Logic Paper
Part I The Fuzzy Logic concept was created by a man named Lotfi Zadeh in 1960. He was a professor at the University of California. He originally presented Fuzzy Logic as a way of processing data, which would allow partial set memberships rather than crisp set membership or non-membership. Overall Fuzzy logic is a problem solving control system. Fuzzy Logic provides a simple way to arrive at a definite conclusion based upon fuzzy, confusing, imprecise, or missing input information. It helps to calculate intermediate values between 0.0 and 1.0. When using Fuzzy Logic it is possible to calculate the degree to which an item is a member. An example of this would be in a person is .85 of tallness, they would be considered “rather tall.” If you used Fuzzy Logic it would calculate the shades of grey that would be between the black & white and true & false. It was also said that Fuzzy Logic is similar to Boolean Logic in that Boolean Logic results are returned by Fuzzy Logic operations when all fuzzy memberships are restricted to 0 and 1. However Fuzzy Logic differs from Boolean Logic in that it is permissive of natural language queries and it is also more like human thinking. Fuzzy Logic is based more on degrees of truth. Fuzzy Logic results appear similar to probability, but they are different. An example of this would be (Probability Statement ;) “There is a 60% chance that Bobby is tall” Bobby is either tall or not, but there is a 60% chance that we know which set Bobby belongs to. The Fuzzy Logic statement would be that “Bobby’s degree of membership is in the set of tall people which is .70’ supposes that Bobby is rather tall.” The Fuzzy Logic statement determines not only the set in which Bobby belongs but it also says to what degree of membership.
Part II - Examples
1. Washing Machine – the washer would need to know the correct amount of water for the amount of clothes put into it.
2. Dishwasher – the dishwasher would need to know the correct water
Part II - Examples
1. Washing Machine – the washer would need to know the correct amount of water for the amount of clothes put into it.
2. Dishwasher – the dishwasher would need to know the correct water
References: Http://www.mathworks.com/access/helpdesk/toolbox/fuzzy/fp351dup8.html Http://en.wikipedia.org.wiki/Neural_network Fuzzy/Neurofuzzy Logic [online] Neurosciences. Available from internet: < http://www.neurosciences.com/nn_fzy.htm>.