Artificial intelligence for conflict management

被引:0
|
作者
Habtemariam, E [1 ]
Marwala, T [1 ]
Lagazio, M [1 ]
机构
[1] Univ Witwatersrand, Sch Elect & Informat Engn, Johannesburg, South Africa
来源
PROCEEDINGS OF THE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), VOLS 1-5 | 2005年
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Militarised conflict is one of the risks that have a significant impact on society. Militarised Interstate Dispute (MID) is defined as an outcome of interstate interactions which result on either peace or conflict. Effective prediction of the possibility of conflict between states is an important decision support tool for policy makers. In a previous research, neural networks (NNs) have been implemented to predict the MID. Support Vector Machines (SVMs) have proven themselves to be very good prediction techniques and are introduced for the prediction of MIDs in this study. The results found show that SVM predicts MID better than NN while NN gives more consistent and easy to interpret sensitivity analysis results than SVM.
引用
收藏
页码:2583 / 2588
页数:6
相关论文
共 50 条
  • [21] Artificial intelligence (AI) and management analytics
    Haenlein, Michael
    Kaplan, Andreas
    Tan, Chee-Wee
    Zhang, Pengzhu
    JOURNAL OF MANAGEMENT ANALYTICS, 2019, 6 (04) : 341 - 343
  • [22] Glaucoma management in the era of artificial intelligence
    Devalla, Sripad Krishna
    Liang, Zhang
    Tan Hung Pham
    Boote, Craig
    Strouthidis, Nicholas G.
    Thiery, Alexandre H.
    Girard, Michael J. A.
    BRITISH JOURNAL OF OPHTHALMOLOGY, 2020, 104 (03) : 301 - 311
  • [23] Knowledge Management and Artificial Intelligence (AI)
    Jallow, Haddy
    Renukappa, Suresh
    Suresh, Subashini
    PROCEEDINGS OF THE 21ST EUROPEAN CONFERENCE ON KNOWLEDGE MANAGEMENT (ECKM 2020), 2020, : 363 - 369
  • [24] Artificial Intelligence Application in Modern Management
    Jiang, Rong
    ADVANCES IN ENGINEERING DESIGN AND OPTIMIZATION, PTS 1 AND 2, 2011, 37-38 : 203 - 206
  • [25] Artificial Intelligence in The Management of Neurodegenerative Disorders
    Dhankhar, Sanchit
    Mujwar, Somdutt
    Garg, Nitika
    Chauhan, Samrat
    Saini, Monika
    Sharma, Prerna
    Kumar, Suresh
    Sharma, Satish Kumar
    Kamal, Mohammad Amjad
    Rani, Nidhi
    CNS & NEUROLOGICAL DISORDERS-DRUG TARGETS, 2024, 23 (08) : 931 - 940
  • [26] Artificial intelligence in electrostatic risk management
    Gulyas, Attila
    Kiss, Istvan
    Berta, Istvan
    JOURNAL OF ELECTROSTATICS, 2013, 71 (03) : 387 - 391
  • [27] Preface: artificial intelligence in operations management
    Wamba, Samuel Fosso
    Queiroz, Maciel M.
    Braganza, Ashley
    ANNALS OF OPERATIONS RESEARCH, 2022, 308 (1-2) : 1 - 6
  • [28] The role of artificial intelligence in knowledge management
    Tsui, E
    Garner, BJ
    Staab, S
    KNOWLEDGE-BASED SYSTEMS, 2000, 13 (05) : 235 - 239
  • [29] Preface: artificial intelligence in operations management
    Samuel Fosso Wamba
    Maciel M. Queiroz
    Ashley Braganza
    Annals of Operations Research, 2022, 308 : 1 - 6
  • [30] Editorial Artificial Intelligence and Innovation Management
    Tanev, Stoyan
    Sandstrom, Gregory
    TECHNOLOGY INNOVATION MANAGEMENT REVIEW, 2019, 9 (12): : 3 - 4