Ontology Models in Intelligent System Engineering: A Case of the Knowledge-Intensive Application Domain

2019 ◽  
pp. 127-139
Author(s):  
Karina A. Gulyaeva ◽  
Irina L. Artemieva
Keyword(s):  
Intelligent System ◽  
System Engineering ◽  
Application Domain ◽  
Knowledge Intensive

The Application of Software Engineering in Intelligent System Validating

2012 ◽  
Vol 442 ◽  
pp. 418-423
Author(s):  
Gui Liang Feng ◽  
Wei Dong Liu ◽  
Shu Hong Wang
Keyword(s):  
Software Engineering ◽  
Systems Engineering ◽  
Software Design ◽  
Intelligent System ◽  
System Engineering ◽  
System Software ◽  
Engineering Software ◽  
Functional Attributes ◽  
Close Relationship ◽  
Significant Factors

As that of coordination and ISO 15288, discipline system engineering and software engineering processes, methods have a lot in common, and concerns. In most of the system software interest, now offers an important function, more and more is the most significant factors determine the non-functional attributes. In the implementation of the system collection and failure are often attributed to the system and/or software engineering recovery. Need to use systems engineering software design and development, and need to incorporate software engineering concepts into system engineering, suggests that the decision of the two disciplines the close relationship between is appropriate. This article describes a definite theory integrating the two disciplines, defines a framework on establishing a vocabulary integration, and gives the use of this framework preliminary results to describe the system and software integration of defense plans.

Combined Application of Emotional Engineering and System Engineering in the Development of a New Motorcycle Paradigm for 2020

2007 ◽  
Author(s):  
Bastiaan van der Meer ◽  
Imre Horva´th ◽  
Wilhelm van der Vegte ◽  
Hiroshi Ohta
Keyword(s):  
Methodological Approach ◽  
New Product ◽  
System Engineering ◽  
New Paradigm ◽  
Product Concept ◽  
Prototype Development ◽  
Combined Application ◽  
Complex Approach ◽  
Knowledge Intensive ◽  
And Control

This paper reports on a complex approach to including emotional engineering and system engineering in the development of a concept of a future product. The concrete problem was to develop a new product paradigm and a feasible concept of a branded motorcycle for 2020. The new product paradigm has been developed by considering some trend-setter new developments in the field of driving, moving, and control systems for motorcycles. Emotional engineering was used to include the opinion of the potential users in the formation of the new paradigm and to provide the users with comfort, pleasure, and emotional sensations. System engineering made it possible to find realistic solution elements for the implementation, and to develop a feasible product concept based on this paradigm that fulfils the functional, utility, and emotional expectations of the users. The information and knowledge intensive sub-processes of emotional and system engineering have been supported by design inclusive research. This methodological approach included the evolving product paradigm, and its various representations and prototypes as a research means. Design inclusive research consisted of an exploration research part, a concept and prototype development part, and a confirmative research part. Using this framing methodology, designers can get a better idea of what preferences their target groups have and understand what can be successful on the market. The results achieved are being used as input for further strategic investigation by the concerned companies.

scholarly journals Fault diagnosis under uncertain situations within a Bayesian knowledge-intensive CBR system

2021 ◽  
Author(s):  
Hoda Nikpour ◽  
Agnar Aamodt
Keyword(s):  
Fault Diagnosis ◽  
Domain Knowledge ◽  
Semantic Networks ◽  
Efficient Solutions ◽  
Case Based Reasoning ◽  
Oil Well ◽  
Application Domain ◽  
Well Drilling ◽  
Knowledge Intensive ◽  
Case Based

AbstractThis paper presents fault diagnosis and problem solving under uncertainty by a Bayesian supported knowledge-intensive case-based reasoning (CBR) system called BNCreek. In this system, the main goal is to diagnose the causal failures behind the symptoms in complex and uncertain domains. The system’s architecture is described in three aspects: the general, structural, and functional architectures. The domain knowledge is represented by formally defined methods. An integration of semantic networks, Bayesian networks, and CBR is employed to deal with the domain uncertainty. An experiment is conducted from the oil well drilling domain, which is a complex and uncertain area as an application domain. The system is evaluated against the expert estimations to find the most efficient solutions for the problems. The obtained results reveal the capability of the system in diagnosing causal failures.

scholarly journals Research on Green Energy Saving ECO Intelligent System Engineering Cycle

2020 ◽  
Vol 555 ◽  
pp. 012076
Author(s):  
Jue-Jia Chen ◽  
Shinn-Dar Wu ◽  
Dong-Yan Chen ◽  
Jie Li ◽  
Ta-Wei Huang
Keyword(s):  
Energy Saving ◽  
Intelligent System ◽  
System Engineering ◽  
Green Energy

Ontology Enabling Information and Knowledge Modeling for Product Design

2014 ◽  
Vol 945-949 ◽  
pp. 446-449
Author(s):  
Ai Min Li ◽  
Fa Rong Kou ◽  
Qin Yu Niu ◽  
Hai Bo Tian
Keyword(s):  
Product Design ◽  
Intelligent System ◽  
Design System ◽  
Design Knowledge ◽  
Knowledge Modeling ◽  
Knowledge Repositories ◽  
Traditional Design ◽  
Product Function ◽  
Knowledge Intensive ◽  
Framework System

Product design and development becomes increasingly knowledge-intensive and collaborative. It is very difficult to meet currently imperious needs for the traditional design mode, knowledge managing methods and the geometry-centric application tool. Designers require more generic knowledge of design and design process and more intelligent system. It establishes the FBPSS framework system supporting modeling of product function, behavior, principle, state and structure. Based on this FBPSS framework system, ontology-based product design system is developed through design knowledge repositories.

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