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Journal articles on the topic 'Decision Support System and Expert System'

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Published: 4 June 2021

Last updated: 13 February 2022

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1

Greer, Marianne L. "Rxpert: A Prototype Expert System for Formulary Decision Making." Annals of Pharmacotherapy 26, no. 2 (February 1992): 244–50. http://dx.doi.org/10.1177/106002809202600221.

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OBJECTIVE: RXPERT, a prototype, computer-based, expert system that models the decision-making processes for an ambulatory (non-hospital) formulary, is described as an example of how expert systems may be used to support pharmacy decision making. Basic information about expert-system technology is provided through this example. BACKGROUND: Computer-assisted decision making is becoming an important and accepted aspect of complex, health-related decisions. Because expert-system support may become an integral component of future, complex, pharmacy decision making, it is important for pharmacists to become familiar with this technology and its possibilities for supporting pharmacy decisions. METHOD: Expert systems offer the potential advantages of making the human decision-making process explicit, more consistent, easily duplicated in many locations simultaneously, and easy to update and document. Although an expert system is seldom intended to replace human decision makers, it can provide valuable support for complex, multivariable decisions. Typical knowledge-acquisition and knowledge-engineering techniques, as well as the characteristics and structure of expert systems, are described, relative to the development of the RXPERT prototype. CONCLUSIONS: Although RXPERT is not yet in use, the process for using an expert system to support an individual committee member's personal assessment of a drug product is described. Decision-support expert systems are potentially useful to pharmacists in complex decision-making tasks.

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Lee, R. M. "On information system semantics: Expert vs. decision support systems." Social Science Information Studies 5, no. 1 (January 1985): 3–10. http://dx.doi.org/10.1016/0143-6236(85)90002-x.

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Megawaty, Megawaty, and Maria Ulfa. "Decision Support System Methods: A Review." Journal of Information Systems and Informatics 2, no. 1 (March 17, 2020): 192–201. http://dx.doi.org/10.33557/journalisi.v2i1.63.

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The current information system is the backbone of most companies or agencies. Currently there are various types of information systems including "transaction processing systems (TPS), office automation systems (OAS), knowledge work systems (KWS), management information systems (MIS), decision support systems (DSS), expert systems, groups decision support systems (GDSS), computer support collaborative work systems (CSCW), and executive support systems (ESS) ". Of the various types of information systems that are currently available decision support systems are widely used as aids in making decisions. For this reason, in this study, a study was conducted with a method that can be used in a decision support system. From the study conducted there are three decision support system methods that are often used, namely simple additive weighting (SAW), analytic hierarchy process (AHP), and simple multi attribute rating technique (SMART). The third method is a method that has a weighting value and criteria in the calculation process

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4

Kersten, Gregory E. "Expert system technology and strategic decision support." Mathematical and Computer Modelling 12, no. 10-11 (1989): 1321–33. http://dx.doi.org/10.1016/0895-7177(89)90371-3.

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Doukidis, Georgios I. "Decision support system concepts in expert systems: An empirical study." Decision Support Systems 4, no. 3 (September 1988): 345–54. http://dx.doi.org/10.1016/0167-9236(88)90021-8.

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Lee, Daniel T. "Expert Decision-support Systems for Decision-making." Journal of Information Technology 3, no. 2 (June 1988): 85–94. http://dx.doi.org/10.1177/026839628800300204.

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Computers have made tremendous contributions towards transactional processing. However, the highest pay-off the computer can make is not in transactional processing but in decision-making. Recently, expert systems have just begun to be used in the decision-making process. Individual technologies alone are inadequate for an effective decision support. The purpose of this paper is to investigate the related issues in decision support and to develop an expert decision support system (EDSS) for combining decision support systems and expert systems into a unified whole for decision support. The emphasis will be on developing a DSS/ES model which can be used to integrate the traditional DSS database and ES knowledge-base for building a user-friendly EDSS.

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Gutenson, J. L., A. N. S. Ernest, J. R. Fattic, L. E. Ormsbee, A. A. Oubeidillah, and X. Zhang. "Water Expert: a conceptualized framework for development of a rule-based decision support system for distribution system decontamination." Drinking Water Engineering and Science 8, no. 2 (August 28, 2015): 9–24. http://dx.doi.org/10.5194/dwes-8-9-2015.

