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

Journal / American Water Works Association

Volumn 94, Issue 7, 2002, Pages 64-72

  Jain, Ashu ^a   Ormsbee, Lindell E ^a  

^a UNIVERSITY OF KENTUCKY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; ENERGY UTILIZATION; ERROR ANALYSIS; EXPERT SYSTEMS; MATHEMATICAL MODELS; NEURAL NETWORKS; REGRESSION ANALYSIS; TECHNOLOGICAL FORECASTING; TIME SERIES ANALYSIS;

WATER DEMAND FORECASTING;

WATER DISTRIBUTION SYSTEMS;

EID: 0036640826     PISSN: 0003150X     EISSN: None     Source Type: Journal    
DOI: 10.1002/j.1551-8833.2002.tb09507.x     Document Type: Article

References (25)

1. A Rule-based expert system for reservoir operation
2. Water savings from lawn watering restrictions during a drought year in Fort Collins, Colo
3. Daily and hourly water consumption forecasting tools using neural networks
4. Expert pattern recognition for pollution source identification
5. An expert system for flood estimation
6. Neural networks
7. Applications of neural networks to groundwater remediation
8. Meter records in systems planning
9. The impact of price on residential water demand and its relation to systems design
10. Peak-period design standards for a small western US water supply
11. Expert systems for environmental problems
12. Demand forecasting for water distribution systems
13. Expert systems in reservoir management and planning
14. Transfer function models of daily urban water use
15. Time patterns of monthly water use in six Texas cities
16. Operational guidance during drought: Expert systems approach
17. Neural network applications in structural mechanics computations
18. Using regression analysis to project pumpage
19. A model of daily municipal water use for short-term forecasting
20. Short-term municipal water use forecasting
21. Rainfall intervention analysis for online applications