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Handling uncertain knowledge is a very tricky problem in the current world as the data, we deal with, is uncertain, incomplete and even inconsistent. Finding an efficient intelligent framework for this kind of knowledge is a challenging task. The knowledge based framework can be represented by a rule based system that depends on a set of rules which deal with uncertainness in the data. Fuzzy rough rules are a good competitive in dealing with the uncertain cases. They are consisted of fuzzy rough variables in both the propositions and consequences. The fuzzy rough variables represent the lower and upper approximations of the subsets of a fuzzy variable. These fuzzy variables use labels (fuzzy subsets) instead of values. An efficient fuzzy rough rule based system must depend on good and accurate rules. This system needs to be enhanced to view the future recommendations or in other words the system in time sequence. This paper tries to make a rule based system for uncertain knowledge using fuzzy rough theory to generate the desired accurate rules and then use fuzzy cellular automata parallel system to enhance the rule based system developed and find out what the system would look like in time sequence so as to give good recommendations about the system in the future. The proposed model along with experimental results and simulations of the rule based systems of different data sets in time sequence is illustrated. rules which handle the linguistic world's problems. The hybridization between fuzzy system and various soft computing techniques is a very interesting search topic these days. Hybridizations like fuzzy rough, fuzzy neural, fuzzy genetic algorithms and many others are very powerful in dealing with uncertain knowledge in linguistic form away from the complicated mathematical calculations of probabilities. The fuzzy rough hybrid(28) is very interesting in the field of building equivalence classes with soft boundaries and degrees of membership of the objects inside these classes. Another interesting mechanism is the fuzzy cellular automata (11) . It is a parallel processing system that is composed of a set of interconnected cells. These systems can be used efficiently to build a grid of rules in time sequence based on initial if-then rules produced from a soft computing rule generating technique. This could be very helpful for experts on the field of the data set under consideration as they need to see what the system would look like in the future. So the cellular automata can be used to enhance the rule based system to reduce the error rate or examine in which variable direction the knowledge discovered goes.

A Fuzzy Rough Rule Based System Enhanced By Fuzzy Cellular Automata