On Generalized Measures of Entropy for Fuzzy Sets

A probability distribution may have uncertainty. Now the question arises how to measure the uncertainty that exists within the probability distribution. Shannon developed the basic idea related to entropy in the year 1948. Later on, this concept extended by Zadeh. According to Zadeh the concept to measure the uncertainty of an event of statement having specific doubtfulness or it may depends linguistic variables. There are various application used in everyday life related to entropy measure such as cloud computing application, pattern recognition, traffic signal processing, interpersonal communication etc. Keeping in view of the above new generalized measure of entropy developed for fuzzy sets with its proof of validity. During this development phase, few of the properties of the measure has also been discussed. Graphical representations are also used to verify the measure with different values of parameters.