Michael B. Richman

发表

Identification of severe weather outbreaks using kernel principal component analysis

Andrew E. Mercer, Michael B. Richman, Lance M. Leslie, 2011, Complex Adaptive Systems.

Intelligent and Adaptive Systems: Machine Learning

Vernon Ireland, Kristin Giammarco, Ayhan Demiriz, 2014 .

Machine Learning Classifiers for Tornado Detection: Sensitivity Analysis on Tornado Data Sets

S. Lakshmivarahan, Theodore B. Trafalis, Michael B. Richman, 2006 .

Missing Data Imputation Through Machine Learning Algorithms

Theodore B. Trafalis, Michael B. Richman, Indra Adrianto, 2009 .

Assessing Atmospheric Variability using Kernel Principal Component Analysis

Andrew E. Mercer, Michael B. Richman, 2012, Complex Adaptive Systems.

Tornado Detection with Support Vector Machines

Theodore B. Trafalis, Michael B. Richman, Huseyin Ince, 2003, International Conference on Computational Science.

Constructing an Efficient Machine Learning Model for Tornado Prediction

Fuad Aleskerov, Theodore B. Trafalis, Michael B. Richman, 2020, Int. J. Inf. Technol. Decis. Mak..

Data selection using support vector regression

Theodore B. Trafalis, Michael B. Richman, Lance M. Leslie, 2015, Advances in Atmospheric Sciences.

Reducing Tropical Cyclone Prediction Errors Using Machine Learning Approaches

Michael B. Richman, Lance M. Leslie, Hamish A. Ramsay, 2017 .

The use of principal component analysis for climatological inference

Michael B. Richman, 2000 .

Machine Learning Methods for Data Assimilation

Theodore B. Trafalis, Michael B. Richman, Lance M. Leslie, 2010 .

Rule-Based Support Vector Machine Classifiers Applied to Tornado Prediction

Budi Santosa, Theodore B. Trafalis, Michael B. Richman, 2004, International Conference on Computational Science.

The 2015-2017 Cape Town Drought: Attribution and Prediction Using Machine Learning

Michael B. Richman, Lance M. Leslie, L. Leslie, 2018 .

Machine-learning classifiers for imbalanced tornado data

S. Lakshmivarahan, Theodore B. Trafalis, Michael B. Richman, 2014, Comput. Manag. Sci..

Determination oftheOptimal BatchSizeinIncremental Approaches: AnApplication toTornado Detection

Theodore B. Trafalis, Michael B. Richman, Hyung-Jin Son, 2005 .

Classification of Changes in Extreme Heat Over Southeastern Australia

Michael B. Richman, Lance M. Leslie, M. Richman, 2013, Complex Adaptive Systems.

Uniqueness and Causes of the California Drought

Michael B. Richman, Lance M. Leslie, 2015, Complex Adaptive Systems.

A Pipeline Support Vector Regression Method to Thin Large Ocean Surface Wind Data On-Line

Theodore B. Trafalis, Michael B. Richman, Lance M. Leslie, 2008 .

Active Learning with Kernel Machines for Tornado Detection

Theodore B. Trafalis, Michael B. Richman, Indra Adrianto, 2008 .

Learning networks for tornado detection

Budi Santosa, Theodore B. Trafalis, Michael B. Richman, 2006, Int. J. Gen. Syst..

Real-Time Prediction Using Kernel Methods and Data Assimilation

S. Lakshmivarahan, Theodore B. Trafalis, Michael B. Richman, 2009 .

Learning networks in rainfall estimation

Budi Santosa, Theodore B. Trafalis, Michael B. Richman, 2005, Comput. Manag. Sci..

Machine Learning Techniques for Imbalanced Data: An Application for Tornado Detection

Theodore B. Trafalis, Michael B. Richman, Indra Adrianto, 2010 .

Machine Learning Approaches to Reducing Tropical Cyclone Prediction Errors

Michael B. Richman, 2018 .

A data-driven kernel method assimilation technique for geophysical modelling

Theodore B. Trafalis, Michael B. Richman, Lance M. Leslie, 2017, Optim. Methods Softw..

Clickers in Introductory Statistics Courses

Michael B. Richman, Curtis C. McKnight, Teri J. Murphy, 2011 .

Comments on: ‘The effect of domain shape on principal components analyses’

Michael B. Richman, M. B. Richman, 1993 .

Learning Networks For Tornado Forecasting:A Bayesian Perspective

Budi Santosa, Theodore B. Trafalis, Michael B. Richman, 2005 .

