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Gmdh-methodology And Implementation In Matlab (eBook)

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  • 40,366 Words
  • 284 Pages

Group method of data handling (GMDH) is a typical inductive modeling method built on the principles of self-organization. Since its introduction, inductive modelling has been developed to support complex systems in prediction, clusterization, system identification, as well as data mining and knowledge extraction technologies in social science, science, engineering, and medicine.

This is the first book to explore GMDH using MATLAB (matrix laboratory) language. Readers will learn how to implement GMDH in MATLAB as a method of dealing with big data analytics. Error-free source codes in MATLAB have been included in supplementary material (accessible online) to assist users in their understanding in GMDH and to make it easy for users to further develop variations of GMDH algorithms.

Contents:
  • Basic/Standard GMDH:
    • Introduction (Godfrey C Onwubolu)
    • GMDH Multilayered Algorithm (Godfrey C Onwubolu)
    • GMDH Multilayered Algorithm in MATLAB (Mohammed Abdalla Ayoub Mohammed)
  • Hybrid GMDH System:
    • GMDH-Based Polynomial Neural Network Algorithm in MATLAB (Elaine Inácio Bueno, Iraci Martinez Pereira and Antonio Teixeira e Silva)
    • Designing GMDH Model Using Modified Levenberg Marquardt Technique in Matlab (Maryam Pournasir Roudbaneh)
    • Group Method of Data Handing Using Discrete Differential Evolution in Matlab (Donald Davendra, Godfrey Onwubolu and Ivan Zelinka)

Readership: Professionals and students interested in data mining and analytics.

Group method of data handling (GMDH) is a typical inductive modeling method built on the principles of self-organization. Since its introduction, inductive modelling has been developed to support complex systems in prediction, clusterization, system identification, as well as data mining and knowledge extraction technologies in social science, science, engineering, and medicine.

This is the first book to explore GMDH using MATLAB (matrix laboratory) language. Readers will learn how to implement GMDH in MATLAB as a method of dealing with big data analytics. Error-free source codes in MATLAB have been included in supplementary material (accessible online) to assist users in their understanding in GMDH and to make it easy for users to further develop variations of GMDH algorithms.

Contents:
  • Basic/Standard GMDH:
    • Introduction (Godfrey C Onwubolu)
    • GMDH Multilayered Algorithm (Godfrey C Onwubolu)
    • GMDH Multilayered Algorithm in MATLAB (Mohammed Abdalla Ayoub Mohammed)
  • Hybrid GMDH System:
    • GMDH-Based Polynomial Neural Network Algorithm in MATLAB (Elaine Inácio Bueno, Iraci Martinez Pereira and Antonio Teixeira e Silva)
    • Designing GMDH Model Using Modified Levenberg Marquardt Technique in Matlab (Maryam Pournasir Roudbaneh)
    • Group Method of Data Handing Using Discrete Differential Evolution in Matlab (Donald Davendra, Godfrey Onwubolu and Ivan Zelinka)

Readership: Professionals and students interested in data mining and analytics.


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