Relevant bibliographies by topics / Computer decision support systems

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Computer decision support systems'

Author: Grafiati
Published: 4 June 2021
Last updated: 15 February 2022

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Journal articles on the topic "Computer decision support systems"

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Payne, Thomas H. "Computer Decision Support Systems." Chest 118, no. 2 (August 2000): 47S—52S. http://dx.doi.org/10.1378/chest.118.2_suppl.47s.

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Marković-Blagojević, Marija, Bratislav Mikarić, and Dušan Trajković. "Computer systems as decision support." Trendovi u poslovanju 2, no. 2 (2014): 33–42. http://dx.doi.org/10.5937/trendpos1402033m.

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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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French, Simon, and Murray Turoff. "Decision support systems." Communications of the ACM 50, no. 3 (March 2007): 39–40. http://dx.doi.org/10.1145/1226736.1226762.

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Finlay, Paul N. "Decision support systems." Data Processing 28, no. 8 (October 1986): 434–37. http://dx.doi.org/10.1016/0011-684x(86)90427-2.

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McDonald, Clement J. "Analyzing Computer-based Decision Support Systems." Annals of Internal Medicine 121, no. 6 (September 15, 1994): 469. http://dx.doi.org/10.7326/0003-4819-121-6-199409150-00017.

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Haynes, R. Brian. "Analyzing Computer-based Decision Support Systems." Annals of Internal Medicine 121, no. 6 (September 15, 1994): 469. http://dx.doi.org/10.7326/0003-4819-121-6-199409150-00032.

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Thornett, Andrew Martyn. "Computer decision support systems in general practice." International Journal of Information Management 21, no. 1 (February 2001): 39–47. http://dx.doi.org/10.1016/s0268-4012(00)00049-9.

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Chin, Jerry M. "Using computer algebra in decision support systems." International Journal of Computer Mathematics 45, no. 3-4 (January 1992): 133–43. http://dx.doi.org/10.1080/00207169208804124.

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Ballantine, Malcolm. "Computer-assisted careers guidance systems as decision support systems." British Journal of Guidance and Counselling 14, no. 1 (January 1, 1986): 21–32. http://dx.doi.org/10.1080/03069888600760031.

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Dissertations / Theses on the topic "Computer decision support systems"

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Riabacke, Ari. "Computer based prescriptive decision support." Licentiate thesis, Mid Sweden University, Department of Information Technology and Media, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-5497.

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Geraghty, Peter James. "Computer based decision support systems for environmental assessment." Thesis, University of Liverpool, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.367243.

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Williams, C. Lesley. "A computer-based decision support system for orthodontic diagnosis and treatment planning." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp04/mq21223.pdf.

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Boyd, Richard K. "A weapons systems development decision support system." Thesis, Monterey, Calif. : Naval Postgraduate School, 1992. http://handle.dtic.mil/100.2/ADA251791.

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Thesis (M.S. in Information Systems)--Naval Postgraduate School, March 1992.
Thesis Advisor: Nakagawa, Gordon. "March 1992." Description based on title screen as viewed on March 4, 2009. Includes bibliographical references (p. 66).
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Li, Xiaobo 1976. "Decision support systems using object-oriented technology." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/86539.

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Hamilton-Wright, Andrew. "Transparent Decision Support Using Statistical Evidence." Thesis, University of Waterloo, 2005. http://hdl.handle.net/10012/778.

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An automatically trained, statistically based, fuzzy inference system that functions as a classifier is produced. The hybrid system is designed specifically to be used as a decision support system. This hybrid system has several features which are of direct and immediate utility in the field of decision support, including a mechanism for the discovery of domain knowledge in the form of explanatory rules through the examination of training data; the evaluation of such rules using a simple probabilistic weighting mechanism; the incorporation of input uncertainty using the vagueness abstraction of fuzzy systems; and the provision of a strong confidence measure to predict the probability of system failure.

