| dc.description.abstract | A Fuzzy Cognitive Map (FCM) is a soft computing method used to analyze and
understand complex systems. This is particularly useful when there is a little
information known about the system or no historical data is available to make a
reasonable prediction about the future outcome of the underlying system. This study
focuses on the development of a fuzzy cognitive map to predict the risk of malaria
outbreak (RMO) in a particular region based on the impact of 15 different factors
classified as environmental factors, demographic factors, socioeconomic factors and
human habitual factors (EDSH). The results show that the system converges to the
same equilibrium point regardless of how the initial conditions are chosen. This study
is very effective when exact numerical data is not available, especially, during the
initial stage of malaria transmission. Therefore, using the knowledge and experience
of experts properly, this study can be of great help to public health authorities to
make a reasonable prediction of the risk of malaria outbreak.
Highlights
• 1. This article develops a fuzzy cognitive map to predict the risk of malaria
outbreak based on 16 factors categorized into environmental, demographic,
socioeconomic, and human habitual factors.
• 2. This study considers a group of five experts to determine the interconnections
and to assign the corresponding weights to each interconnection.
• 3. The sigmoid function is used to determine the value of concepts in each
iteration.
• 4. The FCM model converges to a consistent equilibrium point irrespective of
initial condition. | en_US |
