Thematische Bibliographien / Decision support systems

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Auswahl der wissenschaftlichen Literatur zum Thema „Decision support systems“

Autor: Grafiati

Veröffentlicht am 4. Juni 2021

Zuletzt aktualisiert am 30. Juli 2024

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Zeitschriftenartikel zum Thema "Decision support systems"

B verstam, U. „Decision Support and Decision Support Systems“. Radiation Protection Dosimetry 73, Nr. 1 (01.09.1997): 1–6. http://dx.doi.org/10.1093/oxfordjournals.rpd.a032107.

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Fedkova, Nadezhda Alexandrovna, und Sergey Sergeevich Chudakov. „DECISION SUPPORT SYSTEMS“. Vestnik obrazovatel'nogo konsortsiuma Srednerusskii universitet. Informatsionnye tekhnologii, Nr. 2 (2021): 23–26. http://dx.doi.org/10.52374/15269658_2021_18_2_23.

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Olsen, Christopher R., und William C. Bozeman. „Decision Support Systems“. Journal of Research on Computing in Education 20, Nr. 3 (März 1988): 206–12. http://dx.doi.org/10.1080/08886504.1988.10781835.

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Fralic, Maryann F. „Decision support systems“. Nursing Administration Quarterly 14, Nr. 1 (1989): 1–8. http://dx.doi.org/10.1097/00006216-198901410-00003.

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O'Sullivan, Elizabethann. „Decision Support Systems“. Evaluation Review 9, Nr. 1 (Februar 1985): 84–92. http://dx.doi.org/10.1177/0193841x8500900105.

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French, Simon, und Murray Turoff. „Decision support systems“. Communications of the ACM 50, Nr. 3 (März 2007): 39–40. http://dx.doi.org/10.1145/1226736.1226762.

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Wyatt, J. „Decision Support Systems“. Yearbook of Medical Informatics 02, Nr. 01 (August 1993): 325–27. http://dx.doi.org/10.1055/s-0038-1637983.

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Fieschi, M. „Decision-Support Systems“. Yearbook of Medical Informatics 03, Nr. 01 (August 1994): 315–17. http://dx.doi.org/10.1055/s-0038-1638008.

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Heathfield, Heather A. „Decision Support Systems“. Yearbook of Medical Informatics 04, Nr. 01 (August 1995): 455–57. http://dx.doi.org/10.1055/s-0038-1638034.

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Suermondt, H. J. „Decision-Support Systems“. Yearbook of Medical Informatics 05, Nr. 01 (August 1996): 367–70. http://dx.doi.org/10.1055/s-0038-1638061.

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Dissertationen zum Thema "Decision support systems"

Alkarouri, Muhammad Abdulmuneim. „Distributed decision support systems“. Thesis, University of Sheffield, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.555644.

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Decision support systems are a class of computer based systems that assist in some or all levels of decision making within an organisation. Recently, the growth of data captured that is useful or even critical to the successful running or conclusion of projects in science and industry has been remarkable. Thus, the development of decision support systems that are scalable in terms of the size of data processed. the number of stakeholders, and their geographical span has become of the essence. This thesis identifies the issues in developing distributed decision support systems. Building on that. an architectural style for the development of scalable and extensible software systems is introduced. Subsequently, a framework for the design of distributed decision support systems is developed. This new architectural style is the Resource Oriented Services Architecture (ROSA). It builds on Representational State Transfer (REST), an architectural style that describes the venerable design of the world wide web. An architectural design based on REST revolves around resources, representations, and hyperlinks. \Vhat it lacks is a standardised way to represent computations as resources in a scalable and extensible manner. For systems that cannot be adequately described as a web of documents, this is a shortcoming. ROSA overcomes this by defining a means of representing executable resources in a manner that is consistent with the statelessness and cacheability constraints of REST. The resulting architecture enables the scalability of the system. Additionally, desirable features such as dynamic discovery of resources and extensibility and loose coupling are attained. To illustrate this framework, two new learning algorithms are introduced and implemented as services. The first is a data structure suitable for proximity queries over large datasets of low intrinsic dimension. The other uses a random projection to carry out novelty detection over high dimensional datasets.