Analysis of the hybrid fuzzy system and its constituent parts allows commentary on the weighting scheme and performance of the "Pattern Discovery" system on which it is based.

Comparisons against other well known classifiers provide a benchmark of the performance of the hybrid system as well as insight into the relative strengths and weaknesses of the compared systems when functioning within continuous and mixed data domains.

Classifier reliability and confidence in each labelling are examined, using a selection of both synthetic data sets as well as some standard real-world examples.

An implementation of the work-flow of the system when used in a decision support context is presented, and the means by which the user interacts with the system is evaluated.

The final system performs, when measured as a classifier, comparably well or better than other classifiers. This provides a robust basis for making suggestions in the context of decision support.

The adaptation of the underlying statistical reasoning made by casting it into a fuzzy inference context provides a level of transparency which is difficult to match in decision support. The resulting linguistic support and decision exploration abilities make the system useful in a variety of decision support contexts.

Included in the analysis are case studies of heart and thyroid disease data, both drawn from the University of California, Irvine Machine Learning repository.
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Khan, Q. "A computer graphics approach to logistics strategy modelling." Thesis, Cranfield University, 1990. http://dspace.lib.cranfield.ac.uk/handle/1826/4755.

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This thesis describes the development and application of a decision support system for logistics strategy modelling. The decision support system that is developed enables the modelling of logistics systems at a strategic level for any country or area in the world. The model runs on IBM PC or compatible computers under DOS (disk operating system). The decision support system uses colour graphics to represent the different physical functions of a logistics system. The graphics of the system is machine independent. The model displays on the screen the map of the area or country which is being considered for logistic planning. The decision support system is hybrid in term of algorithm. It employs optimisation for allocation. The customers are allocated by building a network path from customer to the source points taking into consideration all the production and throughput constraints on factories, distribution depots and transshipment points. The system uses computer graphic visually interactive heuristics to find the best possible location for distribution depots and transshipment points. In a one depot system it gives the optimum solution but where more than one depot is involved, the optimum solution is not guaranteed. The developed model is a cost-driven model. It represents all the logistics system costs in their proper form. Its solution very much depends on the relationship between all the costs. The locations of depots and transshipment points depend on the relationship between inbound and outbound transportation costs. The model has been validated on real world problems, some of which are described here. The advantages of such a decision support system for the formulation of a problem are discussed. Also discussed is the contribution of such an approach at the validation and solution presentation stages.
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Gudala, Satyaveer Goud. "Skyline queries for multi-criteria decision support systems." Kansas State University, 2011. http://hdl.handle.net/2097/13250.

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Master of Science
Department of Computing and Information Sciences
William H. Hsu
In decision-making applications, the Skyline query is used to find a set of non-dominated data points (called Skyline points) in a multi-dimensional dataset. A data point dominates another data point if it is at least as good as the other data point in all dimensions and better in at least one dimension. The skyline consists of data points not dominated by any other data point. Computing the skyline points of a dataset is essential for applications that involve multi-criteria decision making. Skyline queries filter out the interesting tuples from a potentially large dataset. No matter how we weigh our preferences along the attributes, only those tuples which score best under a monotone scoring function are part of the skyline. In other words, the skyline does not contain tuples which are nobody's favorite. With a growing number of real-world applications involving multi-criteria decision making over multiple dimensions, skyline queries can be used to answer those problems accurately and efficiently. This report mainly focuses on various skyline computing algorithms which can be used for online processing efficiently and are suitable to present multi-criteria decision making scenario. I implemented the Branch-and-Bound skyline Algorithm on two different data sets; one is a synthetic dataset and the other is a real dataset. My aim is to explore various subspaces of a given dataset and compute skylines over them, especially those subspace skylines which contain the least number of the skyline points.
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Fröberg, Joakim. "Engineering Automotive Electronic Systems: Decision Support for Successful Integration." Doctoral thesis, Mälardalen University, Department of Computer Science and Electronics, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-459.

