This work describes the use of Fuzzy knowledge rule base technique to predict the objects contained in atmospheric temperature and wind speed. Fuzzy Petri nets are used for classification of data with linguistic variables.

In fields such as economy, agriculture, weather etc., forecasting plays an important role as it predicts a way to vague situations and events. Weather prediction plays a crucial role as it provides about Weather condition which is a main aspect in the field of agriculture. In this work, Fuzzy knowledge rule base technique is used to predict the objects contained in atmospheric temperature and wind speed. Fuzzy Petri nets are used for classification of data with linguistic variables.

This paper, deals with fundamental notions in pure and applied sciences, i.e., basic operations related to fuzzy relations. The composition of fuzzy relations are defined in two ways such as max-min composition and max-product composition with suitable example. This paper also introduces the properties of composition of fuzzy relations. The newly introduced properties inculcates zero, identity, equal, not-equal, subset, associative, union, intersection and distributive fuzzy relations. Finally, the paper verifies the properties of composition of fuzzy relations using some numerical values for 2x2 order of matrix. Also gives some exercise problems related to the above concepts with accurate answer keys.