Application of Artificial Neural Networks (ANNs) in Prediction Models in Risk Management

Due to lack of confidence, the process of decision making and planning is a difficult task. Various tools are available to help decision-makers and planners as well as risk management methods for prediction and planning. Being aware of the period and intensity of a phenomenon is the keystone of dealing with critical events in risk management, knowing that the relationships among involved factors are non-linear and complex. Regarding the weak points of traditional methods to solve such problems, in recent years, researches have been conducted on possible use of methods refer to Artificial Intelligence (AI). One of the methods considered as AI is artificial neural network method (ANN). The nerve cell functions, fuzzy logic, approximate inference and genetic algorithm mutation are modeled by ANN. The Zayandeh-rud watershed, located in central part of Iran, due to its climatic and geographical condition is considered as one of the region with occurrence potential of flood and drought. In this study, an artificial neuron perceptron network with 4 hidden layers was formed. The most important part is correctly selection of input data especially when the series data have high variance. Applied ANN for a part this catchment shows that the use of modern techniques, such as artificial neural networks, can provide an appropriate calculation and accurate enough prediction of such events in the region to reduce flood and dough risks its importance in water management.