Literatura académica sobre el tema "Decision-making management system"
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Artículos de revistas sobre el tema "Decision-making management system"
Do, Myungsik. "Development of the Decision-Making System for National Highway Pavement Management". Journal of the Korean Society of Civil Engineers 34, n.º 2 (2014): 645. http://dx.doi.org/10.12652/ksce.2014.34.2.0645.
Texto completoKOZLOVA, Valeria. "ECONOMIC DIAGNOSTICS IN THE SYSTEM OF INFORMATION SUPPORT FOR MANAGEMENT DECISION-MAKING". Herald of Khmelnytskyi National University. Economic sciences 312, n.º 6(2) (29 de diciembre de 2022): 196–201. http://dx.doi.org/10.31891/2307-5740-2022-312-6(2)-33.
Texto completoZubovа, Lyudmila V., Eduard Viktorovich Korovin, Alexey Sergeevich Smirnov, Vladimir N. Kuzmin y Andrey Valerievich Kurakov. "Development of Problem-Oriented Management and Decision-Making System and Optimization of Economic and Social Systems". Webology 18, SI05 (30 de octubre de 2021): 436–51. http://dx.doi.org/10.14704/web/v18si05/web18239.
Texto completoGibney, Lisa A., Scott E. Hansen y Walter E. Wright, CEM. "Emergency management: Consequence management decision making". Journal of Emergency Management 2, n.º 4 (1 de octubre de 2004): 36. http://dx.doi.org/10.5055/jem.2004.0043.
Texto completoAda, Şükrü y Mohsen Ghaffarzadeh. "Decision Making Based On Management Information System and Decision Support System". European Researcher 93, n.º 4 (15 de marzo de 2015): 260–69. http://dx.doi.org/10.13187/er.2015.93.260.
Texto completoBalaban, Edward, Stephen B. Johnson y Mykel J. Kochenderfer. "Unifying System Health Management and Automated Decision Making". Journal of Artificial Intelligence Research 65 (7 de agosto de 2019): 487–518. http://dx.doi.org/10.1613/jair.1.11366.
Texto completoYu., Tararico y Lukashuk V. "Intellectual decision-making technology in agricultural production". Artificial Intelligence 27, jai2022.27(1) (20 de junio de 2022): 219–28. http://dx.doi.org/10.15407/jai2022.01.219.
Texto completoChen, Yi Lin. "Risk Decision-Making System in Manufacture Enterprise Management". Advanced Materials Research 694-697 (mayo de 2013): 3592–95. http://dx.doi.org/10.4028/www.scientific.net/amr.694-697.3592.
Texto completoAwulor, Rita Ifeyinwa, Rhino Obi-Mallam y Nnnena Mary Chukwu. "Enhancing organisational decision-making through management information system". Journal of Global Social Sciences 3, n.º 11 (1 de septiembre de 2022): 115–33. http://dx.doi.org/10.31039/jgss.v3i11.71.
Texto completoBarr, Thomas R. "Critical Decision Making: The Decision to Deploy a Clinical Management System". Journal of Oncology Practice 1, n.º 2 (julio de 2005): 71–74. http://dx.doi.org/10.1200/jop.2005.1.2.71.
Texto completoTesis sobre el tema "Decision-making management system"
Костюченко, Надія Миколаївна, Надежда Николаевна Костюченко, Nadiia Mykolaivna Kostiuchenko, Денис Олегович Смоленніков, Денис Олегович Смоленников y Denys Olehovych Smolennikov. "Institutional decision-making in environmental management system". Thesis, Вид-во СумДУ, 2010. http://essuir.sumdu.edu.ua/handle/123456789/8144.
Texto completoRezgui, Abdelkerim [Verfasser]. "Decision Evaluation System : Towards Sustainable Decision-Making / Abdelkerim Rezgui". Aachen : Shaker, 2018. http://d-nb.info/1188550578/34.
Texto completoTang, Yu-wen S. M. Massachusetts Institute of Technology. "Tradespace as a decision making tool in bioprocess design". Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/107362.
Texto completoCataloged from PDF version of thesis.
Includes bibliographical references (pages 80-83).
