## Abstract Previous ensemble streamflow prediction (ESP) studies in Korea reported that modelling error significantly affects the accuracy of the ESP probabilistic winter and spring (i.e. dry season) forecasts, and thus suggested that improving the existing rainfallβrunoff model, TANK, would be cr
β¦ LIBER β¦
PREDICTION OF THE FEMURAL LOAD USING BONE ADAPTATION MODELS AND ARTIFICIAL NEURAL NETWORKS
β Scribed by Gianni Campoli; Harrie Weinans; Amir Abbas Zadpoor
- Book ID
- 117135476
- Publisher
- Elsevier Science
- Year
- 2012
- Tongue
- English
- Weight
- 296 KB
- Volume
- 45
- Category
- Article
- ISSN
- 0021-9290
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
Rainfall-runoff models using artificial
β
Dae-Il Jeong; Young-Oh Kim
π
Article
π
2005
π
John Wiley and Sons
π
English
β 865 KB
Prediction of Loan Redemption: Logit Mod
β
Dorota Witkowska; Mariola Chrzanowska
π
Article
π
2005
π
Springer US
π
English
β 74 KB
Prediction of soil temperature using reg
β
Mehmet Bilgili
π
Article
π
2010
π
Springer
π
English
β 534 KB
Prediction of skin penetration using art
β
Tuncer DeΔiΜm; Jonathan Hadgraft; Sibel Δ°lbasmiΕ; YalΓ§in Γzkan
π
Article
π
2003
π
John Wiley and Sons
π
English
β 239 KB
Artificial neural network (ANN) analysis was used to predict the skin permeability of selected xenobiotics. Permeability coefficients (log k(p)) were obtained from various literature sources. A previously reported equation, which was shown to be useful in the prediction of skin permeability, uses th
Prediction of siRNA knockdown efficiency
β
Guangtao Ge; G.William Wong; Biao Luo
π
Article
π
2005
π
Elsevier Science
π
English
β 156 KB
Modeling and prediction of Turkeyβs elec
β
Kadir Kavaklioglu; Halim Ceylan; Harun Kemal Ozturk; Olcay Ersel Canyurt
π
Article
π
2009
π
Elsevier Science
π
English
β 765 KB