Title :
Artificial intelligence for conflict management
Author :
Habtemariam, E. ; Marwala, T. ; Lagazio, M.
Author_Institution :
Sch. of Electr. & Inf. Eng., Univ. of the Witwatersrand, Johannesburg, South Africa
fDate :
July 31 2005-Aug. 4 2005
Abstract :
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.
Keywords :
artificial intelligence; neural nets; social sciences computing; support vector machines; artificial intelligence; conflict management; decision support tool; militarised interstate dispute; neural networks; sensitivity analysis; support vector machines; Africa; Artificial intelligence; Artificial neural networks; Biological neural networks; Machine learning; Neural networks; Probability; Sensitivity analysis; Statistical analysis; Support vector machines;
Conference_Titel :
Neural Networks, 2005. IJCNN '05. Proceedings. 2005 IEEE International Joint Conference on
Conference_Location :
Montreal, Que.
Print_ISBN :
0-7803-9048-2
DOI :
10.1109/IJCNN.2005.1556310