1. A method of predicting a future occurrence of an event, the method comprising the steps of: obtaining a history of past occurrences of the event; creating a plurality of variables associated with the event, including a geographic location of the event; assigning a weight to each variable; creating an artificial neural network; and training the artificial neural network with the history of past occurrences of the event to predict the future occurrence of the event, including the steps— applying the variables, including the geographic location of the event, to the artificial neural network for each past occurrence of the event, comparing an output of the network with each past occurrence of the event, and adjusting the weights of the variables such that the output of the network corresponds to each past occurrence of the event.