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Abstract. Significant drinking water contamination events pose a serious threat to public and environmental health. Water utilities often must make timely, critical decisions without evaluating all facets of the incident. The data needed to enact informed decisions are inevitably dispersant and disparate, originating from policy, science, and heuristic contributors. Water Expert is a functioning hybrid decision support system (DSS) and expert system framework that emphasizes the meshing of parallel data structures in order to expedite and optimize the decision pathway. Delivered as a thin-client application through the user's web browser, Water Expert's extensive knowledgebase is a product of inter-university collaboration that methodically pieced together system decontamination procedures. Decontamination procedures are investigated through consultation with subject matter experts, literature review, and prototyping with stakeholders. This paper discusses the development of Water Expert, analyzing the development process underlying the DSS and the system's existing architecture specifications. Water Expert constitutes the first system to employ a combination of deterministic and heuristic models which provide decontamination solutions for water distribution systems. Results indicate that the decision making process following a contamination event is a multi-disciplinary effort. This contortion of multiple inputs and objectives limit the ability of the decision maker to find optimum solutions without technological intervention.

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Gutenson, J. L., A. N. S. Ernest, J. R. Fattic, L. E. Ormsbee, A. A. Oubeidillah, and X. Zhang. "Water Expert: a conceptualized framework for development of a rule-based decision support system for distribution system decontamination." Drinking Water Engineering and Science Discussions 7, no. 1 (May 27, 2014): 169–211. http://dx.doi.org/10.5194/dwesd-7-169-2014.

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Abstract. Significant drinking water contamination events pose a serious threat to public and environmental health. Water utilities often must make timely, critical decisions without evaluating all facets of the incident, as the data needed to enact informed decisions are inevitably dispersant and disparate, originating from policy, science, and heuristic contributors. Water Expert is a functioning hybrid decision support system (DSS) and expert system framework, with emphases on meshing parallel data structures to expedite and optimize the decision pathway. Delivered as a thin-client application through the user's web browser, Water Expert's extensive knowledgebase is a product of inter-university collaboration that methodically pieced together system decontamination procedures through consultation with subject matter experts, literature review, and prototyping with stakeholders. This paper discusses development of Water Expert, analyzing the development process underlying the DSS and the system's existing architecture specifications.

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9

CHAN, CHRISTINE WAICHI, WEERAPONG KRITPIPHAT, and PAITOON TONTIWACHWUTHIKUL. "KNOWLEDGE ENGINEERING OF A MONITORING AND CONTROL DECISION SUPPORT SYSTEM." International Journal of Software Engineering and Knowledge Engineering 10, no. 03 (June 2000): 301–18. http://dx.doi.org/10.1142/s0218194000000183.

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This paper presents the Object-Oriented Knowledge Engineering (OOKE) methodology and its application in developing an expert system. OOKE is an expert system development methodology which incorporates the conceptual modelling tool of Inferential Modelling Technique into the analysis model of the Object-Oriented Software Engineering methodology. It was applied to develop a supervisory and decision support system for monitor and control of a water distribution system called the Water Advisor. The expertise, heuristics and reasoning knowledge of experts were acquired and then formulated in a model building process using the OOKE into a conceptual model which became the basis for a prototype expert system.

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Mulya, Dimmas, Dian Pratiwi, and Is Mardianto. "Decision Support System for Diagnose Hepatitis Type using Expert System Method." Journal of Information Technology and Computer Science 6, no. 1 (April 30, 2021): 66–79. http://dx.doi.org/10.25126/jitecs.202161231.

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In the medical world, there are five types of Hepatitis, namely Hepatitis A, B, C, D, and E. However, the five types of hepatitis have similar symptoms, including yellowing of the skin color, yellowing of the eyeball, loss of appetite, etc. Thus, many of the Medical Personnel often misdiagnose the patient for the type of hepatitis or not suffer from hepatitis.Therefore, previous diagnostic data ware collected from Medical Specialists which will be processed and developed into the Java-based Decision Support System Application with Expert System method with the percentage output of the likelihood of patients from each type of hepatitis along with the possibility of patients not suffering from hepatitis.With the output of this application, the percentage of the possibility of each type of hepatitis or the possibility of not suffering from hepatitis can help Medical Personnel to make diagnostic decisions based on alternatives provided by the application.

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11

Jenicke, Lawrence O. "The Expert System as a Decision Support Tool." American Journal of Business 3, no. 1 (April 22, 1988): 47–52. http://dx.doi.org/10.1108/19355181198800008.

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12

Korpinen, L., T. Pietilä, J. Peltola, M. Nissilä, T. Keränen, T. Tuovinen, B. Falck, E. S. Petránek, and H. Frey. "Evaluation of Epilepsy Expert — a decision support system." Computer Methods and Programs in Biomedicine 45, no. 3 (November 1994): 223–31. http://dx.doi.org/10.1016/0169-2607(94)90206-2.

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Biswas, Gautam, Michael Oliff, and Arun Sen. "An expert decision support system for production control." Decision Support Systems 4, no. 2 (June 1988): 235–48. http://dx.doi.org/10.1016/0167-9236(88)90132-7.

