Expert Support System Research Articles

Water Quality Index: A Fuzzy River-Pollution Decision Support Expert System

Water quality management policies, which are proposed to prevent, control, or treat environmental problems related to quality of water, are broad and complex issues. We have various types of water resources, different water uses, and a lot of decision parameters with several levels of decision makers involved. Moreover, there are a lot of strategies and technologies available to be applied for water quality management and so environmental decision makers are required to evaluate and prioritize them in order to choose the best possible plan for each particular problem. To provide a comprehensive but easy to use tool in the assessment and evaluation of water quality policies, the concept of water quality index (WQI) has been developed. Due to the abovementioned complexities, to get this index, there is a need for a methodology to not only structure and identify information relevant to the problem but also to help users reach a decision. Designing a multiple-attribute decision support expert system, which makes expert knowledge available to nonexpert users, can do this. In doing so, we may encounter qualitative or linguistic assessments in the index making process. Thus, fuzzy set theory can be applied to recognize this inherent fuzziness of such a process. Briefly, in this study we propose a fuzzy multiple-attribute decision support expert system to compute the water quality index and to provide an outline for the prioritization of alternative plans based on the amount of improvements in WQI. At the end, applicability and usefulness of the proposed methodology is revealed by a case study.

Decision support system for innovation with a special emphasis on pollution

Research and practical literature that is relevant to the area of the application of software and intelligent automation applications on pollution minimisation and mitigation processes is analysed in this paper. Especially highlighted and studied are calculators, software, expert and decision support systems, fuzzy logic, and neural networks, which emerge as the most regularly used automation approaches for pollution analysis. The results of this paper's study provide a useful insight into creating one's own Decision Support System for Innovation (DSSI). DSSI differs from other systems in the use of new multiple criteria analysis methods that were developed by the authors. Different criteria characterising various kinds of pollutions are included in databases of the DSSI.

An expert system for dynamic re-coordination of distributed workflows

A persistent problem in the use of automated workflow management systems for inter-organizational workflows has been the need for manual redefinition of coordination points in the process models when either organization changes its processes. Coordinating communications between production-chain organizations are usually based on the notification of completion of tasks by one party which constitute pre-conditions for activity in another organization; autonomous task changes disrupt coordination. This paper describes a workflow re-coordination model and corresponding expert support system based on workflow goals which are more stable than the low-level machine, role and technique dependent activities which implement them. Following development of the model, we describe a set of three elementary disruption cases which span a large number of common workflow changes. Using these cases we demonstrate that common coordination disruption situations can be totally or partially repaired by use of an expert coordination subsystem.

Application of Expert and Decision Support Systems for Optimizing Water Supply in the Jordan Valley

Expert System (ES) and Decision Support System (DSS) are becoming essential tools that support decision makers, professionals, and managers in their efforts to operate, control, and develop decisions on a sound and integrated basis. Applications of ES and DSS are not limited to a certain sector or field, but are typically used in sectors that involve management and planning. The purpose of this paper is to elaborate on the application of these systems in Jordan and specifically in managing and operating the water demand and supply of the main water carrier in the Jordan Valley, the King Abdullah Canal (KAC). This canal extends from the upper part of the valley at Adasiya down to the Dead Sea with a total length of 110 km connecting one of the most complicated irrigation and conveyance systems in the region. At present, the Jordan Valley Authority (JVA), which is responsible for all the activities in the Jordan Valley, is operating and managing the water of KAC using the JVA Water Management Information System (WMIS) and JVA Hydraulic Model. After five years of implementing this management system, there was enough information to analyze and evaluate it as well as to determine the areas of shortcomings. This paper focuses on analyzing these results and providing the necessary recommendations. These recommendations are in the form of software and hardware that will improve using both the Expert System and Knowledge Base System and make it a successful model of water optimization for the country and region.

EXPERT AND KNOWLEDGE SYSTEMS AND DATABASES OF THE BEST PRACTICE

Investigations on the similarities and differences of expert, knowledge management and decision support systems are presented in the paper. Explicit and tacit knowledge is analysed. The benefit of knowledge management systems, their development and implementation are analysed. The aspects of the best practice and its knowledge bases and databases are described. Practical possibilities to apply the knowledge systems are presented. On the base of practice acquired during the FP 6 project INTELCITIES the database of the best practice and the web‐based decision support system for real estate are developed. On the base of the BPJTA in PuBs project the database of the best practice and the web‐based decision support system for retrofit of public buildings are developed.

