Encapsulation of parametric uncertainty statistics by various predictive machine learning models: MLUE method

DL Shrestha; N Kayastha; DP Solomatine; RK Price

doi:10.2166/hydro.2013.242

Encapsulation of parametric uncertainty statistics by various predictive machine learning models: MLUE method

DL Shrestha, N Kayastha, DP Solomatine, RK Price

Water Resources

Research output: Contribution to journal › Article › Scientific › peer-review

9 Citations (Scopus)

Original language	English
Pages (from-to)	95-113
Number of pages	19
Journal	Journal of Hydroinformatics
Volume	16
Issue number	1
DOIs	https://doi.org/10.2166/hydro.2013.242
Publication status	Published - 2014

Bibliographical note

Harvest

Keywords

CWTS JFIS < 0.75

Access to Document

10.2166/hydro.2013.242

Cite this

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title = "Encapsulation of parametric uncertainty statistics by various predictive machine learning models: MLUE method",

keywords = "CWTS JFIS < 0.75",

author = "DL Shrestha and N Kayastha and DP Solomatine and RK Price",

note = "Harvest",

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doi = "10.2166/hydro.2013.242",

language = "English",

volume = "16",

pages = "95--113",

journal = "Journal of Hydroinformatics",

issn = "1464-7141",

publisher = "International Water Association (IWA)",

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AU - Kayastha, N

AU - Solomatine, DP

AU - Price, RK

N1 - Harvest

PY - 2014

Y1 - 2014

KW - CWTS JFIS < 0.75

U2 - 10.2166/hydro.2013.242

DO - 10.2166/hydro.2013.242

M3 - Article

SN - 1464-7141

VL - 16

SP - 95

EP - 113

JO - Journal of Hydroinformatics

JF - Journal of Hydroinformatics

IS - 1

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