Short-term water demand forecast modeling techniques - Conventional methods versus AI

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

128 Scopus citations

Original language	English
Pages (from-to)	64-72
Number of pages	9
Journal	Journal / American Water Works Association
Volume	94
Issue number	7
DOIs	https://doi.org/10.1002/j.1551-8833.2002.tb09507.x
State	Published - Jul 2002

ASJC Scopus subject areas

TY - JOUR

T1 - Short-term water demand forecast modeling techniques - Conventional methods versus AI

AU - Jain, Ashu

AU - Ormsbee, Lindell E.

PY - 2002/7

Y1 - 2002/7

UR - http://www.scopus.com/inward/record.url?scp=0036640826&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0036640826&partnerID=8YFLogxK

U2 - 10.1002/j.1551-8833.2002.tb09507.x

DO - 10.1002/j.1551-8833.2002.tb09507.x

M3 - Article

AN - SCOPUS:0036640826

SN - 0003-150X

VL - 94

SP - 64

EP - 72

JO - Journal / American Water Works Association

JF - Journal / American Water Works Association

IS - 7

ER -