MULTIPLE CRITERIA DECISION SUPPORT WEB‐BASED SYSTEM FOR BUILDING REFURBISHMENT

In order to design and realise an efficient building refurbishment, it is necessary to carry out an exhaustive investigation of all solutions that form it, ie planimetric and volumetric changes, the elimination of building deterioration and obsolescence, the improvement of architectural and aesthetic appearance and indoor environmental quality, etc). The efficiency level of the considered building's refurbishment depends on many factors, including cost of refurbishment, annual fuel economy after refurbishment, tentative pay‐back time, harm to health of the materials used, aesthetics, maintenance properties, functionality, comfort, sound insulation and longevity, etc. Solutions of an alternative character allow for a more rational and realistic assessment of economic, ecological, legislative, climatic, social and political conditions, traditions and for better satisfaction of architectural, comfort, functional, maintenance and other customer's requirements. They also enable one to cut down on refurbishment costs. The selection of a refurbishment version mostly depends on the needs and existing financial capability of tenants. Based on an analysis of the existing neural networks, information, expert and decision support systems and in order to determine the most efficient versions of building refurbishment, a Multiple Criteria Decision Support Web‐Based System for Building Refurbishment (BR‐DSS) consisting of a database, database management system, model‐base, model‐base management system and a user interface was developed. The developed BR‐DSS and its practical application are described in the paper. Basing oneself on the developed system and database, it is possible to perform the alternative design of a building's refurbishment, multiple criteria analysis and make the selection of the most efficient versions, etc.

Multiple criteria decision support web‐based system for building refurbishment

In order to design and realise an efficient building refurbishment, it is necessary to carry out an exhaustive investigation of all solutions that form it, ie planimetric and volumetric changes, the elimination of building deterioration and obsolescence, the improvement of architectural and aesthetic appearance and indoor environmental quality, etc). The efficiency level of the considered building's refurbishment depends on many factors, including cost of refurbishment, annual fuel economy after refurbishment, tentative pay‐back time, harm to health of the materials used, aesthetics, maintenance properties, functionality, comfort, sound insulation and longevity, etc. Solutions of an alternative character allow for a more rational and realistic assessment of economic, ecological, legislative, climatic, social and political conditions, traditions and for better satisfaction of architectural, comfort, functional, maintenance and other customer's requirements. They also enable one to cut down on refurbishment costs. The selection of a refurbishment version mostly depends on the needs and existing financial capability of tenants. Based on an analysis of the existing neural networks, information, expert and decision support systems and in order to determine the most efficient versions of building refurbishment, a Multiple Criteria Decision Support Web‐Based System for Building Refurbishment (BR‐DSS) consisting of a database, database management system, model‐base, model‐base management system and a user interface was developed. The developed BR‐DSS and its practical application are described in the paper. Basing oneself on the developed system and database, it is possible to perform the alternative design of a building's refurbishment, multiple criteria analysis and make the selection of the most efficient versions, etc. First Published Online: 14 Oct 2010

A multiple criteria decision support web-based system for facilities management

An analysis of multiple criteria decision support systems and facilities management web-based automation applications that were developed by researchers from various countries assisted the authors to create their own Multiple Criteria Decision Support Web-Based System for Facilities Management (DSS-FM). DSS-FM differs from others in its use of new multiple criteria analysis methods as were developed by the authors. The database of a facilities management was developed and provides a comprehensive assessment of alternative versions from the economic, technical, technological, infrastructure, qualitative, technological, legislative and other perspectives. Based on the above complex databases, the developed Multiple Criteria Decision Support Web-Based System for Facilities Management enables the user to analyse alternatives quantitatively and conceptually (i.e. the text, formula, schemes, etc.). Applying the DSS-FM may increase the efficiency of calculators, analysers, software, neural networks, expert and decision support systems and e-commerce.

Spatial Expert Support System in Selecting Suitable Sites for Water Harvesting Structures — A Case Study of Song Watershed, Uttaranchal, India

The aim of this paper is to make a user friendly Spatial Expert Support System (SESS) for identifying suitable sites for water harvesting structures such as check dams, farm ponds, and groundwater recharge tanks. The developed system has been used to identify potential sites for water harvesting in the Song watershed, India. Basic input layers required for this study such as a digital elevation model, landuse, soils, drainage, geology, and buffer map for utility points were generated in a geographic information system (GIS). Technical guidelines suggested by the Integrated Mission for Sustainable Development (IMSD), and the Indian National Committee on Hydrology (INCOH), have been used as decision rules in the knowledge base shell of the developed SESS. Monthly water balance has been estimated using remote sensing and GIS techniques to augment the proposed water harvesting structures. The knowledge base can suitably be modified as and when required on the basis of other expert knowledge if found more judicious in this present context.

