کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
408374 | 679025 | 2007 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Evolution of neural networks for classification and regression
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Evolution of neural networks for classification and regression Evolution of neural networks for classification and regression](/preview/png/408374.png)
چکیده انگلیسی
Although Artificial Neural Networks (ANNs) are important data mining techniques, the search for the optimal ANN is a challenging task: the ANN should learn the input–output mapping without overfitting the data and training algorithms may get trapped in local minima. The use of Evolutionary Computation (EC) is a promising alternative for ANN optimization. This work presents two hybrid EC/ANN algorithms: the first evolves neural topologies while the latter performs simultaneous optimization of architectures and weights. Sixteen real-world tasks were used to test these strategies. Competitive results were achieved when compared with a heuristic model selection and other Data Mining algorithms.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 70, Issues 16–18, October 2007, Pages 2809–2816
Journal: Neurocomputing - Volume 70, Issues 16–18, October 2007, Pages 2809–2816
نویسندگان
Miguel Rocha, Paulo Cortez, José Neves,