(2007). Generative learning of visual concepts using multiobjective genetic programming, Pattern Recognition Letters 28: 2385-2400.Krzysztof Krawiec. Generative learning of visual concepts using multiobjective genetic programming. Pattern Recognition Letters, 28(16):2385-2400, 1 Decem- ber 2007....
A niche in genetic algorithms is a group of points that are close to each other, typically in the criterion space. Niche techniques (also called niche schemes, niche mechanism, or the niche-formation method) are methods for ensuring that a set of designs does not converge to a niche. Thus...
The sequential quadratic programming was used for the optimization problem. Riddle et al. [10] solved the shape optimization problem of a missile by using a genetic algorithm method. The predictions of aerodynamic coefficients were obtained by using both AERODSN routine and Missile DATCOM software ...
Multiple Instance Learning with Genetic Programming for Web Mining This paper introduces a multiobjective grammar based genetic programming algorithm to solve a Web Mining problem from multiple instance perspective. This a... A Zafra,EL Gibaja,S Ventura - Elsevier Science Publishers B. V. 被引量:...
“Application of Multiobjective Genetic Programming to the Design of Robot Failure Recognition Systems,” IEEE Transactions on Automation Science and Engineering... Y Zhang,PI Rockett - 《IEEE Transactions on Automation Science & Engineering》 被引量: 8发表: 2009年 Pixel Statistics and False Alarm ...
Genetic Programming GP is an evolutionary technique that expands the genetic learning paradigm into an autonomous synthesis of computer programs that, when executed, lead to candidate solutions. Unlike GAs, in which populations are fixed-length encoded character strings representing candidate solutions, in...
Little work exists in the literature on the evolution of heuristics for combinatorial multiobjective optimization problems using genetic programming. Most notably, Burke et al. [2, 3] have recently ...Kumar R,Banerjee N.Running time analysis of a multiobjective evolutionary algorithm on simple and...
Pareto front:finds noninferior solutions—that is, solutions in which an improvement in one objective requires a degradation in another. Solutions are found with either a direct (pattern) search solver or a genetic algorithm. Both can be applied to smooth or nonsmooth problems with linear and non...
Hashimoto and Matsumoto [3] found multipeaks of objective function and suggested a hybrid method combining the direct search method and successive quadratic programming to find the global optimum solution. Choi and Yang [4] utilized immune genetic algorithm for multiobjective optimization of rotor beari...
1) multiobjective genetic programming 多目标遗传编程 1. A novelmultiobjective genetic programming,which searching aim is to minimize the sum of squares of deviations,the complexity and the maximal dynamic deviation,was put forward to model the main steam temperature system of powe. ...