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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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Sandhu, Raghbir Singh. „Intelligent spatial decision support systems“. Thesis, University College London (University of London), 1998. http://discovery.ucl.ac.uk/1317911/.

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This thesis investigates the conceptual and methodological issues for the development of Intelligent Spatial Decision Support Systems (ISDSS). These are spatial decision support systems (SDSS) integrating intelligent systems techniques (Genetic Algorithms, Neural Networks, Expert Systems, Fuzzy Logic and Nonlinear methods) with traditional modelling and statistical methods for the analysis of spatial problems. The principal aim of this work is to verify the feasibility of heterogeneous systems for spatial decision support derived from a combination of traditional numerical techniques and intelligent techniques in order to provide superior performance and functionality to that achieved through the use of traditional methods alone. This thesis is composed of four distinct sections: (i) a taxonomy covering the employment of intelligent systems techniques in specific applications of geographical information systems and SDSS; (ii) the development of a prototype ISDSS; (iii) application of the prototype ISDSS to modelling the spatiotemporal dynamics of high technology industry in the South-East of England; and (iv) the development of ISDSS architectures utilising interapplication communication techniques. Existing approaches for implementing modelling tools within SDSS and GIS generally fall into one of two schemes - loose coupling or tight coupling - both of which involve a tradeoff between generality and speed of data interchange. In addition, these schemes offer little use of distributed processing resources. A prototype ISDSS was developed in collaboration with KPMG Peat Marwick's High Technology Practice as a general purpose spatiotemporal analysis tool with particular regard to modelling high technology industry. The GeoAnalyser system furnishes the user with animation and time plotting tools for observing spatiotemporal dynamics; such tools are typically not found in existing SDSS or GIS. Furthermore, GeoAnalyser employs the client/server model of distributed computing to link the front end client application with the back end modelling component contained within the server application. GeoAnalyser demonstrates a hybrid approach to spatial problem solving - the application utilises a nonlinear model for the temporal evolution of spatial variables and a genetic algorithm for calibrating the model in order to establish a good fit for the dataset under investigation. Several novel architectures are proposed for ISDSS based on existing distributed systems technologies. These architectures are assessed in terms of user interface, data and functional integration. Implementation issues are also discussed. The research contributions of this work are four-fold: (i) it lays the foundation for ISDSS as a distinct type of system for spatial decision support by examining the user interface, performance and methodological requirements of such systems; (ii) it explores a new approach for linking modelling techniques and SDSS; (iii) it investigates the possibility of modelling high technology industry; and (iv) it details novel architectures for ISDSS based on distributed systems.

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Randall, Todd Andrew. „Decision support for suburban retrofitting /“. *McMaster only, 2001.

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Argile, Andrew Duncan Stuart. „Distributed processing in decision support systems“. Thesis, Nottingham Trent University, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.259647.

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Woerlee, Auke Peter. „Decision support systems of production scheduling /“. Rotterdam : Erasmus universiteit, 1991. http://catalogue.bnf.fr/ark:/12148/cb37438055v.

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Proefschrift--Rotterdam--Erasmus universiteit, 1991.
Mention parallèle de titre ou de responsabilité : Beslissingsondersteunende systemen voor korte termijn produktieplanning. Résumé en néerlandais, 4 p. Ill. par l'auteur. Bibliogr. p. 151-165. Index.

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Hodgkin, Julie. „Provision of intelligent user support in decision support systems“. Thesis, University of Strathclyde, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.366908.

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Kubik, Charles Paul. „Using commercial aviation information systems in operational support airlift decision support systems“. Thesis, Monterey, California. Naval Postgraduate School, 2004. http://hdl.handle.net/10945/1397.

