A hybrid model for monthly water demand prediction: A case study of Austin, Texas

Hongfang Lu; John Matthews; Shuai Han

doi:10.1002/aws2.1175

A hybrid model for monthly water demand prediction: A case study of Austin, Texas

Hongfang Lu
, John Matthews
, Shuai Han

Louisiana Tech University

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

Original language	English
Article number	e1175
Journal	AWWA Water Science
Volume	2
Issue number	2
DOIs	https://doi.org/10.1002/aws2.1175
State	Published - Mar 1 2020
Externally published	Yes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 6 Clean Water and Sanitation
SDG 11 Sustainable Cities and Communities

ASJC Scopus Subject Areas

Environmental Engineering
General Chemistry
Water Science and Technology
Filtration and Separation

Keywords

fruit fly optimization algorithm
genetic cross factor
monthly
simulated annealing algorithm
support vector machine
water demand prediction

Access to Document

10.1002/aws2.1175

Cite this

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title = "A hybrid model for monthly water demand prediction: A case study of Austin, Texas",

keywords = "fruit fly optimization algorithm, genetic cross factor, monthly, simulated annealing algorithm, support vector machine, water demand prediction",

author = "Hongfang Lu and John Matthews and Shuai Han",

note = "Publisher Copyright: {\textcopyright} 2020 American Water Works Association",

year = "2020",

month = mar,

day = "1",

doi = "10.1002/aws2.1175",

language = "English",

volume = "2",

journal = "AWWA Water Science",

issn = "2577-8161",

number = "2",

}

TY - JOUR

T1 - A hybrid model for monthly water demand prediction

T2 - A case study of Austin, Texas

AU - Lu, Hongfang

AU - Matthews, John

AU - Han, Shuai

PY - 2020/3/1

Y1 - 2020/3/1

KW - fruit fly optimization algorithm

KW - genetic cross factor

KW - monthly

KW - simulated annealing algorithm

KW - support vector machine

KW - water demand prediction

UR - https://www.scopus.com/pages/publications/85088570145

UR - https://www.scopus.com/pages/publications/85088570145#tab=citedBy

U2 - 10.1002/aws2.1175

DO - 10.1002/aws2.1175

M3 - Article

AN - SCOPUS:85088570145

SN - 2577-8161

VL - 2

JO - AWWA Water Science

JF - AWWA Water Science

IS - 2

M1 - e1175

ER -

A hybrid model for monthly water demand prediction: A case study of Austin, Texas

UN SDGs

ASJC Scopus Subject Areas

Keywords

Access to Document

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