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The electronic system of a modern vehicle is essential to achieve a successful automotive product. Vehicle development is performed by integrating components that include embedded electronics from several suppliers.

This thesis present results on the subject of integration of automotive electronic systems. Our studies aim at providing knowledge on how to integrate automotive electronic systems successfully in a setting where vehicles are developed based on existing platforms. We focus on early phases of automotive electronic system development and in particular on the decisions taken in integration of electronic sub-systems. The contribution is the presented support for making decisions to successfully integrate electronic systems for modern vehicles. The contribution includes an overview of driving factors of automotive electronics system design, a validated set of success practices for the integration of electronic components, and the proposal and demonstration of a decision model. The influential factors and the validated set of practices stems from case studies of products and projects while the proposed decision model is a result of combining two general models for architecture analysis and decision making, ATAM and AHP.

We demonstrate that choices in strategy and design preceding integration are central to achieve a successful integration. Our studies show that problems arise from omitted strategy decisions and we provide a checklist for decision making in the areas; functionality, platform, integration design, and assigning responsibilities. We provide a recommendation that we validate in a multiple cases study where fulfillment of recommendations is demonstrated to affect project success in integration projects.

The potential gain for OEMs using our results lies in achieving more solid foundations for design decisions. Designers and managers could potentially find central decisions on integration strategy early that, if omitted, could cause delays. Thus, applying the result could avoid pitfalls and enable successful integration projects.

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Chi, Chih-Lin Street William N. "Medical decision support systems based on machine learning." Iowa City : University of Iowa, 2009. http://ir.uiowa.edu/etd/283.

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Books on the topic "Computer decision support systems"

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Flavin, P. G. Computer Aided Decision Support in Telecommunications. Dordrecht: Springer Netherlands, 1996.

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Turban, Efraim. Decision support and expert systems: Management support systems. 3rd ed. New York: Macmillan, 1993.

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Turban, Efraim. Decision support and expert systems: Management support systems. 4th ed. London: Prentice-Hall International, 1995.

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Turban, Efraim. Decision support and expert systems: Management support systems. 2nd ed. New York: Macmillan, 1990.

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Decision support and expert systems: Management support systems. 4th ed. Englewood Cliffs, N.J: Prentice Hall, 1995.

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Turban, Efraim. Decision support systems and intelligent systems. 7th ed. New Delhi: Prentice-Hall of India, 2005.

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Miller, Richard Kendall. Survey on decision support systems. Madison, GA: Future Technology Surveys, 1989.

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Leigh, William E. Decision support and expert systems. Cincinnati: South-Western Pub. Co., 1986.

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E, Aronson Jay, and Liang Ting-Peng 1953-, eds. Decision support systems and intelligent systems. 7th ed. Upper Saddle River, NJ: Pearson Prentice-Hall, 2005.

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E, Aronson Jay, and Liang Ting-Peng 1953-, eds. Decision support systems and intelligent systems. 7th ed. Upper Saddle River, New Jersey: Prentice Hall, 2005.

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Book chapters on the topic "Computer decision support systems"

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Georgakakos, Aris P. "Computer-Aided Management of the Southeastern U.S. Reservoir System." In Decision Support Systems, 407–28. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-76048-8_19.

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Loucks, Daniel P. "Computer-Aided Support for Water Resources Research and Planning." In Decision Support Systems, 173–88. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-76048-8_7.

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Loucks, Daniel P., and João R. da Costa. "Computer-Aided Decision Support in Water Resources Planning and Management." In Decision Support Systems, 3–41. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-76048-8_1.

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Müller, Neitherd, and H. Herman Hahn. "The German Water Authorities Needs for Computer-Aided Support Systems." In Decision Support Systems, 295–304. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-76048-8_13.

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Soncini-Sessa, R., C. Gandolfi, A. Nardini, and A. Kraszewski. "Computer-Aided Water Reservoir Management: A Prototype Two-Level DSS." In Decision Support Systems, 527–74. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-76048-8_24.

