Advancement of Data Analysis, Decision Support System, Data-Driven Modeling on the Eighteenth ICMSEM Proceedings

被引：0
作者：
Xu, Jiuping [1 ]
机构：
[1] Sichuan Univ, Uncertainty Decis Making Lab, Chengdu 610065, Peoples R China
来源：
EIGHTEENTH INTERNATIONAL CONFERENCE ON MANAGEMENT SCIENCE AND ENGINEERING MANAGEMENT, ICMSEM 2024 | 2024年 / 215卷
关键词：
Data analysis; Decision support system; Data-driven modeling;
D O I：
10.1007/978-981-97-5098-6_1
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Management Science (MS) is a discipline that studies how to effectively utilize resources to solve internal organizational problems and optimize decisions. It combines tools from mathematics, statistics, and computer science to help managers make wiser decisions, improve organizational efficiency, and performance. The research fields of management science cover various aspects such as production, operations, project management, aiming to enhance organizational competitiveness and sustainability. This article focuses on MS, briefly describing the first volume of the 18th ICMSEM program. Firstly, it reviews the key research areas of MS: Data Analysis, Decision Support System, Data-driven Modeling. Next, it discusses the most prominent issues in the 18th ICMSEM program volume. Finally, future developments are analyzed using CiteSpace. Overall, ICMSEM continues to provide a valuable platform for academic interaction and exchange to ensure innovation in future Management Science and Engineering Management (MSEM).
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页码：1 / 13
页数：13
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  • [1] Application, adoption and opportunities for improving decision support systems in irrigated agriculture: A review
    Ara, Iffat
    Turner, Lydia
    Harrison, Matthew Tom
    Monjardino, Marta
    deVoil, Peter
    Rodriguez, Daniel
    [J]. AGRICULTURAL WATER MANAGEMENT, 2021, 257
  • [2] Best-compromise solutions for waste management: Decision support system for policymaking
    Boffardi, Raffaele
    De Simone, Luisa
    De Pascale, Angelina
    Ioppolo, Giuseppe
    Arbolino, Roberta
    [J]. WASTE MANAGEMENT, 2021, 121 : 441 - 451
  • [3] Searching for intellectual turning points: Progressive knowledge domain visualization
    Chen, CM
    [J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2004, 101 : 5303 - 5310
  • [4] Data mining techniques for the investigation of the circular economy and sustainability relationship
    Daglis, Theodoros
    Tsironis, Georgios
    Tsagarakis, Konstantinos P.
    [J]. RESOURCES CONSERVATION & RECYCLING ADVANCES, 2023, 19
  • [5] LINEAR PROGRAMMING UNDER UNCERTAINTY
    Dantzig, George B.
    [J]. MANAGEMENT SCIENCE, 1955, 1 (3-4) : 197 - 206
  • [6] Deep learning with long short-term memory networks for financial market predictions
    Fischer, Thomas
    Krauss, Christopher
    [J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2018, 270 (02) : 654 - 669
  • [7] EIA: An algorithm for the statistical evaluation of an environmental impact assessment
    Guisande, Castor
    Rueda-Quecho, Andres J.
    Rangel-Silva, Fabian A.
    Rios-Vasquez, Jorge M.
    [J]. ECOLOGICAL INDICATORS, 2018, 93 : 1081 - 1088
  • [8] Machine learning for environmental monitoring
    Hino, M.
    Benami, E.
    Brooks, N.
    [J]. NATURE SUSTAINABILITY, 2018, 1 (10): : 583 - 588
  • [9] Machine learning applications in cancer prognosis and prediction
    Kourou, Konstantina
    Exarchos, Themis P.
    Exarchos, Konstantinos P.
    Karamouzis, Michalis V.
    Fotiadis, Dimitrios I.
    [J]. COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL, 2015, 13 : 8 - 17
  • [10] A big data approach to assess progress towards Sustainable Development Goals for cities of varying sizes
    Liu, Yu
    Huang, Bo
    Guo, Huadong
    Liu, Jianguo
    [J]. COMMUNICATIONS EARTH & ENVIRONMENT, 2023, 4 (01):
12