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Approved for public release; distribution is unlimited
scheduling solutions for routing aircraft, crews and logistical support needed to successfully operate in this new environment. The opportunity exists for the DoD's private aircraft operation, the Joint Operational Support Airlift Center (JOSAC), to utilize some of the same system features used in commercial operations such as NetJets to improve operations. This thesis will analyze the use of commercial air operator strategies and DSS's to be used in JOSAC to improve operational effectiveness. It will look to add new capabilities and processes used in commercial DSS's along with the implementation of the disruptive technology, microjets. Some of the potential benefits include improved operational performance, solutions to scheduling inefficiencies and improved mission readiness. With these improvements the potential for a military microjet operation in the future is a real possibility.
1st Lieutenant, United States Air Force

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Farrall, Rhys. „Brine management strategies for desalination systems: Decision support system“. Thesis, Farrall, Rhys (2021) Brine management strategies for desalination systems: Decision support system. Honours thesis, Murdoch University, 2021. https://researchrepository.murdoch.edu.au/id/eprint/63768/.

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This thesis explores and evaluates a decision support system (DDS) for the management of desalination brine. The rapid uptake of desalination technologies to meet freshwater demands has led to producing a significant quantity of brine, which is a highly saline solution. Currently, the most popular brine management method in Western Australia (WA) is disposal by surface water discharge (into the ocean), deep-well injection or evaporation ponds. Brine disposal isn’t a long-term sustainable option due to the environmental impacts it can cause, such as salinisation. Brine treatment methods that reduce the liquid volume of brine partially or completely brine is still under development or aren’t currently economically viable. The DDS uses two multi-criteria analysis techniques, interval analytical hierarchy process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) under hybrid information. The use of interval AHP gives decision-makers a reliable method of assigning appropriate weightings to the chosen criteria, using the relative importance between each criterion. The DDS uses TOPSIS to allow for different information types (crisp numbers, interval numbers, fuzzy triangular numbers representing linguistic terms) within the DDS. To showcase the DDS, a case study using 4 emerging brine treatment technologies, membrane distillation (MD), forward osmosis (FO), osmotically-assisted reverse osmosis (OARO) and eutectic freeze crystallisation (EFC) was developed. The results suggest that the most to least appropriate technology are MD. FO, EFC and OARO. Sensitivity analyses using a Monte Carlo simulation determined the influence of varying different criteria weightings on the TOPSIS process. MD was the most dominant appropriate technology with little confusion between FO, which was consistently ranked 2nd. Sensitivity analysis of the entire DDS requires further validation of the interval AHP.

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Van, Dyk Theron Van Zyl. „Decision support systems for solving discrete multicriteria decision making problems“. Master's thesis, University of Cape Town, 1992. http://hdl.handle.net/11427/14300.

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Includes bibliography.
The aim of this study was the design and implementation of an interactive decision support system, assisting a single decision maker in reaching a satisfactory decision when faced by a multicriteria decision making problem. There are clearly two components involved in designing such a system, namely the concept of decision support systems (DSS) and the area of multicriteria decision making (MCDM). The multicriteria decision making environment as well as the definitions of the multicriteria decision making concepts used, are discussed in chapter 1. Chapter 2 gives a brief historical review on MCDM, highlighting the origins of some of the more well-known methods for solving MCDM problems. A detailed discussion of interactive decision making is also given. Chapter 3 is concerned with the DSS concept, including a historical review thereof, a framework for the design of a DSS, various development approaches as well as the components constituting a decision support system. In chapter 4, the possibility of integrating the two concepts, MCDM and DSS, are discussed. A detailed discussion of various methodologies for solving MCDM problems is given in chapter 5. Specific attention is given to identifying the methodologies to be implemented in the DSS. Chapter 6 can be seen as a theoretical description of the system developed, while Chapter 7 is concerned with the evaluation procedures used for testing the system. A final summary and concluding remarks are given in Chapter 8.

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Bücher zum Thema "Decision support systems"

Loucks, Daniel P., und João R. da Costa, Hrsg. Decision Support Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-76048-8.

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Efraim, Turban, und Watkins Paul R, Hrsg. Decision support systems. [Amsterdam]: Elsevier Science Publishers, 1987.

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Brännback, Malin. Strategic decisions and decision support systems. Åbo: Åbo Akademis förlag, 1996.

