasonably. The efficiency of CAMARDF is illustrated by experiments with UCI data sets further.
Boolean satisfiability is a NP-hard problem in computer theoretic science. There are two types of SAT solvers, random local solver and DPLL-based complete solver. Recently, some people have proposed hybrid SAT solvers...
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Boolean satisfiability is a NP-hard problem in computer theoretic science. There are two types of SAT solvers, random local solver and DPLL-based complete solver. Recently, some people have proposed hybrid SAT solvers that combined the advantage of them both. They have successfully applied them to solve large or hard random SAT problems and circuit related problems. However, these solvers often find over-satisfying assignments when solving some circuit related problems. In this paper, circuit observability is considered in hybrid SAT solver, which helps reduce the overhead caused by over-satisfying and prune the searching space. The experimental results show that our hybrid SAT solver is more efficient than other solvers for large and hard circuits.
This paper presents a heuristic polarity decision-making algorithm for solving Boolean satisfiability （SAT）. The algorithm inherits many features of the current state-of-the-art SAT solvers, such as fast BCP, clause...
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This paper presents a heuristic polarity decision-making algorithm for solving Boolean satisfiability （SAT）. The algorithm inherits many features of the current state-of-the-art SAT solvers, such as fast BCP, clause recording, restarts, etc. In addition, a preconditioning step that calculates the polarities of variables according to the cover distribution of Karnaugh map is introduced into DPLL procedure, which greatly reduces the number of conflicts in the search process. The proposed approach is implemented as a SAT solver named DiffSat. Experiments show that DiffSat can solve many ＂real-life＂ instances in a reasonable time while the best existing SAT solvers, such as Zchaff and MiniSat, cannot. In particular, DiffSat can solve every instance of Bart benchmark suite in less than 0.03 s while Zchaff and MiniSat fail under a 900 s time limit. Furthermore, DiffSat even outperforms the outstanding incomplete algorithm DLM in some instances.
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