The field of systems engineering upholds that fundamental engineering principles exist and are applicable across different domains and contexts. In this thesis, a state-of-the art decision and design evaluation method developed for aerospace systems, Multi-Attribute Tradespace Exploration (MATE) is complemented with Design of Experiments (DoE) and applied for the first time to a bioprocess design problem. The implementation of DoE was necessary due to the high complexity of bioprocess systems, where a design variable (or a reasonably small number of design variables) cannot be easily identified to explain a given attribute of the product or process. DoE not only allows the identification of design variables that most influence a given attribute, but also allows the development of Single-Utility-Functions facilitating the incorporation of the Multi- Utility component of the MATE method. The proposed new MATE-DoE method was implemented in two case studies to assess its applicability; namely bio-production of DHA and bio-production of a lipase enzyme. Based on published DoE experimental results, utility functions and cost estimations were carried out to develop a Tradespace. The resulting Tradespace demonstrates: (a) the possible implementation of the proposed method, (b) that the use of Tradespace complements the traditional bioprocess development practice by allowing decision makers to choose an architecture that optimizes for more than one objective (multi-objective), (c) that the proposed method takes into consideration the complex decision making process of customers (multi-attribute), and (d) that simultaneous comparison analysis to competitors and market standards are possible using the method. While the method was proven to be applicable, it is relatively complex and the number of experiments and market data required might prevent its broad implementation. Also, potential errors and misleading results might result from inaccurate input data. Special attention and effort need to be put in accurate Single-Utility Function (SUF) weight designation to avoid this problem. The importance of assessing the complete bioprocess, as opposed to individual unit operations, is highlighted. Finally, further studies to develop "rules of thumb" in order to simplify the proposed MATE-DoE method is suggested.
by Yu-wen Tang.
S.M. in Engineering and Management
Devine, Paul (Paul S. ). "Reliability improvement project decision making : water cooling system redesign". Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/35114.
Texto completoIncludes bibliographical references (p. 66).
Deciding on which reliability & performance improvement projects to launch or to reject has historically been an extremely challenging responsibility of Teradyne management. Incorrect decisions can lead to major customer dissatisfaction, which may subsequently lead to loss of market share. Teradyne Engineering and Marketing team have been trying to develop a tool that would assist in their reliability improvement project decision making. The challenge is the dynamic aspects of the reliability improvement projects. Like most engineering projects, reliability improvement projects have variables such as internal workforce, productivity, skill sets, customer expectations and many others that are in constant motion. These variables make the assessment of reliability projects extremely difficult in a static framework. This research will incorporate these key variables into a dynamic framework to help assess individual reliability improvement projects.
by Paul Devine.
S.M.
Chacon, Vince. "Executive decision making processes and outcomes : structure and robustness". Thesis, Massachusetts Institute of Technology, 2003. http://hdl.handle.net/1721.1/29536.
Texto completoIncludes bibliographical references (p. 48).
Uncertainty in the decision making environment complicates the decision making process because future events may change the effect of a particular decision or series of decisions. This thesis explores the possibility of applying robust engineering design techniques to the decision making process in order to limit the effects of changing circumstances. The intent is to identify solutions that will reduce the variation in the outcome of decisions that are made across many projects by analyzing projects that have been executed at the Dryden Flight Research Center (DFRC) over the past several years. A framework to relate past performance to match the requirements of experiments in a Design of Experiments (DOE) analysis is developed. The approach views factors that are considered in making decisions as controllable elements and factors that unexpectedly affect the outcome of the decisions as noise. The resulting framework is then organized such that the data can be analyzed using the Taguchi approach to DOE, which has been successfully used for analyzing engineering design and manufacturing processes. The analysis approach considers the robustness of the outcome based on the factors used to make the decisions about the various projects that have been conducted at DFRC over the past six years. The decision process performance is analyzed and recommendation are made to improve the performance of the decision making process at DFRC. The analysis indicates that projects providing large increases in technical knowledge were the most influential in reducing the effects from changes in budget and staffing resources that were beyond the control of the decision makers.
by Vince Chacon.
S.M.
Nilekar, Shirish K. "A system-oriented analysis of team decision making in data rich environments". Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/90698.
Texto completoCataloged from PDF version of thesis.
Includes bibliographical references (pages 78-80).
The information processing view of organizations [1] and subsequent works highlight the primary role of information processing in the effective functioning of markets and organizations. With the current wave of "big data" and related technologies, data-oriented decision making is being widely discussed [2] as a means of using this vast amount of available data for better decisions which can lead to improved business results. The focus of many of these studies is at the organization level. However, decisions are made by teams of individuals and this is a complex socio-technical process. The quality of a decision depends on many factors including technical capabilities for data analysis and human factors like team dynamics, cognitive capabilities of the individuals and the team. In this thesis, we developed a systems theory based framework for decision making and identified four socio technical factors viz., data analytics, data sensing, power distribution, and conflict level which affect the quality of decisions made by teams. We then conducted "thought experiments" to investigate the relative contribution of each of these factors to the quality of decisions. Our experiments and subsequent analyses show that while improved data analytics does result in better decisions, human factors have an out-sized contribution to the quality of decisions, even in data rich environments. Moreover, when the human factors in a team improve, the predictability of the positive impacts due to improvements in technical capabilities of the team also increases.
by Shirish K. Nilekar.