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Orlob, G. T., A. E. Bale, M. Malagoli, and H. Rajbhandari. "Computer Graphics for Assessment of Eutrophication Venice Lagoon: A Case Study." In Decision Support Systems, 471–84. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-76048-8_22.

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Dijkman, Jos, and Rob Klomp. "Current Trends in Computer-Aided Water Resources Management at Delft Hydraulics." In Decision Support Systems, 201–49. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-76048-8_9.

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Barritt-Flatt, Paul E. "Implementing a Computer-Aided Support System for Water Resources Research and Management." In Decision Support Systems, 87–96. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-76048-8_3.

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Andreu, J., J. Capilla, and E. Sanchis. "AQUATOOL: A Computer-Assisted Support System for Water Resources Research Management Including Conjunctive Use." In Decision Support Systems, 333–55. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-76048-8_15.

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Walker, Susan. "Computer-Aided Water Resources Planning and Operational Management in a Water Company in the U.K." In Decision Support Systems, 305–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-76048-8_14.

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Conference papers on the topic "Computer decision support systems"

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Gerson, Michael, I. S. Chien, and Vasant Raval. "Computer assisted decision support systems." In the 1992 ACM SIGCPR conference. New York, New York, USA: ACM Press, 1992. http://dx.doi.org/10.1145/144001.144051.

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Encheva, Sylvia, Yuriy Kondratenko, Maryna Z. Solesvik, Sharil Tumin, Theodore E. Simos, and George Psihoyios. "Decision Support Systems in Logistics." In INTERNATIONAL ELECTRONIC CONFERENCE ON COMPUTER SCIENCE. AIP, 2008. http://dx.doi.org/10.1063/1.3037065.

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Ullman, David G., and Bruce D’Ambrosio. "A Taxonomy for Classifying Engineering Decision Problems and Support Systems." In ASME 1995 Design Engineering Technical Conferences collocated with the ASME 1995 15th International Computers in Engineering Conference and the ASME 1995 9th Annual Engineering Database Symposium. American Society of Mechanical Engineers, 1995. http://dx.doi.org/10.1115/detc1995-0197.

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Abstract The design of even the simplest product requires thousands of decisions. Yet very few of these decisions are supported with methods on paper or on computers. Is this because engineering design decisions don’t need support or is it because techniques have yet to be developed that are usable on a wide basis? In considering this question a wide range of decision problem characteristics need to be addressed. In engineering design some decisions are made by individuals, others by teams — some are about the product and others about the processes that support the product — some are based on complete, consistent, quantitative data and others on sparse, conflicting, qualitative discussions. In order to address the reasons why so little support is used and the characteristics of potentially useful decision support tools, a taxonomy of decision characteristics is proposed.1 This taxonomy is used to classify current techniques and to define the requirements for an ideal engineering design decision support system.
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Herling, Derald, David G. Ullman, and Bruce D’Ambrosio. "Engineering Decision Support System (EDSS)." In ASME 1995 Design Engineering Technical Conferences collocated with the ASME 1995 15th International Computers in Engineering Conference and the ASME 1995 9th Annual Engineering Database Symposium. American Society of Mechanical Engineers, 1995. http://dx.doi.org/10.1115/detc1995-0196.

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Abstract Engineers, as well as other decision makers, are required to make many decisions as they are designing a product or resolving a problem. At these decision points there are many alternatives and criteria to be considered. Studies of design sessions show that most decisions made during these times are in an ad hoc manner. Greater understanding of the mechanical design process, data representation for collaborative design and probabilistic inferences have allowed the creation of a computer decision support program, called Engineering Decision Support System (EDSS), that addresses the special needs of design engineers.1 This paper introduces this work, which is still in the developmental stages.
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Averweg, Udo Richard. "CSFs for decision-making support systems." In the 2010 Annual Research Conference of the South African Institute of Computer Scientists and Information Technologists. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1899503.1899561.

