A generic but flexible decision-support system for domestic water demand forecasting and management (DFMS) has been developed as part of a highlyintegrated decision-support system for river-basin management. Its purpose is to provide water-resources planners with the facilities for estimating future water demand for any demand region and time period, having regard to the possibility of introducing demand-management measures. The system has the capability of predicting domestic-water demand by various methods according to the data availability, computing conservation effectiveness due to the implementation of various demand-management measures, forecasting the number of customers for different consumption units (person, household, water connection) and facilitating the development of demand-scenarios for eveluating various options. The system is designed in such a way that makes it easy to use for both novice and experienced users since it is driven by a menu system which relies on a mouse rather than the keyboard. Moreover, the communication between user and the system is by means of a user-friendly interface which makes extensive use of hypertext and colour graphics in presenting the results. Briefly, DFMS comprises the following components: a GIS that stores, displays and analyses all geo-coded information such as satellite imagery, urban areas, cities and towns, etc.; • a database which provides access to non-spatial data such as demand-area location and characteristics including top-level descriptors such as population, total demand, per-capita consumption, etc.; • an expert system which uses the rule-based inference for data entry and predicting values (quantitative or qualitative) of variables from the knowledgebase; . four methods of demand forecasting ranging from superficial to detailed, namely time extrapolation, econometric variables, end-uses variables and households classification; a multi-objective decision component which helps the user to determine the most appropriate forecasting method and conservation measures; • a set of mathematical models to provide the analytical capability for quantifying descriptors, producing multiple outputs etc.; • a user-interface with access to the various functional components of the system and the various help/explain files; • a set of pre- and post-processors which support editing of the inputs data and the visualisation or analysis of model output, in addition to handling scenarios for each of the models or variables; • a set of help files which are used to provide the user with the necessary assistance if for any reason, a more detailed explanation is required, based on a hypertext; In order to demonstrate the system capability, DFMS has been applied to the Swindon demand area of Thames Water Utilities Ltd.

The research notes that deficiencies in knowledge acquisition are impeding the advancement of Knowledge Intensive Systems (KIS), such as Expert Systems (ES) and Decision Support Systems (DSS). Humphreys (1989) maintains the problem is not the quantity of knowledge collected but its quality. Humphreys (1989) contends that 'Knowledge' has too narrow a definition in knowledge acquisition dogma and a wider definition of 'knowledge' capable of handling 'procedural uncertainty' is required. 'Tacit knowledge' by which Polanyi (1967) contends individuals interpret the world appears a fruitful area to widen the definition of knowledge. The subjective nature of tacit knowledge makes its explication problematic, however, it is noted that tacit knowledge has a social aspect (interiorization) which appears amenable to sociological investigation. On the basis of the above it seemed prudent to focus the investigation down to the following research question, 'On the basis of its nature, is there a method whereby at least some tacit knowledge can be explicated for. a) building the knowledge base; b) more accurately predicting or planing for its usage and for setting expectations.' To test the thesis, a pilot investigation was undertaken at a local Housing Association in order to gain first hand experience of knowledge acquisition. Examples of how experts tacitally classify their domain were identified and methods of explicating this knowledge were tentatively formulated. The above resulted in the formulation of a new perspective: traditionally KBS has concerned itself with eliciting knowledge to be embodied in the knowledge base, whereas, IS has concerned itself in gaining the knowledge involved in the systems use/interpretation. Fieldwork was later conducted in the maternity units of two local hospitals in order to test the generalizability of these methods. Five methods for the explication of tacit knowledge were identified. 1) The analysis of the reification of existing systems and the rationality internal to these systems, can be used to explicate tacit knowledge. 2) More than one set of tacit knowledge can be present in one domain. Points where two sets of tacit knowledge interact expose contradictions which can be used as a tool to explicate the tacit knowledge of both groups. 3) The analysis of anecdotes revealed how domains were tacitally delimited and the 'criticality' of tasks within a domain. 4) Action research using a 'mock up' data base revealed tacitally held domain knowledge with implications for micro level criticality, of particular importance to interface design. 5) The thesis identified knowledge acquisition as a method of sociological investigation.

Thesis (M.S.)--Virginia Polytechnic Institute and State University, 1993. / Vita. Abstract. Includes bibliographical references (leaves 178-185). Also available via the Internet.

Thesis (M. Eng.)--Carleton University, 1988. / Also available in electronic format on the Internet.

No description available.

No description available.

No description available.

The use of ready-mixed concrete primarily involves two parties, the supplier and the customer (who is usually a construction contractor), although others may be involved. Ready-mixed concrete is not only a product, it is also a service. This implies that the supply of ready-mixed concrete should satisfy the customers' needs in relation to both quality and supply. To satisfy quality requirements, ready-mixed concrete must contain suitable materials, and be produced under conditions of quality control by experienced staff using reliable equipment To meet the supply requirement, it must be delivered at the time and rate required. Based on the findings in several surveys and studies, the UK ready-mixed concrete industry appears to meet the quality requirement quite well. However, the service provided to the customers could be improved. In addition, the industry's efficiency is not satisfactory when compared to its counterparts in other European countries such as Germany. Due to the peculiar characteristics of the product, which has a "shelf life" of only a few hours, and the unpredictable nature of the operating environment, the planning and scheduling problems of the production and delivery activities are usually unstructured and complex. In practice, UK ready-mixed concrete companies rely on their shippers' personal experience or intuition to make their planning and scheduling decisions. This research explored the feasibility of using a knowledge-based decision support system for planning' and scheduling the production and delivery of ready-mixed concrete. A prototype called ISRMC has been successfully developed as a result of a study of the operations of concrete production and construction as well as the ready-mixed concrete production and delivery process and detailed collection of knowledge from various sources.

Interactive as well as Automatic Verification and Validation is valuable, especially when the size of a knowledge base grows and manual techniques are not feasible. It ensures the stability of the system and raises the confidence in its level of performance. In this dissertation I address the problem of verification and validation of rule based expert systems. It is a problem knowledge engineers have to deal with while building their expert systems to ensure the reliability, accuracy, and completeness of their knowledge bases. The objective of this research is to make it easy for expert systems developers to build the right system by proposing practical and simple methods for building verification and validation programs to insure the integrity and performance of large scale knowledge based systems.

No description available.