S.M. in Engineering and Management
Wang, Ming-hua. "A knowledge-based system approach for project management decision-making support". Thesis, University of Warwick, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.340476.
Texto completoQueiroz, Vieira Turnell M. de F. "A decision making aid system based on a small microprocessor". Thesis, University of Bradford, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.379855.
Texto completoXu, Hua S. M. Massachusetts Institute of Technology. "A system approach to augment clinical decision-making using machine learning". Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/121803.
Texto completoCataloged from PDF version of thesis.
Includes bibliographical references (pages 76-80).
This thesis helps find limits within which automated methods can support and surpass the capabilities of medical professionals and the limits beyond which these methods are not yet adequate. This will inform later exploration about (a) what improvements in data collection, interpretation, and visualization will enhance technology's capacity and (b) what changes clinicians can make to improve their decision making-augmented or not. This thesis includes (a) describing clinical decisions, informed by literature and clinical case studies and (b) reviewing current capabilities of machine methods. This led to (c) a test experiment-how to use data about a particular condition (e.g. in-hospital mortality rate prediction) from a particular source (the MIMIC III data base). The results will help define current limits on augmenting clinical decisions and establish direction for future work including more demanding experiments.
Artificial Intelligence (AI) includes Machine Learning (ML), Natural Language Processing (NLP), Computer Vision, Speech Recognition, and Robotics. As an important branch of Al, ML builds statistical models to learn from sample data, known as "training", identifies patterns, and makes predictions based on new data, known as "inference." In this way, ML is useful in rationalizing and predicting in uncertain environments, with minimum human interventions. Decision making is central to the healthcare practice, with many decisions made under conditions of uncertainty. Clinicians must integrate a huge variety of data while pressured to decrease diagnostic uncertainties and risks to patients. Deciding what information to gather, which test to order, how to interpret and integrate this information to draw diagnostic conclusions, and which treatments to give are essential.
In typical situations, clinicians evaluate patient symptoms and potential disease patterns, confirmed by a variety of tests, and they initiate treatments based on their experience and customary practice. This is complicated when multiple illnesses coexist, the illness may be rare, the information may be conflicting, or prior interventions may affect the presenting symptoms.
by Hua Xu.
S.M. in Engineering and Management
S.M.inEngineeringandManagement Massachusetts Institute of Technology, System Design and Management Program
Barton, John Edward Built Environment Faculty of Built Environment UNSW. "A spatial decision support system for the management of public housing". Awarded by:University of New South Wales, 2007. http://handle.unsw.edu.au/1959.4/35209.
Texto completoLibros sobre el tema "Decision-making management system"
Nadia, Nedjah y Macedo Mourelle Luiza de, eds. Real-world multi-objective system engineering. New York: Nova Science, 2005.
Buscar texto completoMancini, Daniela. Accounting Information Systems for Decision Making. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.
Buscar texto completoBrailsford, Sally, Leonid Churilov y Brian Dangerfield, eds. Discrete-Event Simulation and System Dynamics for Management Decision Making. Chichester, UK: John Wiley & Sons Ltd, 2014. http://dx.doi.org/10.1002/9781118762745.
Texto completoWilimowska, Zofia, Leszek Borzemski, Jerzy Świątek y Adam Grzech. Information systems architecture and technology: System analysis in decision aided problems. Wrocław: Wrocław University of Technology, 2009.
Buscar texto completoFlood, Robert L. Liberating systems theory. New York: Plenum Press, 1990.
Buscar texto completoManaging with systems thinking: Making dynamics work for you in business decision making. London: McGraw-Hill, 1994.
Buscar texto completoWang, Ming-hua. A knowledge-based system approach for project management decision-making support. [s.l.]: typescript, 1997.
Buscar texto completoW, Morecroft John D., Sanchez Ron y Heene Aimé, eds. Systems perspectives on resources, capabilities, and management processes. Amsterdam: Pergamon, 2002.
Buscar texto completoV, Gheorghe Adrian y SpringerLink (Online service), eds. Quality Decision Management - The Heart of Effective Futures-Oriented Management: A Primer for Effective Decision-Based Management. Dordrecht: Springer Netherlands, 2009.