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Moreno-Jiménez, José María, Isabelle Linden, Fatima Dargam und Uchitha Jayawickrama, Hrsg. Decision Support Systems X: Cognitive Decision Support Systems and Technologies. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-46224-6.

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Davis, Michael W. Applied decision support. Englewood Cliffs, N.J: Prentice Hall, 1988.

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Sànchez-Marrè, Miquel. Intelligent Decision Support Systems. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-87790-3.

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Greco, Salvatore, Vincent Mousseau, Jerzy Stefanowski und Constantin Zopounidis, Hrsg. Intelligent Decision Support Systems. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-96318-7.

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Berner, Eta S., Hrsg. Clinical Decision Support Systems. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-31913-1.

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Wallace, Mark. Building Decision Support Systems. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-41732-1.

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Parsaei, Hamid R., Sai Kolli und Thomas R. Hanley, Hrsg. Manufacturing Decision Support Systems. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4613-1189-8.

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Buchteile zum Thema "Decision support systems"

Nir, Dov. „Expert Systems for Agricultural Water Systems“. In Decision Support Systems, 461–69. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-76048-8_21.

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Phillips-Wren, Gloria, Manuel Mora und Guisseppi Forgionne. „Assessing Today: Determining the Decision Value of Decision Support Systems“. In Decision Support, 203–20. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-6181-5_11.

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Eom, Sean. „The Intellectual Structure of Decision Support Systems Research (1991–2004)“. In Decision Support, 49–68. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-6181-5_3.

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Salles, Maryse. „Decision Support Systems“. In Decision-Making and the Information System, 43–88. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2015. http://dx.doi.org/10.1002/9781119102663.ch2.

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Zopounidis, Constantin, und Michael Doumpos. „Decision Support Systems“. In Intelligent Decision Aiding Systems Based on Multiple Criteria for Financial Engineering, 37–82. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4663-4_2.

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Crossland, Martin D. „Decision Support Systems“. In Encyclopedia of GIS, 1. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-23519-6_269-2.

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Walterscheid, Heinz. „Decision Support Systems“. In Effektivität computergestützter Management-Entscheidungsprozesse, 21–59. Wiesbaden: Deutscher Universitätsverlag, 1996. http://dx.doi.org/10.1007/978-3-322-97723-6_3.

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Filip, Florin Gheorghe, Constantin-Bălă Zamfirescu und Cristian Ciurea. „Decision Support Systems“. In Automation, Collaboration, & E-Services, 31–69. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47221-8_2.

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Smith, William. „Decision Support Systems“. In Systems Building with Oracle, 376–407. London: Macmillan Education UK, 2004. http://dx.doi.org/10.1007/978-0-230-00094-0_16.

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Crossland, Martin D. „Decision Support Systems“. In Encyclopedia of GIS, 460. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-17885-1_269.

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Konferenzberichte zum Thema "Decision support systems"

Chen, Man-kuen S., Chui-fat C. Chau und Waldo C. Kabat. „Decision support systems“. In the 1985 ACM annual conference. New York, New York, USA: ACM Press, 1985. http://dx.doi.org/10.1145/320435.320586.

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Loyko, A. O., und S. A. Gusev. „Decision Support Systems“. In the 2019 10th International Conference. New York, New York, USA: ACM Press, 2019. http://dx.doi.org/10.1145/3345035.3345081.

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Aggarwal, Anil. „A Taxonomy of Sequential Decision Support Systems“. In 2001 Informing Science Conference. Informing Science Institute, 2001. http://dx.doi.org/10.28945/2382.

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Advances in information technology and explosion of internet technology is creating new professional users, across and within countries. These users are looking at technology to provide decision support for non-recurring tasks, to provide prototyping capabilities and to provide research support. However, organizational decision environment is also changing, creating havoc for system builders who must match changing technology to changing decision environment. This paper focuses on one such technology, namely, Decision Support System (DSS) and one such decision environment, namely, sequential decisions. It is argued that the next millennium DSS must focus on the 'D' of DSS because of the complexities of the decisions they are trying to support. These DSSs, called SDSSs, are further examined in the context of data-dialog-model- communication. Communication component is needed because of the complexity of sequential decision-making which spans across several hierarchical levels or involves several decision makers at the same level.