EFFICIENCY INCREASE OF E-LEARNING BY APPLYING ON‐LINE INTELLIGENCE COMPUTER LEARNING SYSTEMS

Based on the analysis of existing computer learning, neural networks, information, expert and decision support systems, the following e‐learning systems were developed by authors: construction, real estate, facilities management, international trade, ethics, innovation, sustainable development, building refurbishment, etc. Application of above multiple criteria computer learning systems developed by authors allows one to determine the strengths and weaknesses of analysed alternatives and its constituent parts. Calculations were made to find out by what degree one version is better than an other and the reasons disclosed why it is namely so. Landmarks are set for an increase in the efficiency of versions, etc.

A case-based expert support system for due-date assignment in a wafer fabrication factory

Owing to the complexity of wafer fabrication, the traditional human approach to assigning due-date is imprecise and very prone to failure, especially when the shop status is dynamically changing. Therefore, assigning a due date to each order becomes a challenge to the production planning and scheduling staff. Since most production orders are similar to those previously manufactured, the case based reasoning (CBR) approach provides a suitable means for solving the due-date assignment problem. This research proposes a CBR approach that employs the k-nearest neighbors concept with dynamic feature weights and non-linear similarity functions. The test results show that the proposed approach can more accurately predict order due dates than other approaches.

Neural network identification of high-risk suicide patients.

A history of medically serious suicide attempts (MSSA) has been considered a major risk factor for suicide. Backpropagation (BP) neural networks (NN) successfully detected patient files of patients who had committed MSSA but failed to identify MSSA patients when trained with data collected during face-to-face interviews. To develop an expert support system for the detection of suicide risk in patients with major psychiatric disorders using fuzzy adaptive learning control networks (FALCON) and BP enhanced with fuzzy logic neural networks. We used four types of input sets: (a) the most significant variables as defined by Garson's calculation of trained BP; (b) variables identified by logistic regression; (c) variables considered significant by experienced clinicians; or (d) the variables considered definitive by the computer programmer. In addition, the complete set of 59 input variables was used. The target variable was the existence of prior MSSA. Four training trials were performed with each input set (75% of the data was used for training and 25% for testing). Data was collected from 197 (50 MSSA, 147 non-MSSA) patients hospitalized at Sha'ar Menashe Mental Health Centre. BP enhanced with fuzzy logic achieved the most accurate results with the three variables chosen by the programmer (mean +/- SD; sensitivity=97% +/- 3.4%, specificity=69.2% +/- 6.9%), and FALCON trained with 15 variables chosen by an expert clinician obtained the highest sensitivity and specificity (mean +/- SD; sensitivity=94% +/- 6.9%, specificity=69% +/- 6.9%). A combined system of BP enhanced with fuzzy logic and FALCON may improve the detection rate of MSSA patients during patient interviews. A prospective validation study testing a combined system across 1, 2 and 5-year spans may provide a reliable instrument to aid in the detection of suicide prone psychiatric patients.

Rationality in Information Systems Support to Decision Making

Management information systems serve business organizations by providing information for decision making. Various types of systems serve different types of decision contexts. The philosophic basis of information system support is discussed. The rational (or normative) philosophy is widely used, and appears in business theory in the form of agency theory and transaction cost analysis. While this approach has been valuable in some contexts, there are other contexts where the rational approach has limited in utility for real business decision making. Decision makers need to consider subjective factors to enable them to cope with the high levels of uncertainty, incomplete understanding, and imperfect data typical of dynamic open systems. There are alternative philosophies upon which to base decision-making that are appropriate for specific decision contexts. Churchman identified empirical, multi-perspective frameworks, dialectic, and cause-and-effect inquiring systems as alternatives to the rational (normative) system. A number of information system tools, such as decision support systems, expert systems, and group support systems can be supported by models based on philosophies other than rational models. A more empirically based philosophy, with decision-makers balancing hypothesis generation and observations of performance, is often more appropriate. The relationship between Churchman's inquiring systems and information system types are discussed.

Neural Networks in the Intelligent Information Systems of Production Control

The paper presents the project of the hybrid expert system for decision-making support in production control. Since the majority of problems, which are solved on industrial control, are semistructured or non-structural, it is proposed to use the neural Hamming net as an output mechanism for processing fuzzy knowledge in the system. The sample of the problem solution on choosing the product policy is considered.

