Towards a Unified Modeling and Knowledge-Representation based on Lattice Theory : Computational Intelligence and Soft Computing Applications /
By: Kaburlasos, Vassilis G [author.].
Contributor(s): SpringerLink (Online service).
Material type:
BookPublisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2006.Description: XXII, 245 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783540341703.Subject(s): Computer science | Computers | Artificial intelligence | Applied mathematics | Engineering mathematics | Computer Science | Theory of Computation | Artificial Intelligence (incl. Robotics) | Appl.Mathematics/Computational Methods of Engineering | Applications of MathematicsDDC classification: 004.0151 Online resources: Click here to access online | Item type | Current location | Call number | Status | Date due | Barcode | Item holds |
|---|---|---|---|---|---|---|
E books
|
PK Kelkar Library, IIT Kanpur | Available | EBK9089 |
The Context -- Origins in Context -- Relevant Literature Review -- Theory and Algorithms -- Novel Mathematical Background -- Real-World Grounding -- Knowledge Representation -- The Modeling Problem and its Formulation -- Algorithms for Clustering, Classification, and Regression -- Applications and Comparisons -- Numeric Data Applications -- Nonnumeric Data Applications -- Connections with Established Paradigms -- Conclusion -- Implementation Issues -- Discussion.
By ‘model’ we mean a mathematical description of a world aspect. With the proliferation of computers a variety of modeling paradigms emerged under computational intelligence and soft computing. An advancing technology is currently fragmented due, as well, to the need to cope with different types of data in different application domains. This research monograph proposes a unified, cross-fertilizing approach for knowledge-representation and modeling based on lattice theory. The emphasis is on clustering, classification, and regression applications. It is shown how rigorous analysis and design can be pursued in soft computing using conventional (hard computing) methods. Moreover, non-Turing computation can be pursued. The material here is multi-disciplinary based on our on-going research published in major scientific journals and conferences. Experimental results by various algorithms are demonstrated extensively. Relevant work by other authors is also presented both extensively and comparatively.
There are no comments for this item.