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Boukhayma, Khaoula, und Abdellah ElManouar. „Evaluating decision support systems“. In 2015 15th International Conference on Intelligent Systems Design and Applications (ISDA). IEEE, 2015. http://dx.doi.org/10.1109/isda.2015.7489263.

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KACPRZYK, JANUSZ. „DECISION MAKING, DECISION PROCESSES AND DECISION SUPPORT SYSTEMS“. In Proceedings of the MS'10 International Conference. WORLD SCIENTIFIC, 2010. http://dx.doi.org/10.1142/9789814324441_0002.

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Ullman, David G., und 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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Lausberg, Carsten, und Patrick Krieger. „Decisions, decision-making, and decision support systems in real estate investment management“. In 22nd Annual European Real Estate Society Conference. European Real Estate Society, 2015. http://dx.doi.org/10.15396/eres2015_215.

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Taktak, A. F. G., A. Eleuteri, S. P. Lake und A. C. Fisher. „Decision support systems in cancer“. In 4th IET International Conference on Advances in Medical, Signal and Information Processing (MEDSIP 2008). IEE, 2008. http://dx.doi.org/10.1049/cp:20080451.

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Encheva, Sylvia, Yuriy Kondratenko, Maryna Z. Solesvik, Sharil Tumin, Theodore E. Simos und 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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Gerson, Michael, I. S. Chien und 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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Berichte der Organisationen zum Thema "Decision support systems"

Bostick, K. V. Decision support system to select cover systems. Office of Scientific and Technical Information (OSTI), Februar 1995. http://dx.doi.org/10.2172/10116819.

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Sorensen, H. B., John S. Park und Jr. Instructional Systems Development Decision Support. Fort Belvoir, VA: Defense Technical Information Center, November 1990. http://dx.doi.org/10.21236/ada228052.

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Grevet, Jean-Louis M., und Alexander H. Levis. Coordination in Organizations with Decision Support Systems. Fort Belvoir, VA: Defense Technical Information Center, Juli 1988. http://dx.doi.org/10.21236/ada197951.

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Gurney, John O., Marsh Jr., Wauchope Elaine und Kenneth. Focus of Attention in Decision Support Systems. Fort Belvoir, VA: Defense Technical Information Center, Mai 1995. http://dx.doi.org/10.21236/ada294037.

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Hawgood, John. Formal 'Systems Languages' in Decision Support Systems for Military Commanders. Fort Belvoir, VA: Defense Technical Information Center, Juni 1986. http://dx.doi.org/10.21236/ada169673.

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Kennedy, John C., Piyush Sabharwall, Shannon M. Bragg-Sitton, Konor L. Frick, Patrick McClure und D. V. Rao. Special Purpose Application Reactors: Systems Integration Decision Support. Office of Scientific and Technical Information (OSTI), September 2018. http://dx.doi.org/10.2172/1475413.

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Hirsch, Gary B., Jack Homer, Brooke N. Chenoweth, George A. Backus und David R. Strip. Behavior-aware decision support systems : LDRD final report. Office of Scientific and Technical Information (OSTI), November 2007. http://dx.doi.org/10.2172/934860.

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Mowrer, H. Todd, Klaus Barber, Joe Campbell, Nick Crookston, Cathy Dahms, John Day, Jim Laacke et al. Decision support systems for ecosystem management: An evaluation of existing systems. Ft. Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Forest and Range Experiment Station, 1997. http://dx.doi.org/10.2737/rm-gtr-296.

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Smirnov, Alexander, Tatiana Levashova, Nikolay Teslya und Michael Pashkin. Decision Support in Socio-cyber-physical Systems: Conceptual Framework and Decision Making Stages. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, Oktober 2019. http://dx.doi.org/10.7546/crabs.2019.10.10.

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Riedel, Sharon L. User Acceptance and Field Implementation of Decision Support Systems. Fort Belvoir, VA: Defense Technical Information Center, Mai 1988. http://dx.doi.org/10.21236/ada200412.

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