Semantics has become a key topic of research in Genetic Programming (GP). Semantics refers to the outputs (behaviour) of a GP individual when this is run on a data set. The majority of works that focus on semantic diversity in single-objective GP indicates that it is highly beneficial in ...
In this chapter we examine how multi-objective genetic programming can be used to perform symbolic regression and compare its performance to single-objective genetic programming. Multi-objective optimization is implemented by using a slightly adapted version of NSGA-II, where the optimization objectives ...
non-linear systemIn this paper, a new multi-objective genetic programming GP with a diversity preserving mechanism and a real number alteration operator is presented and successfully used for Pareto optimal modelli...A. JamaliE. KhaleghiI. GholaminezhadN. Nariman-zadeh...
Fig. 8. Multi-objective genetic programming algorithm for the optimization of the HEMS strategy. The values of the parameters of the inner nodes are generated randomly when a tree is initialized. 5. Case study In this section, the data used for the simulation and the strategy optimization are...
objective evolutionary and genetic algorithms and then presents the fundamental principles and design considerations of MOGAs such as encoding, crossover and mutation operators, fitness assignments, selection methods, and diversity preservation. Applications, future directions, challenges, and opportunities ...
Shaobo, "Multi-objective optimization of RFID network based on genetic programming," Netw. Based Genet. Program. Inf. Technol. J. 10, vol. 10, no. 12, 2011.P. Weijie, L. Saobo, X. Qingsheng, and Y. Guanci (2011). Multi-objective optimization of RFID network based on genetic ...
Evolutionary algorithms like genetic algorithms, particle swarm optimization and simulated annealing fall under this category, as do Multi-objective Genetic Algorithms such as NSGA-II, SPEA2, MOEA/D and NSGA-II19. Interactive techniques: these strategies necessitate human engagement throughout the ...
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:...
Jeneticsis aGenetic Algorithm,Evolutionary Algorithm,Grammatical Evolution,Genetic Programming, andMulti-objective Optimizationlibrary, written in modern day Java. It is designed with a clear separation of the several concepts of the algorithm, e.g.Gene,Chromosome,Genotype,Phenotype,Populationand fitnessFunc...
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. ...