The hybrid forecasting model based on chaotic mapping, genetic algorithm and support vector machine

Author:

Wu Qi

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference28 articles.

1. Abdelhadi, B., Benoudjit, A., & Nait-Said, N. (2003). Self-adaptive genetic algorithms based characterization of structured model parameters. In: Proceedings of the 35th southeastern symposium on system theory, Virginia (pp. 181–185).

2. Multiobjective analysis of chaotic dynamic systems with sparse learning machines;Abedalrazq;Advances in Water Resources,2006

3. Control of chaotic dynamical systems using support vector machines;Abhijit;Physics Letters A,2003

4. Support vector machines combined with feature selection for breast cancer diagnosis;Akay;Expert Systems with Applications,2009

5. Selecting of the optimal feature subset and kernel parameters in digital modulation classification by using hybrid genetic algorithm–support vector machines: HGASVM;Avci;Expert Systems with Applications,2009

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