System of systems engineering(So SE) involves the complex procedure of translating capability needs into the high-level requirements for system of systems(So S) and evaluating how the SoS quality requirements meet the...System of systems engineering(So SE) involves the complex procedure of translating capability needs into the high-level requirements for system of systems(So S) and evaluating how the SoS quality requirements meet their capability needs. One of the key issues is to model the So S requirements and automate the verification procedure. To solve the problem of modeling and verification, meta-models are proposed to refine both functional and non-functional characteristics of the So S requirements. A domain-specific modeling language is defined by extending Unified Modeling Language(UML) class and association with fuzzy constructs to model the vague and uncertain concepts of the SoS quality requirements. The efficiency evaluation function of the cloud model is introduced to evaluate the efficiency of the SoS quality requirements. Then a concise algorithm transforms the fuzzy UML models into the description logic(DL) ontology so that the verification can be automated with a DL reasoner. This method implements modeling and verification of high-level So S quality requirements. A crisp case is used to facilitate and demonstrate the correctness and feasibility of this method.展开更多
Description logics （DLs） are widely employed in recent semantic web application systems. However, classical description logics are limited when dealing with imprecise concepts and roles, thus providing the motivatio...Description logics （DLs） are widely employed in recent semantic web application systems. However, classical description logics are limited when dealing with imprecise concepts and roles, thus providing the motivation for this work. In this paper, we present a type-2 fuzzy attributive concept language with complements （ALC） and provide its knowledge representation and reasoning algorithms. We also propose type-2 fuzzy web ontology language （OWL） to build a fuzzy ontology based on type- 2 fuzzy ALC and analyze the soundness, completeness, and complexity of the reasoning algorithms. Compared to type-1 fuzzy ALC, type-2 fuzzy ALC can describe imprecise knowledge more meticulously by using the membership degree interval. We implement a semantic search engine based on type-2 fuzzy ALC and carry out experiments on real data to test its performance. The results show that the type-2 fuzzy ALC can improve the precision and increase the number of relevant hits for imprecise information searches.展开更多
基金Project supported by the National Natural Science Foundation of China(No.61273210)
文摘System of systems engineering(So SE) involves the complex procedure of translating capability needs into the high-level requirements for system of systems(So S) and evaluating how the SoS quality requirements meet their capability needs. One of the key issues is to model the So S requirements and automate the verification procedure. To solve the problem of modeling and verification, meta-models are proposed to refine both functional and non-functional characteristics of the So S requirements. A domain-specific modeling language is defined by extending Unified Modeling Language(UML) class and association with fuzzy constructs to model the vague and uncertain concepts of the SoS quality requirements. The efficiency evaluation function of the cloud model is introduced to evaluate the efficiency of the SoS quality requirements. Then a concise algorithm transforms the fuzzy UML models into the description logic(DL) ontology so that the verification can be automated with a DL reasoner. This method implements modeling and verification of high-level So S quality requirements. A crisp case is used to facilitate and demonstrate the correctness and feasibility of this method.
基金Acknowledgements This work was supported by the National Natural Science Foundation of China （Grant Nos. 60873225, 60873083, and 70771043）, the National High Technology Research and Development Program of China （2007AA01Z403）, the Natural Science Foundation of Hubei Province （2009CDB298）, the Natural Science Foundation of Hubei Province for Distinguished Young Scholars （2008CDB351）, the Wuhan Youth Science and Technology Chenguang Program （200950431171）, the Open Foundation of State Key Laboratory of Software Engineering （SKLSE20080718）, the Innovation Fund of Huazhong University of Science and Technology （2010MS068, Q2009021）.
文摘Description logics （DLs） are widely employed in recent semantic web application systems. However, classical description logics are limited when dealing with imprecise concepts and roles, thus providing the motivation for this work. In this paper, we present a type-2 fuzzy attributive concept language with complements （ALC） and provide its knowledge representation and reasoning algorithms. We also propose type-2 fuzzy web ontology language （OWL） to build a fuzzy ontology based on type- 2 fuzzy ALC and analyze the soundness, completeness, and complexity of the reasoning algorithms. Compared to type-1 fuzzy ALC, type-2 fuzzy ALC can describe imprecise knowledge more meticulously by using the membership degree interval. We implement a semantic search engine based on type-2 fuzzy ALC and carry out experiments on real data to test its performance. The results show that the type-2 fuzzy ALC can improve the precision and increase the number of relevant hits for imprecise information searches.
