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User fatigue reduction by an absolute rating data-trained predictor in IEC, Proceedings of IEEE Congress on Evolutionary Computation, pp. 2195-2200, IEEE Press 44 Evolutionary Computation Wei, W. (2004). ; et al. (2005). Phase estimations of individual’s fitness based on NN in interactive genetic algorithms. Control and Decision, 20, 234-236 3 A Genetic Algorithm for Optimizing Hierarchical Menus Shouichi Matsui and Seiji Yamada Central Research Institute of Electric Power Industry & National Institute of Informatics Japan 1.
1. X j P xj X i P x j xi xi Xi xj xiP N x j xi Xj x x Fig. 1. X i dominates over X j in interval If ∃x" ∈ X j , ∋: x" ∈ Xi , and ∃x' ∈ Xi , ∋: x' ∈ X j , then we call that X i and X j is incomparable in interval, and denote Xi || X j , which is shown as Fig. 2. X jx x x jP xi j N i Xi x Fig. 2. 3 Fuzzy numbers A fuzzy number is a number with fuzzy meaning. g. “about 10“, “close to 48“, “around 95“. It is easy to observe that a fuzzy number is usually composed of a fuzzy operator and an accurate (or a precise) number.
39 Interactive Genetic Algorithms with Individual’s Uncertain Fitness We then run the system based on IGA-IFF 8 times independently, and calculate ∑σ (x,t) x and ∑ c(x, t) in each generation. Their averages of the 8 runs are shown as Fig. 9. x generations 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 sum of width of interval fitness 5012 4970 4075 3791 3854 3067 2997 2373 2647 2707 2071 1925 1797 1577 1173 sum of midpoints of interval fitness 4100 4404 4437 4265 4870 5167 5411 5268 5031 5923 5966 6148 6264 6629 6611 Table 2.