Buscar texto completoCoplin, William D. Power persuasion: A surefire system to get ahead in business. Reading, Mass: Addison-Wesley, 1985.
Buscar texto completoCapítulos de libros sobre el tema "Decision-making management system"
Lenhard, Raymond E. "Data Management in Clinical Decision Making". En A Clinical Information System for Oncology, 22–38. New York, NY: Springer New York, 1989. http://dx.doi.org/10.1007/978-1-4612-3638-2_2.
Texto completoMartin, Arnaud, Pascale Zarate y Guy Camillieri. "A Multi-Criteria Recommender System Based on Users’ Profile Management". En Multiple Criteria Decision Making, 83–98. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-39292-9_5.
Texto completoPohl, Edward. "System Reliability". En Decision Making in Systems Engineering and Management, 227–72. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2010. http://dx.doi.org/10.1002/9780470926963.ch8.
Texto completoDelgado-Álvarez, Carlos A. y Yris Olaya-Morales. "Modeling Disaster Operations Management Problems with System Dynamics". En Decision-making in Humanitarian Operations, 223–48. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91509-8_10.
Texto completoDriscoll, Patrick J. y Paul Kucik. "System Life Cycle". En Decision Making in Systems Engineering and Management, 65–93. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2010. http://dx.doi.org/10.1002/9780470926963.ch3.
Texto completoGröwe-Kuska, Nicole, Krzysztof C. Kiwiel, Matthias P. Nowak, Werner Römisch y Isabel Wegner. "Power Management in a Hydro-Thermal System under Uncertainty by Lagrangian Relaxation". En Decision Making Under Uncertainty, 39–70. New York, NY: Springer New York, 2002. http://dx.doi.org/10.1007/978-1-4684-9256-9_3.
Texto completoJablonský, Josef. "Decision Support System for Management of Patient Nutrition: An Interactive AHP/Goal Programming Approach". En Multiple Criteria Decision Making, 135–48. New York, NY: Springer New York, 1992. http://dx.doi.org/10.1007/978-1-4612-2918-6_11.
Texto completoGuzmán Cortés, Diana Carolina, Leonardo José González Rodríguez y Carlos Franco. "Collaborative Strategies for Humanitarian Logistics with System Dynamics and Project Management". En Decision-making in Humanitarian Operations, 249–73. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91509-8_11.
Texto completoKanatas, P., I. Travlos, A. Tataridas y I. Gazoulis. "Decision-Making and Decision Support System for a Successful Weed Management". En Information and Communication Technologies for Agriculture—Theme III: Decision, 159–79. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-84152-2_8.
Texto completoJakubeit, N., M. Rajabalinejad, A. J. J. Braaksma y L. A. M. van Dongen. "Collaborative Decision-Making Challenges in the Dutch Railway System". En Complex Systems Design & Management, 193. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-34843-4_18.
Texto completoActas de conferencias sobre el tema "Decision-making management system"
Yong Sun, Lin Ma, Warwick Robinson y Colin Fidge. "Using decision trees in economizer repair decision making". En 2010 Prognostics and System Health Management Conference (PHM). IEEE, 2010. http://dx.doi.org/10.1109/phm.2010.5414571.
Texto completoRosanty, Elvira Soufyani, Halina Mohamed Dahlan y Ab Razak Che Hussin. "Multi-Criteria Decision Making for Group Decision Support System". En 2012 International Conference on Information Retrieval & Knowledge Management (CAMP). IEEE, 2012. http://dx.doi.org/10.1109/infrkm.2012.6205015.
Texto completoIntezari, Ali, David J. Pauleen y Nazim Taskin. "The DIKW Hierarchy and Management Decision-Making". En 2016 49th Hawaii International Conference on System Sciences (HICSS). IEEE, 2016. http://dx.doi.org/10.1109/hicss.2016.520.
Texto completoAlfajri, I., A. Ali y N. N. Al-Zaid. "Information Management System to Improve Decision Making Efficiency". En SPE Kuwait Oil and Gas Show and Conference. Society of Petroleum Engineers, 2015. http://dx.doi.org/10.2118/175406-ms.
Texto completoTang, Hong y Lindu Zhao. "Knowledge Management System of Intercity Emergency Decision Making". En 2009 WRI World Congress on Software Engineering. IEEE, 2009. http://dx.doi.org/10.1109/wcse.2009.232.
Texto completoWei-bing Liu y Min Li. "Dynamic decision making in social security system". En 2011 International Conference on Management Science and Industrial Engineering (MSIE). IEEE, 2011. http://dx.doi.org/10.1109/msie.2011.5707509.
