Knowledge-based System

"With the development of computing technology, numerical models are often employed to simulate flow and water quality processes in coastal environments. However, the emphasis has conventionally been placed on algorithmic procedures to solve specific problems. These numerical models, being insufficiently user-friendly, lack knowledge transfers in model interpretation. This results in significant constraints on model uses and large gaps between model developers and practitioners. It is a difficult task for novice application users to select an appropriate numerical model. It is desirable to incorporate the existing heuristic knowledge about model manipulation and to furnish intelligent manipulation of calibration parameters. The advancement in artificial intelligence (AI) during the past decade rendered it possible to integrate the technologies into numerical modelling systems in order to bridge the gaps. The objective of this paper is to review the current state-of-the-art of the integration of AI into water quality modelling. Algorithms and methods studied include knowledge-based system, genetic algorithm, artificial neural network, and fuzzy inference system. These techniques can contribute to the integrated model in different aspects and may not be mutually exclusive to one another. Some future directions for further development and their potentials are explored and presented.

Keywords: water quality modelling; artificial intelligence; knowledge-based system; genetic algorithm; artificial neural network; fuzzy inference system"

"It would be greatly helpful to neophytes if knowledge-based system technology incorporating the existing heuristic knowledge about model manipulation can be integrated into the hydrological system. This paper delineates the development and implementation of a prototype knowledge-based system for model manipulation for hydrological processes by employing an expert system shell. The architecture and main components of the system are presented. The prototype system is verified and validated in two real watershed applications. It helps inexperienced users of hydrological models make the right choice of the appropriate model and/or direct the users throughout the calibration process.

Keywords: hydrological models; model manipulation; knowledge-based system"

"The choice of good construction site layout is inherently difficult, yet has a significant impact on both monetary and time saving. It is desirable to encapsulate systematically the heuristic expertise and empirical knowledge into the decision making process by applying the latest artificial intelligence technology. This paper describes a prototype knowledge-based system for the construction site layout, SITELAYOUT. It has been developed using an expert system shell VISUAL RULE STUDIO, which acts as an ActiveX Designer under the Microsoft Visual Basic programming environment, with hybrid knowledge representation approach under object-oriented design environment. By using custom-built interactive graphical user interfaces, it is able to assist designers by furnishing with much needed expertise in this planning activity. Increase in efficiency, improvement, consistency of results and automated record keeping are among the advantages of such expert system. Solution strategies and development techniques of the system are addressed and discussed.

Keywords: knowledge-based system, construction, site level facilities, layout"

"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.

Keywords: knowledge-based system; object-oriented; system; preliminary design; water retaining structures"

"Computers which are used conventionally in numerical models for problem-solving and fast number-crunching are not user-friendly and lack knowledge transfer in model interpretation. Recent advances in artificial intelligence make it possible to systemise the experience and decision-making procedures of human experts. This paper describes the development of a prototype knowledge-based system (an advanced technique of artificial intelligence) as a knowledge-transfer tool for water-resource planning and management in coastal waters. The system can (a) run on a desktop computer and (b) act as a design aid, to assist in numerical modelling to simulate flow and/or water quality. Using the application in Hong Kong coastal waters, it was verified that the prototype system had the capability to undertake the reasoning process to select the model and associated parameters, equivalent to a human expert.

Keywords: artificial intelligence; coastal waters; knowledge-based system; knowledge transfer; water-resources management"

"The recent advances in artificial intelligence, coupled with the popularity of personal computers, have led to its widespread application in different domain problems. This paper describes the development of a prototype knowledge-based expert system - an advanced technique of artificial intelligence - as a tool of knowledge transfer and training for personnel in water resources planning and management. Details and a description of the application of the knowledge-based system on design of river network in Hong Kong are also presented.

Keywords: knowledge-based system; water resources management; knowledge transfer tool; artificial intelligence; and river network"

"A novice engineer often faces many difficulties during the design of liquid retaining structures, which involve making many decisions on the basis of judgment, heuristics, code of practice, rules of thumb, and previous experience. There is a need to develop programming environments that can incorporate engineering judgment along with algorithmic tools. In this paper, the development of a web-based knowledge-based system in design of liquid retaining structures, using blackboard architecture with hybrid knowledge representation techniques including production rule system and object-oriented approach, is presented. It is based on British Standards Codes of Practice BS8007 and BS8110. Tailor-made explanations are furnished to direct and assist inexperienced designers or civil engineering students to learn and capture how to design liquid retaining structures effectively and sustainably in their design practices. The use of this intelligent tutoring system in disseminating heuristic knowledge as well as experience to practitioners and civil engineering students is demonstrated.

Keywords: Web-Based, Knowledge-Based System, Liquid Retaining Structure Design, Instructional Tool"

A computerized Decision Support System (CDSS) can improve the adherence of the clinicians to clinical guidelines and protocols. Integrating it within the clinical workflow can reduce the workload of the physicians, and improve the acceptance of the system. The building of a prescriptive CDSS and its integration with a legacy cancer patient management system is the aim of the Oncocure project, which implements the existing protocol for the medical treatment of breast cancer in the Asbru language, and interfaces the Asbru interpreter with the Electronic Patient Record (EPR) in use in an oncologic unit. Our work is not constrained to a specific domain or EPR implementation, but can be generalized to other fields of medicine and patient management systems. When implemented, our CDSS is expected to reduce the cost of care while improving the adherence to the guideline and the quality of the documentation.

Design of concrete mixtures is the process of selecting the most economical and practical proportions of all the ingredients to produce quality concrete. Because of the nature of the mix design process and all the heuristic knowledge that is associated with it, concrete mix design lends itself well to a knowledge-based application. This paper describes a prototype knowledge-based system called HPCMIX that can be used to load the experimental data, develop several statistical models to determine the responses, evaluate the predicted models, and predict the 28 days strength and slump. It can also be used to design HPC mix proportions that are subjected to specified constraints (e.g. strength and slump). It is capable of selecting proportions of mixing water, cement, supplementary cementitious materials, aggregates and superplasticizer, with consideration being given to the effects of air content as well as water contributed by superplasticizer and moisture conditions of aggregates. As most of knowledge-based systems, this system has explanation facilities, can be incrementally expanded, and has an easy to understand knowledge base. The system was tested on a sample project. The system's selection of the concrete proportions compared favourably with the expert's selection. The system is very useful for civil engineering students as well as practicing engineers. © 2008 ASCE.

http://ascelibrary.org/doi/abs/10.1061/41002%28328%2957

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.

Keywords: knowledge-based system; object-oriented; system; preliminary design; water retaining structures

"This paper delineates the development of a prototype hybrid knowledge-based system for the optimum design of liquid retaining structures by coupling the blackboard architecture, an expert system shell VISUAL RULE STUDIO and genetic algorithm (GA). Through custom-built interactive graphical user interfaces under a user-friendly environment, the user is directed throughout the design process, which includes preliminary design, load specification, model generation, finite element analysis, code compliance checking, and member sizing optimization. For structural optimization, GA is applied to the minimum cost design of structural systems with discrete reinforced concrete sections. The design of a typical example of the liquid retaining structure is illustrated. The results demonstrate extraordinarily converging speed as near-optimal solutions are acquired after merely exploration of a small portion of the search space. This system can act as a consultant to assist novice designers in the design of liquid retaining structures.

Keywords: knowledge-based system, optimum design, liquid retaining structures, genetic algorithms"