Joint Session 3 | |||
Artificial Intelligence and Climate Applications (Joint between 5th Conference on Applications of Artificial Intelligence in the Environmental Sciences and 19th Conference on Climate Variability and Change) | |||
Cochairs: Antonello Pasini, CNR, Rome Italy; Vladimir M. Krasnopolsky, Univ. of Maryland and SAIC at NOAA/NCEP/EMC, Camp Springs, MD | |||
1:40 PM | Welcoming Remarks | ||
1:45 PM | J3.2 | Hybrid Numerical Climate and Weather Prediction Models Combining Deterministic and Statistical Learning Model Components (Invited Speaker) Vladimir M. Krasnopolsky, Univ. of Maryland and NOAA/NCEP/EMC/SAIC, Camp Springs, MD; and M. S. Fox-Rabinovitz | |
2:15 PM | J3.3 | Accurate and fast neural network emulation of full, long, and short wave, model radiation used for decadal climate simulations with NCAR CAM Vladimir M. Krasnopolsky, Univ. of Maryland and NOAA/NCEP/EMC/SAIC, Camp Springs, MD; and M. Fox-Rabinovitz and A. Belochitski | |
2:30 PM | J3.4 | Predictability in past and future climate conditions: a preliminary analysis by neural networks using unforced and forced Lorenz systems as toy models Antonello Pasini, CNR, Rome, Italy | |
2:45 PM | J3.5 | Linking Climatic Variables with Colombian Development Indicators via Inductive Learning Tools John Alexander Segura Sr., Hydrosciences Research Group, Bogotá, Colombia; and R. J. Brito, Y. R. Coronel, and N. Obregón | |
3:00 PM | Coffee Break in Exhibit Hall | ||
3:30 PM | J3.6 | Nonlinear principal component analysis: A new information criterion for model selection in noisy climate datasets (Invited Speaker) William W. Hsieh, Univ. of British Columbia, Vancouver, BC, Canada | |
4:00 PM | J3.7 | Robust nonlinear multivariate statistical models for climate analysis Alex J. Cannon, MSC, Vancouver, BC, Canada; and W. W. Hsieh | |
4:15 PM | J3.8 | Finding interesting climate phenomena by exploratory statistical techniques Alexander Ilin, Helsinki University of Technology, Espoo, Finland; and H. Valpola and E. Oja | |
4:30 PM | J3.9 | Multiple imputation through machine learning algorithms Michael B. Richman, Univ. of Oklahoma, Norman, OK; and T. B. Trafalis and I. Adrianto | |
4:45 PM | J3.10 | Object-oriented analysis of precipitation systems in NCEP Stage II analyses Michael E. Baldwin, Purdue Univ., West Lafayette, IN; and R. J. Trapp |
Tuesday, 16 January 2007: 1:40 PM-5:00 PM, 210B
* - Indicates paper has been withdrawn from meeting