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Extra info for Advanced Intelligent Computing Theories and Applications: 6th International Conference on Intelligent Computing, ICIC 2010, Changsha, China, August 18-21, 2010. Proceedings
These test cases include various types (linear, nonlinear and quadratic) of objective functions with different number of decision variables and a range of types (linear inequalities, nonlinear equalities, and nonlinear inequalities) and number of constraints. These 8 problems pose a challenge for constraint-handling methods and are a good measure of testing their ability. HGPS performs 30 independent runs for each test function. The number of fitness function evaluations (FFEs) is fixed to 180 000.
Y. Gan  For each feature j , Random Forests is used to train a classifier h j ( x i ) . a) b) c) For i = 1, ⋅⋅⋅, K , a vector θi is generated. Use CART algorithm to construct tree h( x,θi ) . Each tree casts 1 vote for the most popular class at x , the class at x is predicted by selecting the class with max votes. Return a hypothesis h j ( x) .  Update the weights wt +1, i = wt , i β t1− e i where e i = 0 if example (4) xi is classified correctly, otherwise, e i = 1 . β t = εt 1− ε . t  The final strong classifier is ⎧ ⎪1, H ( x) = ⎨ ⎪0, ⎩ where α t = log 1 βt T 1 T α t h t ( x) ≥ ∑ α t ∑ 2t t =1 =1 (5) others .
Proceedings of The IEEE 87(9), 1423–1447 (1999) 13. : Enabling Autonomic Behavior in Systems Software with Hot Swapping. IBM Systems Journal (2003) 14. : Toward Autonomic Computing: Adaptive Neural Network for Trajec-tory Planning. International Journal of Cognitive Informatics and Natural Intelligence 1, 16–33 (2007) 15. : Optimizing Feed Forward Artificial Neural Network Architecture. Engineering Applications of Artificial Intelligence 20, 365–382 (2007) 16. : Decision Making in Autonomic Manager using Fuzzy Inference System.