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14

Özbay, Kaan, and Shirsendu Mukherjee. "Web-Based Expert Geographical Information System for Advanced Transportation Management Systems." Transportation Research Record: Journal of the Transportation Research Board 1719, no. 1 (January 2000): 200–208. http://dx.doi.org/10.3141/1719-26.

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The Internet is fast becoming the standard environment for client-server applications that involve multiple users. The proliferation of Internet-based application development tools opens new doors to transportation researchers who work in real-time decision support system development. In the 1990s, one of the most important problems in advanced transportation management systems research was the development of better incident management systems. Although the incident management process has been well studied, the development of real-time decision support systems that can be used by all the involved agencies remains a challenging area of transportation engineering research. Existing incident management systems are developed on various traditional computing platforms, including UNIX and Windows. However, with the advent of the World Wide Web and Internet-based programming tools such as Java, it is possible to develop platform independent decision support tools for the incident management agencies. Web-based support tools offer an invaluable opportunity to develop next-generation online decision support tools for real-time traffic management. The applicability of Web-based tools to the development of online decision support systems for incident management is explored and demonstrated, and a prototype incident management decision support system (DSS) that has most of the capabilities of similar UNIX-based DSS support systems is developed and tested. Briefly described are the implementation and development of a prototype wide-area incident management system using Web-based tools.

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Kulshrestha, S., and R. Khosa. "CLIPS based decision support system for Water Distribution Networks." Drinking Water Engineering and Science Discussions 4, no. 1 (March 7, 2011): 1–38. http://dx.doi.org/10.5194/dwesd-4-1-2011.

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Abstract. The Water Distribution Networks (WDN) are managed by experts, who, over the years of their association and responsibility, acquire an empirical knowledge of the system and, characteristically, this knowledge remains largely confined to their respective personal domains. In the event of any new information and/or emergence of a new problem, these experts apply simple heuristics to design corrective measures and cognitively seek to predict network performance. The human interference leads to inefficient utilization of resources and unfair distribution. Researchers over the past, have tried to address to the problem and they have applied Artificial Intelligence (AI) tool to automate the decision process and encode the heuristic rules. The application of AI tool in the field of WDN management is meager. This paper describes a component of an ongoing research initiative to investigate the potential application of artificial intelligence package CLIPS (short for C Language Integrated Production System, developed at NASA/Johnson Space Center) in the development of an expert decision support system for management of a water distribution network. The system aims to meet several concerns of modern water utility managers as it attempts to formalize operational and management experiences, and provides a frame work for assisting water utility managers even in the absence of expert personnel.

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Kentala, Erna, Yrjö Auramo, Ilmari Pyykkö, and Martti Juhola. "Otoneurological Expert System." Annals of Otology, Rhinology & Laryngology 105, no. 8 (August 1996): 654–58. http://dx.doi.org/10.1177/000348949610500812.

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An otoneurological expert system was developed to help collect data and diagnose both central and peripheral diseases causing vertigo. Patient history and otoneurological and other examination results are used in the reasoning process. The case history data can be either mandatory or supportive. Mandatory questions are used to confirm a diagnosis, and conflicting answers are used to reject an unlikely disease. Supportive questions support or suppress a diagnosis, but their presence is not obligatory. The reasoning procedure of the otoneurological expert system scores every question independently for different diagnoses, depending on how well they agree with the symptom entity of a disease. Diagnostic criteria are set for each disease. Graphic displays illustrate the linear and nonlinear correlation between the symptoms and diseases. Emphasis is placed on diminishing the possibility of a wrong decision rather than maximizing the likelihood of reaching only one right decision, so that even rare diseases can be taken into consideration.

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17

Walek, Bogdan, Ondrej Pektor, and Radim Farana. "Decision Support System for Evaluating Suitable Job Applicants." Mathematics 9, no. 15 (July 27, 2021): 1773. http://dx.doi.org/10.3390/math9151773.

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This paper describes a novel approach in the area of evaluating suitable job applicants for various job positions, and specifies typical areas of requirement and their usage. Requirements for this decision-support system are defined in order to be used in middle-size companies. Suitable tools chosen were fuzzy expert systems, primarily the inference system Takagi-Sugeno type, which were then supplied with implementation of methods of variant multi-criteria analysis. The resulting system is a variable tool with the possibility to simply set the importance of individual selection criteria so that it can be used in various situations, primarily in repeated selection procedures for similar job positions. A strong emphasis is devoted to the explanatory module, which enables the results of the expert system to be used easily. Verification of the system on real data in cooperation with a collaborating company has proved that the system is easily usable.

