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Attribute-Value Pair Aim of developing this representation is to reduce the development time especially the transition time between the rule based to the representation employed by the software package utilisation. Attributes are the antecedents/conclusions of the rule Values are the limits imposed on attributes Example: If shahid is of age 5 Then he should go to the school If X < 10 and Y>2 Then Z=3 Lahore University of Management Sciences, Lahore, Pakistan 2 Dr. M.M. Awais- Computer Science Department Attribute-Value Pair Example: Rule R1 R3 R2 R3 R4 R4 R1 R3 R2 R4 R1 R2 R3 R4 if x=5 then z=2 if y=6 then s=1 if x=2 and y=2 then z=2 if s=1 and e=2 then d=7 Clause 1 1 1 2 1 2 3 3 3 3 Lahore University of Management Sciences, Lahore, Pakistan Attribute x x y y s e z z s d 3 Value 5 2 6 2 1 2 2 2 1 7 Dr. M.M. Awais- Computer Science Department Example 1: Waste Disposal R1: R2: R3: R4: If waste origin = source A and waste amount = large Then waste destination = site X If waste origin = source A and waste amount = modest Then waste destination = site Y If waste origin = source B and waste contents = toxic Then waste destination = site Z If waste origin = source B and waste contents = nontoxic Then waste destination = site Y Lahore University of Management Sciences, Lahore, Pakistan 4 Dr. M.M. Awais- Computer Science Department Example 1: Solution of Waste Disposal Lahore University of Management Sciences, Lahore, Pakistan 5 Dr. M.M. Awais- Computer Science Department Example 2: R1: R2: R3: If A = a and B = b Then R = r If A = NOT a and C = c Then S = s If S = s and B = b Then X = x Lahore University of Management Sciences, Lahore, Pakistan 6 Dr. M.M. Awais- Computer Science Department Example 2: Solution Lahore University of Management Sciences, Lahore, Pakistan 7 Dr. M.M. Awais- Computer Science Department Inference Networks Another Graphical Approach Symbols are used to present rules Box: represents assertion/antecedents Circles: represents conclusions Connectives are represented by special symbols Assertion conclusion intermediate conclusion Lahore University of Management Sciences, Lahore, Pakistan 8 and or Dr. M.M. Awais- Computer Science Department Example: R1: R2: If assertion 1 is true and assertion 2 is true Then conclusion 1 is established If assertion 3 is true or assertion 4 is true Then conclusion 2 is established Lahore University of Management Sciences, Lahore, Pakistan 9 Dr. M.M. Awais- Computer Science Department Example : inference Net Lahore University of Management Sciences, Lahore, Pakistan 10 Dr. M.M. Awais- Computer Science Department Example 1: R1: R2: R3: R4: R5: If B and C Then G If A and G Then I If D and G Then J If E or F then H If D and H Then K Lahore University of Management Sciences, Lahore, Pakistan 11 Dr. M.M. Awais- Computer Science Department Example 1: inference Net Lahore University of Management Sciences, Lahore, Pakistan 12 Dr. M.M. Awais- Computer Science Department Neural Networks Neural Networks can be used to represent Knowledge but has a unique way of storing the knowledge Works on the principles of biological neural system Human nervous system contains more than 10 billion neurons These neurons are massively interconnected 1. Dendrites are the parts which receive impulses 2. Axons transmit these impulses 3. Between two neurons is the synaptic junction 4. If the impulse energy is high enough it will jump the synaptic junction and impulse is passed to the next neurons 5. Different Impulses activate the synaptic junction differently 6. Thus knowledge can be stored as a pool of activations that responds to its particular input impulse. Lahore University of Management Sciences, Lahore, Pakistan 13 Dr. M.M. Awais- Computer Science Department Neural Networks Artificial Neural networks have Inputs Outputs Weights that corresponds to dendrites synaptic jump store synaptic activity of different inputs numeric form Lahore University of Management Sciences, Lahore, Pakistan 14 Dr. M.M. Awais- Computer Science Department