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Multi-layer Perceptron and Radial Basis Function for Modeling Interstate Conflict

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Book cover Militarized Conflict Modeling Using Computational Intelligence

Part of the book series: Advanced Information and Knowledge Processing ((AI&KP))

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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.

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  1. University of Johannesburg, Johannesburg, South Africa

    Tshilidzi Marwala & Dr. Monica Lagazio

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  1. Tshilidzi Marwala
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Marwala, T., Lagazio, M. (2011). Multi-layer Perceptron and Radial Basis Function for Modeling Interstate Conflict. In: Militarized Conflict Modeling Using Computational Intelligence. Advanced Information and Knowledge Processing. Springer, London. https://doi.org/10.1007/978-0-85729-790-7_3

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