19 resultados para research of science
Resumo:
Design of liquid retaining structures involves many decisions to be made by the designer based on rules of thumb, heuristics, judgment, code of practice and previous experience. Various design parameters to be chosen include configuration, material, loading, etc. A novice engineer may face many difficulties in the design process. Recent developments in artificial intelligence and emerging field of knowledge-based system (KBS) have made widespread applications in different fields. However, no attempt has been made to apply this intelligent system to the design of liquid retaining structures. The objective of this study is, thus, to develop a KBS that has the ability to assist engineers in the preliminary design of liquid retaining structures. Moreover, it can provide expert advice to the user in selection of design criteria, design parameters and optimum configuration based on minimum cost. The development of a prototype KBS for the design of liquid retaining structures (LIQUID), using blackboard architecture with hybrid knowledge representation techniques including production rule system and object-oriented approach, is presented in this paper. An expert system shell, Visual Rule Studio, is employed to facilitate the development of this prototype system. (C) 2002 Elsevier Science Ltd. All rights reserved.
Resumo:
A soft linguistic evaluation method is proposed for the environmental assessment of physical infrastructure projects based on fuzzy relations. Infrastructure projects are characterized in terms of linguistic expressions of 'performance' with respect to factors or impacts and the 'importance' of those factors/impacts. A simple example is developed to illustrate the method in the context of three road infrastructure projects assessed against five factors/impacts. In addition, a means to include hard or crisp factors is presented and illustrated with respect to a sixth factor.
Resumo:
This article presents Monte Carlo techniques for estimating network reliability. For highly reliable networks, techniques based on graph evolution models provide very good performance. However, they are known to have significant simulation cost. An existing hybrid scheme (based on partitioning the time space) is available to speed up the simulations; however, there are difficulties with optimizing the important parameter associated with this scheme. To overcome these difficulties, a new hybrid scheme (based on partitioning the edge set) is proposed in this article. The proposed scheme shows orders of magnitude improvement of performance over the existing techniques in certain classes of network. It also provides reliability bounds with little overhead.
Resumo:
The use of bibliometric data is a means of comparing. research productivity and scholarly. impact for individuals, work groups, institutions and nations within and between disciplines. Central to this debate is the notion that disciplines differ in the ways in which,they exchange ideas and disseminate information and therefore have diverse publishing and citation patterns. In this article we use two different approaches to compiling bibliometric data to compare publishing patterns of five different disciplines that encompass Molecular Biology; Administration/Political Science, Psychology,. Philosophy and Sociology/Anthropology. We find that the social sciences differ from each other as well as from the physical sciences in their publication and citation patterns. Further, while the different ways of organizing the data produce somewhat different results, the substantive findings for the general patterning of publications and citations of disciplines are consistent for both data sets. Sociology/Anthropology, when compared with the other disciplines, shows substantial differences across universities.