Multi-layer perceptron and radial basis function for modeling interstate Conflict

Tshilidzi Marwala, Monica Lagazio

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

This chapter introduces and then compares the multi-layer perceptron neural network to the radial basis function neural network to help understand and predict interstate conflict. These two techniques are described in detail and justified with a review of relevant literature and they are implemented to interstate conflict. The results obtained from the implementation of these techniques demonstrate that the multi-layer perceptron neural network is better at predicting interstate conflict than the radial basis function network. This is mainly due to the cross-coupled chartacteristics of the multi-layer perceptron’s network compared to the radial basis function network.

Original languageEnglish
Title of host publicationAdvanced Information and Knowledge Processing
PublisherSpringer London
Pages43-64
Number of pages22
Edition9780857297891
DOIs
Publication statusPublished - 2011

Publication series

NameAdvanced Information and Knowledge Processing
Number9780857297891
ISSN (Print)1610-3947
ISSN (Electronic)2197-8441

ASJC Scopus subject areas

  • Management Information Systems
  • Information Systems
  • Information Systems and Management
  • Artificial Intelligence

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