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18

Sandeep, K., and K. Rakesh. "CLIPS based decision support system for water distribution networks." Drinking Water Engineering and Science 4, no. 1 (October 27, 2011): 37–50. http://dx.doi.org/10.5194/dwes-4-37-2011.

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Abstract. The difficulty in knowledge representation of a water distribution network (WDN) problem has contributed to the limited use of artificial intelligence (AI) based expert systems (ES) in the management of these networks. This paper presents a design of a Decision Support System (DSS) that facilitates "on-demand'' knowledge generation by utilizing results of simulation runs of a suitably calibrated and validated hydraulic model of an existing aged WDN corresponding to emergent or even hypothetical but likely scenarios. The DSS augments the capability of a conventional expert system by integrating together the hydraulic modelling features with heuristics based knowledge of experts under a common, rules based, expert shell named CLIPS (C Language Integrated Production System). In contrast to previous ES, the knowledge base of the DSS has been designed to be dynamic by superimposing CLIPS on Structured Query Language (SQL). The proposed ES has an inbuilt calibration module that enables calibration of an existing (aged) WDN for the unknown, and unobservable, Hazen-Williams C-values. In addition, the daily run and simulation modules of the proposed ES further enable the CLIPS inference engine to evaluate the network performance for any emergent or suggested test scenarios. An additional feature of the proposed design is that the DSS integrates computational platforms such as MATLAB, open source Geographical Information System (GIS), and a relational database management system (RDBMS) working under the umbrella of the Microsoft Visual Studio based common user interface. The paper also discusses implementation of the proposed framework on a case study and clearly demonstrates the utility of the application as an able aide for effective management of the study network.

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Taylor, Jason. "Linking psychiatric registers to decision support systems." Psychiatric Bulletin 16, no. 5 (May 1992): 275–78. http://dx.doi.org/10.1192/pb.16.5.275.

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This paper discusses the concept of Psychiatric Register Integrated Support Modules (PRISM). It addresses issues around the linkage of longitudinal data held on individual patients in case register systems to expert and other decision support systems. The paper describes two developed systems which link to the SafetyNet case register system, an inexpensive and comprehensive Mental Health Information System which runs on single or networked computers and which was previously described in detail (Taylor & Bhumgara, 1989). The merits of the two approaches in aiding clinical decision making on anti-psychotic medication are discussed as are the medico-legal implications of using expert systems.

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Yang, Zong Xiao, Tian Xiao, Lei Song, and Guan Qiang Dong. "Expressway Event Management Expert System Based on Ontology and Rule Reasoning." Advanced Materials Research 601 (December 2012): 361–68. http://dx.doi.org/10.4028/www.scientific.net/amr.601.361.

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Response and decision-making support in expressway emergency management and rescue greatly affects some key factors like emergency rescue plan, emergency duration time, effect range, economy and time loss. Experts system is a kind of intelligent program, using knowledge and reasoning to solve the complex problem that only experts can work out, it is a popular and efficient decision-support means, has some practical features that manual way cannot compare with and offers a modem scientific measure in incident management. Expert system can provide high-efficiency, rapid, exact and powerful assistance in decision support. In order to deal with various possible emergencies promptly and efficiently and therefore ensure the safety and unblocked state of the expressway, develop the expert system has become a trend of emergency rescue and management. In expert system,The knowledge representation is the key basic issues has the important influence to construction of the knowledge base and the reasoning of the expert system. So there has the practical significance to further research on knowledge representation of expressway accident management system, According to features of different knowledge, in exsiting expert systems different knowledge representation methods were adopted such as frame, production rule, procedure, first-order predicate logic, etc. This paper focus on the ontology’s application in the field of expressway emergency rescue and propose a expressway event managemnet expert system based on ontology and rule reasoning.

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Chang-Shing Lee and Mei-Hui Wang. "A Fuzzy Expert System for Diabetes Decision Support Application." IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 41, no. 1 (February 2011): 139–53. http://dx.doi.org/10.1109/tsmcb.2010.2048899.

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22

Borgers, Aloys, and Harry Timmermans. "A decision support and expert system for retail planning." Computers, Environment and Urban Systems 15, no. 3 (January 1991): 179–88. http://dx.doi.org/10.1016/0198-9715(91)90007-z.

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23

Plant, R. E. "An integrated expert decision support system for agricultural management." Agricultural Systems 29, no. 1 (1989): 49–66. http://dx.doi.org/10.1016/0308-521x(89)90070-x.

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Ning, Bo, Jiafeng Xu, Yangming Hu, Zhanguo Ma, Man Bi, and Lingbo Liu. "An expert decision support system for sandstone acidizing design." Journal of Petroleum Exploration and Production Technology 9, no. 3 (December 10, 2018): 1927–41. http://dx.doi.org/10.1007/s13202-018-0588-3.

