کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6866066 | 679096 | 2015 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Discovery scientific laws by hybrid evolutionary model
ترجمه فارسی عنوان
قوانین علمی کشف توسط مدل تکاملی ترکیبی
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کلمات کلیدی
الگوریتم تکاملی ترکیبی، قوانین علمی را بیابید برنامه نویسی ژنتیک،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
Constructing a mathematical model is an important issue in engineering application and scientific research. Discovery high-level knowledge such as laws of natural science in the observed data automatically is a very important and difficult task in systematic research. The authors have got some significant results with respect to this problem. In this paper, high-level knowledge modelled by systems of ordinary differential equations (ODEs) is discovered in the observed data routinely by a hybrid evolutionary algorithm called HEA-GP. The application is used to demonstrate the potential of HEA-GP. The results show that the dynamic models discovered automatically in observed data by computer sometimes can compare with the models discovered by humanity. In addition, a prototype of KDD Automatic System has been developed which can be used to discover models in observed data automatically.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 148, 19 January 2015, Pages 143-149
Journal: Neurocomputing - Volume 148, 19 January 2015, Pages 143-149
نویسندگان
Fei Tang, Sanfeng Chen, Xu Tan, Tao Hu, Guangming Lin, Zuo Kang,