I don't think it would be harmful for them to give a clue about what algorithms they use. There is so much tuning required to get these algorithms to perform the way you'd expect that I think they could still keep their IP locked up even if they gave a general hint.
With that said, I'll speculate as well:
Perhaps you'd need some type of ideal dataset, one that included departure times/arrivals and distances and weather conditions of flights that came in on time as expected. Then you might start introducing some noisy data, ie. flights that made the same trip but came in late or early with same weather conditions. Then you'd add in the effect of weather conditions and see how flights fared. I'd speculate that you could get away with doing some type of regression analysis, but maybe you'd need to resort to a more complex algorithm for classifying ("On-time", "Early", "Late") based on a series of features ("Distance","Weather","Mechanical", "Time", etc). SVM could pull this off, or perhaps even a naive bayesian classifier. For research purposes I'd probably check out RVM because it might need less information to classify. Not sure if it would be realistic to use it though...this problem is in need of a highly scalable solution.
With that said, I'll speculate as well: Perhaps you'd need some type of ideal dataset, one that included departure times/arrivals and distances and weather conditions of flights that came in on time as expected. Then you might start introducing some noisy data, ie. flights that made the same trip but came in late or early with same weather conditions. Then you'd add in the effect of weather conditions and see how flights fared. I'd speculate that you could get away with doing some type of regression analysis, but maybe you'd need to resort to a more complex algorithm for classifying ("On-time", "Early", "Late") based on a series of features ("Distance","Weather","Mechanical", "Time", etc). SVM could pull this off, or perhaps even a naive bayesian classifier. For research purposes I'd probably check out RVM because it might need less information to classify. Not sure if it would be realistic to use it though...this problem is in need of a highly scalable solution.