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Kustra, Todd W., Subhashini Ganapathy, Amanda C. Muller, and S. Narayanan. "Decision Support System for Logistics Systems Analysis Using Image Theory and Work Domain Analysis." Journal of Defense Modeling and Simulation: Applications, Methodology, Technology 2, no. 2 (April 2005): 71–85. http://dx.doi.org/10.1177/154851290500200203.

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In this study, image theory and work domain analysis were used to develop an interactive decision support system for sortie generation tasks in an Air Force aircraft maintenance unit. Aircraft maintenance personnel were charged with creating a short list of aircraft for deployment using either maintenance information alone or maintenance information with the interactive decision support system. Results were compared with a deployment list developed by expert aircraft maintenance superintendents. The deployment lists generated with the interactive decision support system more closely resembled the experts' list and took less time to create than those generated using maintenance information alone. These results show the viability of the methodology outlined in this study for creating decision support systems in complex logistics planning.

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Albrigo, L. G., J. I. Valiente, and H. W. Beck. "FLOWERING EXPERT SYSTEM DEVELOPMENT FOR A PHENOLOGY BASED CITRUS DECISION SUPPORT SYSTEM." Acta Horticulturae, no. 584 (July 2002): 247–54. http://dx.doi.org/10.17660/actahortic.2002.584.30.

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Malik, Meenakshi, Mukesh Sehgal, A. K. Kanojia, and R. V. Singh. "A review paper on decision support system/expert system developed on mango." INTERNATIONAL JOURNAL OF PLANT PROTECTION 11, no. 1 (April 15, 2018): 119–23. http://dx.doi.org/10.15740/has/ijpp/11.1/119-123.

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Fahmi, Ali, Amin Dorostanian, Hassan Rezazadeh, and Alireza Ostadrahimi. "An Intelligent Decision Support System (IDSS) for Nutrition Therapy." International Journal of Reliable and Quality E-Healthcare 2, no. 4 (October 2013): 14–27. http://dx.doi.org/10.4018/ijrqeh.2013100102.

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In this paper, the authors have presented an expert system to support decision makers in nutrition therapy planning. This system is an extended version of a fuzzy decision support system for nutrition therapy. The presented expert system is equipped with an updated knowledge base component by using a set of rules. Also in order to deal with vagueness and uncertainty, fuzzy set theory could provide a suitable framework for data management, modelling and decision support. Therefore, fuzzy rules empower this system to be implemented more realistically. In addition, for developing knowledge management component, artificial neural network (ANN) is applied to survey the input data and information in the long term. The integration of ANN with the expert system provides the possibility for a set of novel rules to be generated and consequently adds new knowledge to the system.

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Kaklauskas, Artūras, and Andrius Gulbinas. "KNOWLEDGE BASED DECISION SUPPORT SYSTEM FOR BUILDING REFURBISHMENT." Technological and Economic Development of Economy 11, no. 3 (September 30, 2005): 176–82. http://dx.doi.org/10.3846/13928619.2005.9637696.

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The need to effectively integrate decision‐making tasks (such as interactive access to data and support for numerical and quantitative modelling techniques) together with the knowledge representation and visualisation tasks and inference procedures that model an expert's thought process has provoked research efforts to integrate decision support systems (DSS) with knowledge and expert systems (ES), neural networks and multimedia towards the formulation of intelligent DSS. We can analyse the intelligent DSS as a network of distributed systems (DSS, ES, neural networks, etc.) each of them facing and solving a specific problem. Under this point of view different systems can be integrated in the integrated system. Knowledge based decision support system for building refurbishment developed in Vilnius Gediminas Technical University is described in the paper in order to describe the above systems integration.

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Masciopinto, C., V. Palmisano, F. Tangorra, and M. Vurro. "A Decision Support System for Artificial Recharge Plant." Water Science and Technology 24, no. 9 (November 1, 1991): 331–42. http://dx.doi.org/10.2166/wst.1991.0262.

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The need for artificial recharge plants is the result of the qualitative and quantitative worsening of groundwater resources due to increased pumping and wastewater discharge. This paper described a system that uses artificial intelligence techniques for designing an artificial recharge plant. The system can be used as a training tool for new engineers, as well as an aid in the choices for expert engineers. The system is an application of an expert system shell running on a common p.c. machine. The model is made up of two knowledge bases, respectively denoted as Quantity artificial recharge and Quality artificial recharge. The former is related to the quantitative aspects, such as geology, climate and land availability, the latter to qualitative aspects, such as water use and treatment plant. Two case studies have been implemented in order to confirm the validity of this kind of systemic approach.