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LIN, Hsuan-Hung, Po-Chou CHAN, Ming-Huei LEE, Yung-Fu CHEN, Yung-Kuan CHAN, Wei-Sheng CHUNG, and Dah-Jye LEE. "Decision Support Systems for Predicting Erectile Dysfunction." In International Conference on Computer Networks and Communication Technology (CNCT 2016). Paris, France: Atlantis Press, 2017. http://dx.doi.org/10.2991/cnct-16.2017.83.

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Asghar, Sohail, Simon Fong, and Rukhsana. "A Contemplation of Group Decision Support Systems." In 2009 Fourth International Conference on Computer Sciences and Convergence Information Technology. IEEE, 2009. http://dx.doi.org/10.1109/iccit.2009.316.

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"Decision Support System for Urban Service Failures." In International conference on Computer Science and Information Systems. International Institute of Engineers, 2014. http://dx.doi.org/10.15242/iie.e1014045.

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Kurakin, Pavel V., George G. Malinetskii, Sergey A. Makhov, and Nikolai A. Mitin. "MATLAB - Based software for decision support systems." In 2014 International Conference on Computer Technologies in Physical and Engineering Applications (ICCTPEA). IEEE, 2014. http://dx.doi.org/10.1109/icctpea.2014.6893295.

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Kozielski, Michał, Marek Sikora, and Łukasz Wróbel. "DISESOR - decision support system for mining industry." In 2015 Federated Conference on Computer Science and Information Systems. IEEE, 2015. http://dx.doi.org/10.15439/2015f168.

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Reports on the topic "Computer decision support systems"

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Wang, Zuyi. A Computer-Based Decision Support System for Breast Cancer Diagnosis. Fort Belvoir, VA: Defense Technical Information Center, September 2001. http://dx.doi.org/10.21236/ada398377.

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Luo, Lan. A Computer-Based Decision Support System for Breast Cancer Diagnosis. Fort Belvoir, VA: Defense Technical Information Center, September 1999. http://dx.doi.org/10.21236/ada384615.

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Wang, Zuyi. A Computer-Based Decision Support System for Breast Cancer Diagnosis. Fort Belvoir, VA: Defense Technical Information Center, September 2000. http://dx.doi.org/10.21236/ada393462.

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Roth, Steven F., and Stephen F. Smith. Intelligent Support for Human Computer Interaction and Decision-Making in Distribution Planning and Scheduling Systems. Fort Belvoir, VA: Defense Technical Information Center, February 1993. http://dx.doi.org/10.21236/ada263985.

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Sexton, Porter. A computer decision support system to assist in providing equality of educational opportunity. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.795.

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Jones, David W., Max H. Miller, James A. Ballas, and Janet I. Olsonbaker. Analysis of Human-Computer Interaction in the Expeditionary Warfare Decision Support System (EDSS). Fort Belvoir, VA: Defense Technical Information Center, September 2004. http://dx.doi.org/10.21236/ada427048.

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Armstrong, Kartina. Development of a Computer Decision Support System for Women With BRCA1 of BRCA2 Mutations. Fort Belvoir, VA: Defense Technical Information Center, August 2003. http://dx.doi.org/10.21236/ada421257.

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Armstrong, Katrina. Development of a Computer Decision Support System for Women with BRCA1 and BRACA2 Mutations. Fort Belvoir, VA: Defense Technical Information Center, August 2000. http://dx.doi.org/10.21236/ada393401.

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Ohno-Machado, Lucila. FACTS (Find Appropriate Clinical Trials) for You: A Computer-Based Decision Support System for Breast Cancer Patients. Fort Belvoir, VA: Defense Technical Information Center, May 2002. http://dx.doi.org/10.21236/ada408466.

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Ohno-Machado, Lucila. FACTS (Find the Appropriate Clinical Trials) for You: A Computer-Based Decision Support System for Breast Cancer Patients. Fort Belvoir, VA: Defense Technical Information Center, May 1999. http://dx.doi.org/10.21236/ada381179.

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