Predicting Suicide Attacks: A Fuzzy Soft Set Approach
  This paper models a decision support system to predict the occurance of
suicide attack in a given collection of cities. The system comprises two parts.
First part analyzes and identifies the factors which affect the prediction.
Admitting incomplete information and use of linguistic terms by experts, as two
characteristic features of this peculiar prediction problem we exploit the
Theory of Fuzzy Soft Sets. Hence the Part 2 of the model is an algorithm vz.
FSP which takes the assessment of factors given in Part 1 as its input and
produces a possibility profile of cities likely to receive the accident. The
algorithm is of O(2^n) complexity. It has been illustrated by an example solved
in detail. Simulation results for the algorithm have been presented which give
insight into the strengths and weaknesses of FSP. Three different decision
making measures have been simulated and compared in our discussion.