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King, Dave. "Intelligent decision support: Strategies for integrating decision support, database management, and expert system technologies." Expert Systems with Applications 1, no. 1 (January 1990): 23–38. http://dx.doi.org/10.1016/0957-4174(90)90066-4.

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Barnett, Barbara J. "Perspectives on Decision Analysis for Decision Support System Design." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 37, no. 16 (October 1993): 1101. http://dx.doi.org/10.1177/154193129303701613.

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This symposium addresses the characterization of human decision making within a complex environment for the purpose of developing improved decision support systems. All of the work presented in this symposium was conducted under a Navy research program entitled “Tactical Decision Making Under Stress” (TADMUS). The overall objective of the TADMUS program is to improve tactical decision making of anti-air warfare (AAW) crew members within the Aegis cruiser's combat information center (CIC) under conditions of stress and uncertainty. The unique aspect of this effort is that each presentation addresses decision making behavior, within a single domain, from a different perspective. The goal of each effort is to characterize some aspect of expert decision making performance within the AAW task environment, and to make recommendations for the resulting decision support system design based upon these characterizations. The result is a multi-faceted, human-centered approach to information organization and interface display design for a decision support system.

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Felföldi, János. "Work Organisation Supported by an Expert System in Agriculture." Acta Agraria Debreceniensis, no. 1 (December 4, 2001): 57–60. http://dx.doi.org/10.34101/actaagrar/1/3612.

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Expert systems are softwares that incorporate the experience of an expert and support decision makers by leading them through the thinking processes of an expert in the form of „if…then” rules. To use an expert system we have to work with knowledge expressed in a pre-determined form. To do so, we used a shell that can be purchased, and we acquired knowledge about the topic from experts through interviews and personal monitoring. Attributes that are non-measurable, such as many of the factors determining work-place organisation and revealing knowledge related to it, can be formed into words by using expert systems. The goal of the study was to present a suggested form of expert system model to help judge the level of work-place organisation.

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Goul, Michael, and Fred Tonge. "PROJECT IPMA: APPLYING DECISION SUPPORT SYSTEM DESIGN PRINCIPLES TO BUILDING EXPERT-BASED SYSTEMS*." Decision Sciences 18, no. 3 (July 1987): 448–67. http://dx.doi.org/10.1111/j.1540-5915.1987.tb01535.x.

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Rassbach, Laura, Elizabeth Bradley, and Ken Anderson. "Providing Decision Support for Cosmogenic Isotope Dating." AI Magazine 32, no. 2 (March 16, 2011): 69. http://dx.doi.org/10.1609/aimag.v32i2.2349.

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Human experts in scientific fields routinely work with evidence that is noisy and untrustworthy, heuristics that are unproven, and possible conclusions that are contradictory. We present a deployed AI system, Calvin, for cosmogenic isotope dating, a domain that is fraught with these difficult issues. Calvin solves these problems using an argumentation framework and a system of confidence that uses two-dimensional vectors to express the quality of heuristics and the applicability of evidence. The arguments it produces are strikingly similar to published expert arguments. Calvin is in daily use by isotope dating experts.

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Hao, Xuelong, Chen Wen, Ning Zhao, Lu Lu, Kai Zhang, and Donghui Zhang. "Prototype of an Expert System for the Selection of Aircraft Structural Materials." International Journal of Photoenergy 2020 (December 19, 2020): 1–7. http://dx.doi.org/10.1155/2020/8891541.

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Expert systems (ES) are widely used for engineering and manufacturing applications nowadays. In order to solve the problems in material selection in the aviation field, an aircraft material expert system (AMES) was developed. This expert system is based on the knowledge of multiple experts and aviation data. A decision support system (DSS) was designed for selecting the materials used in aviation fields. The flows of material selection were designed, and the models of AMES were established. A data base system was also designed to implement AMES.

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�stermark, Ralf, and Hannu Salmela. "Connecting expert system features to a multiple criteria programming based decision support system." Computer Science in Economics and Management 1, no. 3 (1988): 175–88. http://dx.doi.org/10.1007/bf00436279.

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Karmakar, S., M. NKetia, C. Laguë, and J. Agnew. "Development of expert system modeling based decision support system for swine manure management." Computers and Electronics in Agriculture 71, no. 1 (April 2010): 88–95. http://dx.doi.org/10.1016/j.compag.2009.12.009.

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Vedder, Richard G., and Richard O. Mason. "AN EXPERT SYSTEM APPLICATION FOR DECISION SUPPORT IN LAW ENFORCEMENT." Decision Sciences 18, no. 3 (July 1987): 400–414. http://dx.doi.org/10.1111/j.1540-5915.1987.tb01532.x.

