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Assessing Suitability of GP Modeling for Groundwater Level

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Artificial Neural Network and other soft computing techniques have been widely used for modeling groundwater level changes. Emphasis has been laid by different researches in improving the quality of input data which significantly affects the final model. In this study Genetic Programming (GP) is used to model spatial variation of groundwater in Arjuna Nadhi sub basin region. For a limited list of monthly groundwater level data the result indicates that when information from neighbouring wells, which are selected on their appropriation, is incorporated, the modeling accuracy improves significantly. It is also concluded that each region/ zone needs individual modeling irrespective of their geographic proximity.

Keywords:groundwater level; spatial variation; genetic programming; input selection

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Informasi Detail

Judul Seri

Aquatic Procedia

No. Panggil

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Penerbit

: Elsevier., 2015

Deskripsi Fisik

Aquatic Procedia 4 ( 2015 ) 693 – 699

Bahasa

English

ISBN/ISSN

doi: 10.1016/j.aqpro

Klasifikasi

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Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

KIMIA

Info Detail Spesifik

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Pernyataan Tanggungjawab

Wati/Agus

Versi lain/terkait

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