Multi-time-step ahead daily and hourly intermittent reservoir inflow prediction by artificial intelligent techniques using lumped and distributed data

Journal of Hydrology

Volumn 450-451, Issue , 2012, Pages 293-307

  Jothiprakash, V ^a   Magar, R B ^a  

^a INDIAN INSTITUTE OF TECHNOLOGY BOMBAY   (India)

Author keywords

Artificial intelligent techniques; Cause effect models; Combined models; Daily and hourly; Lumped and distributed data; Time series models

Indexed keywords

ARTIFICIAL INTELLIGENT; CAUSE-EFFECT; COMBINED MODEL; DAILY AND HOURLY; DISTRIBUTED DATA; TIME SERIES MODELS;

GENETIC PROGRAMMING; INPUT OUTPUT PROGRAMS; NETWORK ARCHITECTURE; NEURAL NETWORKS; RAIN; STATISTICAL TESTS;

FORECASTING;

ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; DISCHARGE; INFLOW; LINEARITY; NUMERICAL MODEL; RAINFALL; RESERVOIR; TIME SERIES; WATERSHED;

INDIA; KOYNA BASIN; MAHARASHTRA;

EID: 84862673732     PISSN: 00221694     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jhydrol.2012.04.045     Document Type: Article

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