This kind of models can't <i>predict</i> when the attack will happened. They are only useful to <i>estimate</i> the frequency of the attacks. (I din't check the original paper, so perhaps the model is not even good for that.)<p>For example, it is possible to predict the eclipses with a very high precision (the exact day, hour, ...), years before it happens.<p>But it is impossible to predict when or where will be the hurricanes of the next month. It is possible to get an estimation of the number of the hurricanes in a region, but impossible to get the exact number or dates.
I was initially concerned that the release of the model would diminish its efficacy but it seems the authors have already taken this possibility into consideration.<p>From the conclusion of the actual paper:<p>"One might argue that analyses of this kind are useless once publicly known, because they can be invalidated by insurgents’ free will. However, we believe this will not happen for the same reason that all commuters know that a traffic jam will appear every day at rush hour on a certain route, yet many still end up joining it. External constraints of working hours, school schedules, and finite numbers of direct roads mean that such predictability is hard to avoid. Similarly, the spontaneity of fatal attacks by an insurgency is probably constrained by many factors, including the availability of troop convoys, explosive materials, and sympathy within the local population."
Ancient literature can predict floods, lumberjack says.<p>My point is, I'm skeptical of a physicists' insight into the psychology of insurgents that would give this model any legitimacy in terms of making accurate future predictions, rather than just modeling past data. The former requires a lot more faith.
This model predicts when an insurgent attack may occur. I wonder if there is anything similar that could be used to predict where with enough precision to be useful.