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Potocan, Vojko. "Managerial Expert System as an Information Support to Decision - Making." IFAC Proceedings Volumes 30, no. 24 (September 1997): 89–92. http://dx.doi.org/10.1016/s1474-6670(17)42230-0.

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Hodhod, Rania, Shuangbao Wang, and Shamim Khan. "Cybersecurity Curriculum Development Using AI and Decision Support Expert System." International Journal of Computer Theory and Engineering 10, no. 4 (2018): 111–15. http://dx.doi.org/10.7763/ijcte.2018.v10.1209.

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Segev, Eli, and Paul Gray. "Integrating an Expert System and DSS for Strategic Decision Support." Information Resources Management Journal 2, no. 1 (January 1989): 1–13. http://dx.doi.org/10.4018/irmj.1989010101.

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Huynh, T., and C. Lassez. "An expert decision-support system for option-based investment strategies." Computers & Mathematics with Applications 20, no. 9-10 (1990): 1–14. http://dx.doi.org/10.1016/0898-1221(90)90108-v.

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Ashraf, Ather, Muhammad Akram, and Mansoor Sarwar. "Type-II Fuzzy Decision Support System for Fertilizer." Scientific World Journal 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/695815.

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Type-II fuzzy sets are used to convey the uncertainties in the membership function of type-I fuzzy sets. Linguistic information in expert rules does not give any information about the geometry of the membership functions. These membership functions are mostly constructed through numerical data or range of classes. But there exists an uncertainty about the shape of the membership, that is, whether to go for a triangle membership function or a trapezoidal membership function. In this paper we use a type-II fuzzy set to overcome this uncertainty, and develop a fuzzy decision support system of fertilizers based on a type-II fuzzy set. This type-II fuzzy system takes cropping time and soil nutrients in the form of spatial surfaces as input, fuzzifies it using a type-II fuzzy membership function, and implies fuzzy rules on it in the fuzzy inference engine. The output of the fuzzy inference engine, which is in the form of interval value type-II fuzzy sets, reduced to an interval type-I fuzzy set, defuzzifies it to a crisp value and generates a spatial surface of fertilizers. This spatial surface shows the spatial trend of the required amount of fertilizer needed to cultivate a specific crop. The complexity of our algorithm isO(mnr), wheremis the height of the raster,nis the width of the raster, andris the number of expert rules.

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Yu, Yong Hai, Rui Hong Zhang, Bin Cheng, and Hai Liang Ren. "Study on Expert Decicion System for Spraying of Trellis Crop." Key Engineering Materials 584 (September 2013): 225–30. http://dx.doi.org/10.4028/www.scientific.net/kem.584.225.

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Bases on accurate spraying of the trellis crop, the expert decision-making technology was used to provide the decision support. The intelligent decision support system was combined with accurate spraying technology of pesticides. According to the differences of relevant factor of accurate spraying, the expert decision-making system of job parameters of trellis spraying machine was researched and set up. And systematic target, system expansion and system architecture were analyzed. Through C4.5 algorithm, the expert decision-making system was to decide if the trellis crop was sprayed under different climatic conditions, and the decision tree of spraying was constructed. It provided intelligent decision support to accurate spraying.

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Póvoa, P., A. Nobre, P. Leitão, P. Galvão, H. Santos, A. Frazão, R. Neves, and J. S. Matos. "Operational decision support system for large combined sewage systems: Lisbon/Tagus estuary case study." Water Science and Technology 72, no. 8 (July 9, 2015): 1421–27. http://dx.doi.org/10.2166/wst.2015.352.

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Managing combined sewage systems in large cities discharging to coastal waters, often bearing recreational activities, remains a challenge. Studying the impacts of such discharges requires the development of specific models. Hydrodynamic and water quality modelling of coastal waters employs numerical methods and algorithms, leading to the design of complex models which require expert use. The use of such models as decision support tools to simulate discharge impacts and define adequate corrective measures could represent a key part in meeting this challenge. In this paper, the authors describe the work undertaken to develop an operational decision support system (ODSS) methodology aiming to enable wastewater utilities' non-expert staff to carry out user-friendly scenario analysis based on computational fluid dynamics simulations. This article depicts the application and validation of the ODSS to the combined sewage system and the Tagus estuary of the city of Lisbon in Portugal. The ODSS was used for simulating the effects in the receiving coastal waters of a discharge caused by a scheduled maintenance operation in the sewage infrastructure. Results show that the use of such ODSS by non-expert staff increases their decision capabilities and knowledge of the wastewater utility's contribution to reducing negative impacts of sewage discharges on the receiving water bodies.

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Yaw Addai Duah, Daniel, Kevin Ford, and Matt Syal. "Expert knowledge elicitation for decision-making in home energy retrofits." Structural Survey 32, no. 5 (November 4, 2014): 377–95. http://dx.doi.org/10.1108/ss-01-2014-0004.

