We are improving our search experience. To check which content you have full access to, or for advanced search, go back to the old search.

Search

Please fill in this field.
Filters applied:
Chapter Evolutionary biology Pattern recognition

Search Results

Showing 21-40 of 10,000 results

  1. Type-1 Fuzzy Logic

    This chapter introduces the basic concepts, notation, and basic operations for the type-1 fuzzy sets that will be needed in the following chapters....
    Patricia Melin, Oscar Castillo in Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing
    Chapter

  2. Human Recognition using Face, Fingerprint and Voice

    We describe in this chapter a new approach for human recognition using as information the face, fingerprint, and voice of a person. We have described...
    Patricia Melin, Oscar Castillo in Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing
    Chapter

  3. Voice Recognition with Neural Networks, Fuzzy Logic and Genetic Algorithms

    We describe in this chapter the use of neural networks, fuzzy logic and genetic algorithms for voice recognition. In particular, we consider the case...
    Patricia Melin, Oscar Castillo in Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing
    Chapter

  4. Clustering with Intelligent Techniques

    Cluster analysis is a technique for grou** data and finding structures in data. The most common application of clustering methods is to partition a...
    Patricia Melin, Oscar Castillo in Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing
    Chapter

  5. Componentwise Least Squares Support Vector Machines

    This chapter describes componentwise Least Squares Support Vector Machines (LS-SVMs) for the estimation of additive models consisting of a sum of...
    K. Pelckmans, I. Goethals, ... B.D. Moor in Support Vector Machines: Theory and Applications
    Chapter

  6. Support Vector Machines for Signal Processing

    This chapter deals with the use of the support vector machine (SVM) algorithm as a possible design method in the signal processing applications. It...
    D. Mattera in Support Vector Machines: Theory and Applications
    Chapter

  7. Theoretical and Practical Model Selection Methods for Support Vector Classifiers

    In this chapter, we revise several methods for SVM model selection, deriving from different approaches: some of them build on practical lines of...
    D. Anguita, A. Boni, ... D. Sterpi in Support Vector Machines: Theory and Applications
    Chapter

  8. Adaptive Discriminant and Quasiconformal Kernel Nearest Neighbor Classification

    Nearest neighbor classification assumes locally constant class conditional probabilities. This assumption becomes invalid in high dimensions due to...
    J. Peng, D.R. Heisterkamp, H.K. Dai in Support Vector Machines: Theory and Applications
    Chapter

  9. Simulated Annealing Approach for the Multi-objective Facility Layout Problem

    In general, facility layout problems are occurred if there are changes in requirements of space, people and equipments. When the changes of...
    Umut R. Tuzkaya, Tijen Ertay, Da Ruan in Intelligent Data Mining
    Chapter

  10. Penalty-Reward Analysis with Uninorms: A Study of Customer (Dis)Satisfaction

    In customer (dis)satisfaction research, analytic methods are needed to capture the complex relationship between overall (dis)satisfaction with a...
    Koen Vanhoof, Pieter Pauwels, ... Geert Wets in Intelligent Data Mining
    Chapter

  11. Association Rule Based Specialization in ER Models

    Association rules (ARs) emerged in the domain of market basket analysis and provide a convenient and effective way to identify and represent certain...
    Martine De Cock, Chris Cornelis, ... Etienne E. Kerre in Intelligent Data Mining
    Chapter

  12. Mining Association Rules with Rough Sets

    We say that there is an association between two sets of items when the sets are likely to occur together in transactions. In information retrieval,...
    D.A. Bell, J.W. Guan, D.Y. Liu in Intelligent Data Mining
    Chapter

  13. A User Centred Approach to Management Decision Making

    The management decision making process is becoming increasingly complicated as more detailed and extensive data is available in this information age....
    L.P. Maguire, T.A. McCloskey, ... R. McIvor in Intelligent Data Mining
    Chapter

  14. Techniques to Improve Multi-Agent Systems for Searching and Mining the Web

    Nowadays, an abundant amount of information is created and delivered over electronic media. The information gathering in the Internet is a complex...
    E. Herrera-Viedma, C. Porcel, ... A.G. Lopez-Herrera in Intelligent Data Mining
    Chapter

  15. Gene Regulating Network Discovery

    Gene regulation has been an important research topic for the past 30 years and data processing models based on different assumptions have been...
    Yingjun Cao, Paul P. Wang, Alade Tokuta in Intelligent Data Mining
    Chapter

  16. Semantic Relations and Information Discovery

    The treatment of semantic relations between terms is essential in information retrieval (IR). Each term in a thesaurus might have classes of...
    D. Cai, C.J. van Rijsbergen in Intelligent Data Mining
    Chapter

  17. Fuzzy Support Vector Machines with Automatic Membership Setting

    Support vector machines like other classification approaches aim to learn the decision surface from the input points for classification problems or...
    C.-fu Lin, S.-de Wang in Support Vector Machines: Theory and Applications
    Chapter

  18. Some Considerations in Multi-Source Data Fusion

    We introduce the data fusion problem and carefully distinguish it from a number of closely problems. Some of the considerations and knowledge that...
    Ronald R. Yager in Intelligent Data Mining
    Chapter

  19. Fuzzy Process Control with Intelligent Data Mining

    The quality-related characteristics cannot sometimes be represented in numerical form, such as characteristics for appearance, softness, color, etc....
    Murat Gülbay, Cengiz Kahraman in Intelligent Data Mining
    Chapter

  20. Accelerating the New Product Introduction with Intelligent Data Mining

    New product development (NPD) is a vital activity for companies. It is also a very risky process since every development stage involves a high degree...
    Gülçin Büyüközkan, Orhan Feyzioğlu in Intelligent Data Mining
    Chapter
Did you find what you were looking for? Share feedback.