The effectiveness of expert support technology for decision making: individuals versus small groups

Expert support systems (ESSs) are increasingly used in organizations to support individuals and groups in decision making. Although ESSs have been shown to enhance the decision-making capabilities of individuals, their benefits in supporting group decision making are less clear. To the best of our knowledge, no empirical research has evaluated the effectiveness of the technology in the group setting or compared its usefulness for supporting individual versus group decision making. The results of this research show that ESSs benefit decision making of both individuals and groups and novices are able to gain more from ESSs than experts. The findings also suggest that groups outperform individuals in both with and without ESS support settings.

The Effectiveness of Expert Support Technology for Decision Making: Individuals versus Small Groups

Expert support systems (ESSs) are increasingly used in organizations to support individuals and groups in decision making. Although ESSs have been shown to enhance the decision-making capabilities of individuals, their benefits in supporting group decision making are less clear. To the best of our knowledge, no empirical research has evaluated the effectiveness of the technology in the group setting or compared its usefulness for supporting individual versus group decision making. The results of this research show that ESSs benefit decision making of both individuals and groups and novices are able to gain more from ESSs than experts. The findings also suggest that groups outperform individuals in both with and without ESS support settings.

Modelling Farm Diversification in Regions Using Expert and Decision Support Systems

The building of expert systems (ES) and decision support systems (DSS) has become a recent feature of many academic disciplines, but few examples can be found in human geography research. This paper draws attention to the potential of ES and DSS by reporting research on modelling farm diversification in the northern Pennines of England for four agricultural policy ‘scenarios’. The results of similar modelling in four other ‘lagging’ regions of the European Union (in Ireland, Scotland, France and Greece) are discussed. The research shows the opportunities that diversification can bring to farm businesses, including raised farm incomes and increased farm employment. But much depends on the willingness and ability of farmers to modify traditional farming systems, undertake the borrowing of capital and occupy more farmland.

Using the analytic hierarchy process in new product screening

The initial screening of a new product idea is critically important. Risky projects (i.e., those with high probabilities of failure) need to be eliminated early before significant investments are made and opportunity costs incurred. Unfortunately, previous research suggests that it is often difficult for managers to kill new product development projects once they have begun. Furthermore, recent studies (including some centering on PDMA members) suggest there is much room for improving new product screening, because this decision often is taken informally or unsystematically. Whereas tools such as Cooper's NewProd software are available to aid in the screening decision, management science decision support models for screening are not used frequently. In the present study, the authors illustrate the use of the Analytic Hierarchy Process (AHP) as a decision support model to aid managers in selecting new product ideas to pursue. The need for flexible models that are highly customized to each firm's challenges (such as AHP) to support the screening decision and to generate knowledge that will be used as input for a firm's expert support system is emphasized. The authors then present an in-depth example of an actual application of AHP in new product screening and discuss the usefulness of this process in gathering and processing knowledge for making new product screening decisions. Finally, the authors explain how a customized AHP process can be incorporated into a sophisticated information system or used as standalone support.

Using the Analytic Hierarchy Process in New Product Screening

The initial screening of a new product idea is critically important. Risky projects (i.e., those with high probabilities of failure) need to be eliminated early before significant investments are made and opportunity costs incurred. Unfortunately, previous research suggests that it is often difficult for managers to “kill” new product development projects once they have begun. Furthermore, recent studies (including some centering on PDMA members) suggest there is much room for improving new product screening, because this decision often is taken informally or unsystematically. Whereas tools such as Cooper's NewProd software are available to aid in the screening decision, management science decision support models for screening are not used frequently. In the present study, the authors illustrate the use of the Analytic Hierarchy Process (AHP) as a decision support model to aid managers in selecting new product ideas to pursue. The need for flexible models that are highly customized to each firm's challenges (such as AHP) to support the screening decision and to generate knowledge that will be used as input for a firm's expert support system is emphasized. The authors then present an in‐depth example of an actual application of AHP in new product screening and discuss the usefulness of this process in gathering and processing knowledge for making new product screening decisions. Finally, the authors explain how a customized AHP process can be incorporated into a sophisticated information system or used as standalone support. © 1999 Elsevier Science Inc.

人工衛星データを用いた都市環境管理支援エキスパートシステムの開発と開発達上国への適用

The purpose of this paper is to develop an environmental management support expert system for developing countries. First, we arrange the knowledge base from environmental management plans of Japanese four cities. It consists of environmental zoning areas, environmental guidelines, evaluation items and database required for reasoning. Then, we propose the evaluation method and indexes that enable to infer within the limits of data acquired, especially using satellite data as a substitute for landuse and vegetation data, and formulate the inference using fuzzy set theory. Finally, the usefulness of the system is shown through the application to Oita, Kitakyushu, Mokpo and Ujung Pandang.