Texto completo"Session 6.2 — Decision-making & maintainability". En 2012 Prognostics and System Health Management Conference (PHM). IEEE, 2012. http://dx.doi.org/10.1109/phm.2012.6228924.
Texto completoYaohui Zhang, Xiaohai Han, Shixin Zhang y Shaohua Wang. "Decision-making methods of condition-based maintenance". En 2015 Prognostics and System Health Management Conference (PHM). IEEE, 2015. http://dx.doi.org/10.1109/phm.2015.7380098.
Texto completoGorelov, M. A. "Decision Making with Abundance of Information". En 2020 13th International Conference Management of large-scale system development (MLSD). IEEE, 2020. http://dx.doi.org/10.1109/mlsd49919.2020.9247780.
Texto completoMikštienė, Ruta y Violeta Keršulienė. "Legal decision support system application possibility in corporate governance". En Business and Management 2016. VGTU Technika, 2016. http://dx.doi.org/10.3846/bm.2016.39.
Texto completoInformes sobre el tema "Decision-making management system"
Barber, D. S., D. L. Brockman y L. D. Buxton. Integrated Services Management System (ISMS): A management and decision making tool. Office of Scientific and Technical Information (OSTI), octubre de 1995. http://dx.doi.org/10.2172/120884.
Texto completoKappes, Sandra F., Simon S. Kim, Patrick J. Tanner, Roddy J. Williams y Louis F. Cohn. Employing Expert System Technologies to Real Property Management Decision making. Fort Belvoir, VA: Defense Technical Information Center, julio de 1990. http://dx.doi.org/10.21236/ada226176.
Texto completoBuyak, Bogdan B., Ivan M. Tsidylo, Victor I. Repskyi y Vitaliy P. Lyalyuk. Stages of Conceptualization and Formalization in the Design of the Model of the Neuro-Fuzzy Expert System of Professional Selection of Pupils. [б. в.], noviembre de 2018. http://dx.doi.org/10.31812/123456789/2669.
Texto completoLagutin, Andrey y Tatyana Sidorina. SYSTEM OF FORMATION OF PROFESSIONAL AND PERSONAL SELF-GOVERNMENT AMONG CADETS OF MILITARY INSTITUTES. Science and Innovation Center Publishing House, diciembre de 2020. http://dx.doi.org/10.12731/self-government.
Texto completoSeale, Maria, Natàlia Garcia-Reyero, R. Salter y Alicia Ruvinsky. An epigenetic modeling approach for adaptive prognostics of engineered systems. Engineer Research and Development Center (U.S.), julio de 2021. http://dx.doi.org/10.21079/11681/41282.
Texto completoCallaghan, Caitlin, Matthew Bigl, Brandon Booker, Kyle Elliott, Paulina Lintsai, Marissa Torres, Kathryn Trubac y Jacqueline Willan. Energy Atlas—mapping energy-related data for DoD lands in Alaska : Phase 1—assembling the data and designing the tool. Engineer Research and Development Center (U.S.), octubre de 2021. http://dx.doi.org/10.21079/11681/42226.
Texto completoCallaghan, Caitlin, Matthew Bigl, Brandon Booker, Kyle Elliott, Paulina Lintsai, Marissa Torres, Kathryn Trubac y Jacqueline Willan. Energy Atlas—mapping energy-related data for DoD lands in Alaska : Phase 1—assembling the data and designing the tool. Engineer Research and Development Center (U.S.), octubre de 2021. http://dx.doi.org/10.21079/11681/42226.
Texto completoRuiz de Gauna, Itziar, Anil Markandya, Laura Onofri, Francisco (Patxi) Greño, Javier Warman, Norma Arce, Alejandra Navarrete et al. Economic Valuation of the Ecosystem Services of the Mesoamerican Reef, and the Allocation and Distribution of these Values. Inter-American Development Bank, mayo de 2021. http://dx.doi.org/10.18235/0003289.
Texto completoBrinkerhoff, Derick W., Sarah Frazer y Lisa McGregor-Mirghani. Adapting to Learn and Learning to Adapt: Practical Insights from International Development Projects. RTI Press, enero de 2018. http://dx.doi.org/10.3768/rtipress.2018.pb.0015.1801.
Texto completoLempert, Robert J., Michelle Miro y Diogo Prosdocimi. A DMDU Guidebook for Transportation Planning Under a Changing Climate. Editado por Benoit Lefevre y Ernesto Monter Flores. Inter-American Development Bank, febrero de 2021. http://dx.doi.org/10.18235/0003042.
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