Lattice Computing in Hybrid Intelligent Systems

被引:0
作者
Grana, Manuel [1 ]
机构
[1] Univ Basque Country, Dept CCIA, Computat Intelligence Grp, San Sebastian, Spain
来源
2012 12TH INTERNATIONAL CONFERENCE ON HYBRID INTELLIGENT SYSTEMS (HIS) | 2012年
关键词
Lattice Computing; Hybrid Intelligent Systems; SELF-ORGANIZING MAP; NEURAL-NETWORKS; OPTIMAL-DESIGN; FIXED-POINTS; FUZZY ARTMAP; KERNEL; FRAMEWORK; MODEL; GRSOM;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Lattice Computing is the class of algorithms built on the basis of Lattice Theory. They either perform operations in the ring of the real valued spaces endowed with some (inf, sup) lattice operators, or use lattice theory to produce generalizations or fusions of conventional approaches. Lattice Computing has produced a variety of algorithms for data processing, classification, signal filtering over the last decades. On the other hand, hybrid algorithms are flourishing in the last years giving innovative solutions to new and old problems. Hybrid algorithms are free combinations of Computational Intelligence approaches for data mining, signal processing or general artificial intelligence questions, including statistical, nature and bio-inspired algorithms. In this paper we review some Lattice Computing approaches and how they have been hybridized for specific problems.
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页码:1 / 5
页数:5
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