Decision making for uncertain data in dynamic environment using hybrid method

摘要: Predicting plays a main role in making good decision dynamic environment with real time data, such as weather predictions that normally are heterogeneous, various and vast. The use of heterogeneous data available causes increasing uncertainty. Vast amount from will be very uncertain the prediction future behavior situation is hard if it possible, result not accurate may lead to incorrect predictions, Therefore, for problem statement we propose new framework called hybrid method based on Fuzzy c-mean clustering Type-2 fuzzy logic system gradient descent algorithm training would applicable environment, able manage outliers noise get more results well. proved usable than (Type-2 FLS).