A least-square-driven functional networks type-2 fuzzy logic hybrid model for efficient petroleum reservoir properties prediction
Various computational intelligence techniques have been used in the prediction of petroleum reservoir properties. However, each of them has its limitations depending on different conditions such as data size and dimensionality. Hybrid computational intelligence has been introduced as a new para...
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主要な著者: | , , |
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フォーマット: | E-Article |
言語: | English |
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Springer London
2013
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オンライン・アクセス: | http://ir.unimas.my/id/eprint/8469/1/A%20least-square-driven%20functional%20networks%20type-2%20fuzzy%20logic%20hybrid%20model%20for%20efficient%20petroleum%20reservoir%20properties%20prediction%20%28abstract%29.pdf http://ir.unimas.my/id/eprint/8469/ http://link.springer.com/article/10.1007%2Fs00521-012-1298-2 |
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http://ir.unimas.my/id/eprint/8469/1/A%20least-square-driven%20functional%20networks%20type-2%20fuzzy%20logic%20hybrid%20model%20for%20efficient%20petroleum%20reservoir%20properties%20prediction%20%28abstract%29.pdfhttp://ir.unimas.my/id/eprint/8469/
http://link.springer.com/article/10.1007%2Fs00521-012-1298-2