## Abstract The primary objective of this study is to investigate the possibility of including more temporal and spatial information on shortβterm inflow forecasting, which is not easily attained in the traditional timeβseries models or conceptual hydrological models. In order to achieve this objec
β¦ LIBER β¦
Short-Term Water Demand Forecast Modelling at IIT Kanpur Using Artificial Neural Networks
β Scribed by Ashu Jain; Ashish Kumar Varshney; Umesh Chandra Joshi
- Book ID
- 110328701
- Publisher
- Springer Netherlands
- Year
- 2001
- Tongue
- English
- Weight
- 167 KB
- Volume
- 15
- Category
- Article
- ISSN
- 0920-4741
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
Short-term inflow forecasting using an a
β
Z. X. Xu; J. Y. Li
π
Article
π
2002
π
John Wiley and Sons
π
English
β 230 KB
π 1 views
Short-term electric load forecasting usi
β
Subhes C. Bhattacharyya; Le Tien Thanh
π
Article
π
2004
π
John Wiley and Sons
π
English
β 131 KB
π 1 views
Short-term electric load forecasting is an important requirement for electric system operation. This paper employs a feed-forward neural network with a back-propagation algorithm for three types of short-term electric load forecasting: daily peak (valley) load, hourly load and the total load. The fo
Using statistical and artificial neural
β
V. Uddameri
π
Article
π
2006
π
Springer
β 608 KB