Title :
The use of cultural algorithms with evolutionary programming to control the data mining of large-scale spatio-temporal databases
Author :
Reynolds, Robert ; Al-Shehri, Hasan
Author_Institution :
Dept. of Comput. Sci., Wayne State Univ., Detroit, MI, USA
Abstract :
We use an evolutionary computational approach based upon cultural algorithms to guide the incremental learning decision trees by ITI. The results are compared to those produced by ITI itself for a complex real-world database. The results suggest that ITI can indeed produce optimal trees in some cases, and can produce optimal trees using an evolutionary approach in others
Keywords :
database theory; deductive databases; genetic algorithms; knowledge acquisition; learning (artificial intelligence); temporal databases; trees (mathematics); very large databases; visual databases; ITI; complex real-world database; cultural algorithms; data mining; deductive database; evolutionary computational approach; evolutionary programming; incremental learning decision trees; large-scale spatio-temporal databases; optimal trees; Computer science; Cultural differences; Data mining; Databases; Decision trees; Entropy; Genetic programming; Large-scale systems; Machine learning algorithms; Partitioning algorithms;
Conference_Titel :
Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-4053-1
DOI :
10.1109/ICSMC.1997.637338