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Purpose – The purpose of this paper is to develop a knowledge elicitation strategy to elicit and compile home energy retrofit knowledge that can be incorporated into the development of an intelligent decision support system to help increase the uptake of home energy retrofits. Major problems accounting for low adoption rates despite well-established benefits are: lack of information or information in unsuitable and usable format for decision making by homeowners. Despite the important role of expert knowledge in developing such systems, its elicitation has been fraught with challenges. Design/methodology/approach – Using extensive literature review and a Delphi-dominated data collection technique, the relevant knowledge of 19 industry experts, selected based on previously developed determinants of expert knowledge and suitable for decision making was elicited and compiled. Boolean logic was used to model and represent such knowledge for use as an intelligent decision support system. Findings – A combination of comprehensive knowledge elicitor training, Delphi technique, semi-structured interview, and job shadowing is a good elicitation strategy. It encourages experts to describe their knowledge in a natural way, relate to specific problems, and reduces bias. Relevant and consensus-based expert knowledge can be incorporated into the development of an intelligent decision support system. Research limitations/implications – The consensus-based and relevant expert knowledge can assist homeowners with decision making and industry practitioners and academia with corroboration and enhancement of existing knowledge. The strategy contributes to solving the knowledge elicitation challenge. Originality/value – No previous study regarding a knowledge elicitation strategy for developing an intelligent decision support system for the energy retrofit industry exists.

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Grabowski, Martha. "Decision Support to Masters, Mates on Watch, and Pilots: The Piloting Expert System." Journal of Navigation 43, no. 03 (September 1990): 364–84. http://dx.doi.org/10.1017/s0373463300014004.

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Piloting large vessels in increasingly congested waterways is no simple task. As in many ‘decision-making under uncertainty’ scenarios, masters, mates and pilots engaged in piloting are inundated with much information and required to make crucial decisions in real time. Piloting is also an inherently judgmental activity. Pilots and ships' captains invariably develop heuristics for transiting particular waterways. As vessels become larger, cargoes more hazardous, and the waterways more congested, decision aid technology is being considered to improve piloting decision-making. This paper describes one approach to providing improved on-board decision support to masters, mates on watch, and pilots navigating in restricted waters. We discuss (1) the use of cognitive decision aids in piloting, (2) the design of such a decision aid developed for New York harbour, (3) simulator experiments evaluating the expert system, and (4) plans to apply the approach and ‘lessons learned’ to the development of an expert system for tankers transiting the Gulf of Alaska.

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Teoh, A., S. A. Samad, and A. Hussain. "FUSION DECISION FOR A BIMODAL BIOMETRIC VERIFICATION SYSTEM USING SUPPORT VECTOR MACHINE AND ITS VARIATIONS." ASEAN Journal on Science and Technology for Development 19, no. 1 (December 10, 2017): 1–16. http://dx.doi.org/10.29037/ajstd.326.

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This paw presents fusion detection technique comparisons based on support vector machine and its variations for a bimodal biometric verification system that makes use of face images and speech utterances. The system is essentially constructed by a face expert, a speech expert and a fusion decision module. Each individual expert has been optimized to operate in automatic mode and designed for security access application. Fusion decision schemes considered are linear, weighted Support Vector Machine (SVM) and linear SVM with quadratic transformation. The conditions tested include the balanced and unbalanced conditions between the two experts in order to obtain the optimum fusion module from these techniques best suited to the target application.

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Bačkalić, Todor, Vladimir Bugarski, Filip Kulić, and Željko Kanović. "Adaptable Fuzzy Expert System for Ship Lock Control Support." Journal of Navigation 69, no. 6 (May 3, 2016): 1341–56. http://dx.doi.org/10.1017/s0373463316000242.

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A ship lock zone represents a specific area on waterway, and control of the ship lockage process requires a comprehensive approach. This research is a practical application of a Mamdani-type fuzzy inference system and particle swarm optimisation to control this process. It presents an optimisation process that adapts control logic to the desired criteria. The initially proposed Fuzzy Expert System (FES) was developed using suggestions from lockmasters (ship lock operators) with extensive experience. Further optimisation of the membership function parameters of the input variables was performed to achieve better results in the local distribution of ship arrivals. The presented fuzzy logic-based expert system was designed as part of a Programmable Logic Controller (PLC) and Supervisory Control And Data Acquisition (SCADA) system to support decision making and control. The developed fuzzy algorithm is a rare application of artificial intelligence in navigable canals and significantly improves performance of the ship lockage process. This adaptable FES is designed to be used as a support in decision-making processes or for the direct control of ship lock operations.

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