By S. Gao
The works offered during this booklet supply insights into the construction of leading edge advancements over set of rules functionality, capability functions on a variety of useful initiatives, and mix of alternative strategies. The publication offers a connection with researchers, practitioners, and scholars in either man made intelligence and engineering groups, forming a beginning for the advance of the sphere.
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Extra resources for Bio-Inspired Computational Algorithms and Their Applns. [appl. math]
0 0 0 15 0 0 0 0 0 1 0 0 0 0 1 The Network Operator Method for Search of the Most Suitable Mathematical Equation ( y = cos q1 x13 ) 3 33 x12 + x22 . Consider the examples of improper variations that change the number of nodes in the T network operator. We have a variation vector w = [ 6 4 7 0 ] . Number of variation w1 = 6 shows that we add the node with binary operation w4 = 0 and an outcoming edge with unary operation w3 = 7 . After variation we obtain the NOM 0 0 0 = w Ψ = 0 Ψ 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 14 2 0 0 0 0 0 2 0 0 0 0 1 0 0 1 7 .
1992). Genetic Programming: On the Programming of Computers by Means of Natural Selection, MIT Press. ISBN 0-262-11170-5. 840 p. R. (1994). Genetic Programming II: Automatic Discovery of Reusable Programs, MIT Press. ISBN 0-262-11189-6. 768 p. ; Andre, D. A. (1999). Genetic Programming III: Darwinian Invention and Problem Solving, Morgan Kaufmann. ISBN 1-55860-543-6. 1154 p. ; Lanza, G. (2003). Genetic Programming IV: Routine Human-Competitive Machine Intelligence, Springer. ISBN 14020-7446-8.
To construct the set of network operators we use a basic matrix Ψ 0 and all possible sets W of variation vectors. 9. Genetic algorithm for method of variations of basic solution Consider genetic algorithm that searches both structure and parameters of mathematical equation. Initially we set the basic solution Ψ 0 = ψ 0ij , i , j = 1, L . (18) We generate the ordered sets of variation vectors ( ) W i = w i ,1 , , w i ,l , i = 1, H , w i , j = w1i , j w2i , j w 3i , j (19) T w 4i , j , i = 1, H , j = 1, l , (20) where H is a number of possible solutions in the population.