205888828
Non-fuzzy versions of fuzzy reasoning in classical logics
Abstract Fuzzy reasoning features fuzzy logic in its narrow sense, FLn, and fuzzy modus ponens (FMP) is the core of fuzzy reasoning. As is well known, FMP is far more general and complicated than the conventional rule of modus ponens (MP) and takes the latter as special case under certain conditions. This paper proves that there exist non-fuzzy versions of FMP in classical 2-valued logic as well as in conventional multivalued systems and reveals the roots of these seemingly surprising results.
6984424
Ontology-based security assessment for software products
This paper proposes an ontology-based approach to analyzing and assessing the security posture for software products. It provides measurements of trust for a software product based on its security requirements and evidence of assurance, which are retrieved from an ontology built for vulnerability management. Our approach differentiates with the previous work in the following aspects: (1) It is a holistic approach emphasizing that the system assurance cannot be determined or explained by its component assurance alone. Instead, the software system as a whole determines its assurance level. (2) Our approach is based on widely accepted standards such as CVSS, CVE, CWE, CPE, and CAPEC. Our ontology integrated these standards seamlessly thus provides a solid foundation for security assessment. (3) Automated tools have been built to support our approach, delivering the environmental scores for software products.
8066461
Scalability of Hybrid Fuzzy C-Means Algorithm Based on Quantum-Behaved PSO
A new hybrid fuzzy clustering algorithm that incorporates the fuzzy c-means (FCM) into the quantum-behaved particle swarm optimization (QPSO) algorithm is proposed in this paper (QPSO+FCM). The QPSO has less parameters and higher convergent capability of the global optimizing than particle swarm optimization algorithm (PSO). So the iteration algorithm is replaced by the QPSO based on the gradient descent of FCM, which makes the algorithm have a strong global searching capacity and avoids the local minimum problems of FCM and in a large degree avoids depending on the initialization values. This paper also investigates the ability of FCM algorithm, PSO+FCM algorithm and GA+FCM algorithm with Iris testing data and Wine testing data. The simulation result proves that compared with other algorithms, the new algorithm not only has the favorable convergence but also has been obviously improved the clustering effect.
16326025
Research on Positioning Technology of Xinjiang Mobile GIS
In this paper, the characteristics of Xinjiang mobile communication network are analyzed, the results show that for a reliable mobile communication network, BS (base station) and base station control BSC (base station controller) monitoring system, cable and fiber optic cable monitoring system and mobile communications troubleshooting and dispatching system should be built. Combined with GIS, GPS, GSM and geographic database technology, positioning technology for different targets and detection on fault point are studied, the results indicate that precise positioning of static target can accurately locate the failure telecom equipment in the electronic map and provide data source for the realization of real-time monitoring and management system for telecom equipment based on GIS & wireless sensor network technology. GSM-based wireless messaging communications and real-time fast positioning of dynamic target is the key to the emergency repair vehicles monitoring and dispatch system. The proposed fault determination and fault point location method can provide fast accurately fault devices location with detailed geography information and prompt the efficiency of fault management and improve the reliability of telecom network services. The above research results are important basis on the design and implementation of the system.
22165485
An Efficient Fuzzy Kohonen Clustering Network Algorithm
Fuzzy Kohonen clustering networks (FKCN) are well known for clustering analysis (unsupervised learning and self-organizing). This classification of FKCN algorithm is a set of iterative procedures that suffer some major problems, for example its constringency rate is not too fast for a large amount of datasets. To overcome these defects, an efficient fuzzy Kohonen network algorithm is proposed in this paper, which can significantly reduce the computation time required to partition a dataset into desired clusters. By introducing the threshold values and fuzzy convergence operators in the network learning procedure to adjust the learning rates dynamically, the network convergence rate is greatly improved and the error rates of dataset cluster are significantly decreased. Experimental results show the new algorithm is on average three times faster than the original FKCN algorithm. We also demonstrate that the quality of the improved FKCN is better than the original FKCN algorithm.
33243327
Certain Predicates Defined by Induction Schemata
It is known that we can introduce in number theory (for example, the system Z of Hilbert-Bernays) by induction schemata certain predicates of natural numbers which cannot be expressed explicitly within the framework of number theory. The question arises how we can define these predicates in some richer system, without employing induction schemata. In this paper a general notion of definability by induction (relative to number theory), which seems to apply to all the known predicates of this kind, is introduced; and it is proved that in a system L 1 which forms an extension of number theory all predicates which are definable by induction (hereafter to be abbreviated d.i.) according to the definition are explicitly expressible. In order to define such predicates and prove theorems answering to their induction schemata, we have to allow certain impredicative classes in L 1 . However, if we want merely to prove that for each constant number the special case of the induction schema for a predicate d.i. is provable, we do not have to assume the existence of impredicative classes. A certain weaker system L 2 , in which only predicative classes of natural numbers are allowed, is sufficient for the purpose. It is noted that a truth definition for number theory can be obtained in L 2 . Consistency proofs for number theory do not seem to be formalizable in L 2 , although they can, it is observed, be formalized in L 1 . In general, given any ordinary formal system (say Zermelo set theory), it is possible to define by induction schemata, in the same manner as in number theory, certain predicates which are not explicitly definable in the system. Here again, by extending the system in an analogous fashion, these predicates become expressible in the resulting system. The crucial predicate instrumental to obtaining a truth definition for a given system is taken as an example.
16399618
Fast filter-and-refine algorithms for subsequence selection
Large sequence databases, such as protein, DNA and gene sequences in biology, are becoming increasingly common. An important operation on a sequence database is approximate subsequence matching, where all subsequences that are within some distance from a given query string are retrieved. This paper proposes a filter-and-refine algorithm that enables efficient approximate subsequence matching in large DNA sequence databases. It employs a bitmap indexing structure to condense and encode each data sequence into a shorter index sequence. During query processing, the bitmap index is used to filter out most of the irrelevant subsequences, and false positives are removed in the final refinement step. Analytical and experimental studies show that the proposed strategy is capable of reducing response time substantially while incurring only a small space overhead.