By analyzing the results, I was able to see that it is quite hard to model a fire. There is only one thing that a user might want during a situation in which he/she is requesting information regarding a fires path: what should we do next? Therefore, though it may degrade accuracy by a small bit, certain factors can be excluded. The research indicated that though even the smallest change can affect the big picture, there is a point when a user can say that the results are “close enough.”

That is one of the reasons that a precision option was incorporated into the program so if a user wanted the program to be able to detect the status of every square inch or every 50 square feet.

Other conclusions that were made were regarding effective ways to model a fire. Now that I look at the method I used to model the fire, I see that it was probably the best way for this project and it is probably an achievable method for even a larger project regarding the topic. The method allows for the many factors to communicate effectively with each other and the driving method, which is important because many of the factors are related. For example, the amount of rain falling is highly related to the relative humidity.