Active Learning with Support Vector Machines for Tornado Prediction

Theodore B. Trafalis, Michael B. Richman, Indra Adrianto, 2007, International Conference on Computational Science.

Classifying Drought in Ethiopia Using Machine Learning

Michael B. Richman, Lance M. Leslie, Zewdu T. Segele, 2016 .

Attribution and Prediction of Maximum Temperature Extremes in SE Australia

Michael B. Richman, Lance M. Leslie, L. Leslie, 2014, Complex Adaptive Systems.

Cluster Analysis of North Atlantic Tropical Cyclones

Michael B. Richman, Lance M. Leslie, Peter J. Lamb, 2014, Complex Adaptive Systems.

Machine Learning for Attribution of Heat and Drought in Southwestern Australia

Michael B. Richman, Lance M. Leslie, L. Leslie, 2020 .

An automated technique to categorize storm type from radar and near-storm environment data

Michael B. Richman, Travis M. Smith, Valliappa Lakshmanan, 2012 .

Linear classification tikhonov regularization knowledge-based support vector machine for tornado forecasting

Theodore B. Trafalis, Michael B. Richman, Olutayo O. Oladunni, 2011, Comput. Manag. Sci..

Adaptive Big Data Analytics III

Rajab Challoo, Anthony D. Joseph, Claude Turner, 2011 .

Tornado Detection with Kernel-Based Classifiers from WSR-88D Radar Data

Budi Santosa, Theodore B. Trafalis, Michael B. Richman, 2016 .

Prediction of Rainfall from WSR-88D Radar Using Kernel-Based Methods

Budi Santosa, Theodore B. Trafalis, Michael B. Richman, 2003 .

On the Application of Cluster Analysis to Growing Season Precipitation Data in North America East of the Rockies

Michael B. Richman, M. Richman, Xiaofeng Gong, 1995 .

MULTIPLE IMPUTATION THROUGH MACHINE LEARNING ALGORITHMS

Theodore B. Trafalis, Michael B. Richman, Indra Adrianto, 2006 .

Data mining techniques for improved WSR-88D rainfall estimation

Theodore B. Trafalis, Michael B. Richman, Budi Santosa, 2002 .

Climatic Pattern Analysis of Three- and Seven-Day Summer Rainfall in the Central United States: Some Methodological Considerations and a Regionalization

Michael B. Richman, Peter J. Lamb, P. Lamb, 1985 .

Climate regionalization and rotation of principal components

Michael B. Richman, Dale White, Brent Yarnal, 2007 .

Evaluation of WRF Forecasts of Tornadic and Nontornadic Outbreaks when Initialized with Synoptic-Scale Input

Charles A. Doswell, Andrew E. Mercer, Michael B. Richman, 2008 .

Ocean Surface Wind Vector Forecasting Using Support Vector Regression

Theodore B. Trafalis, Michael B. Richman, Lance M. Leslie, 2007 .

Classification and regionalization through kernel principal component analysis

Michael B. Richman, Indra Adrianto, I. Adrianto, 2010 .

Variable selection and prediction of rainfall from WSR-88D radar using support vector regression

Theodore B. Trafalis, Michael B. Richman, Budi Santosa, 2005 .

Damaging Weather Conditions in the United States: A Selection of Data Quality and Monitoring Issues

Michael B. Richman, Peter J. Lamb, P. Lamb, 1999 .

Range-Correcting Azimuthal Shear in Doppler Radar Data

Michael B. Richman, Pamela L. Heinselman, Travis M. Smith, 2012 .

Procrustes target analysis: A multivariate tool for identification of climate fluctuations

Michael B. Richman, William E. Easterling, W. Easterling, 1988 .

Seasonal tropical cyclone predictions using optimized combinations of ENSO regions: application to the Coral Sea Basin

Michael B. Richman, Lance M. Leslie, Hamish A. Ramsay, 2014 .

Obliquely Rotated Principal Components: An Improved Meteorological Map Typing Technique?

Michael B. Richman, M. B. Richman, 1981 .

An Observational Study of Derecho-Producing Convective Systems

David J. Stensrud, Michael B. Richman, Michael C. Coniglio, 2004 .

Weekly precipitation cycles? Lack of evidence from United States surface stations

Michael B. Richman, David M. Schultz, Ari Laaksonen, 2007 .

REVIEW ARTICLE ROTATION OF PRINCIPAL COMPONENTS

Michael B. Richman, M. B. Richman, 1986 .

Evaluation of WRF Model Simulations of Tornadic and Nontornadic Outbreaks Occurring in the Spring and Fall

Charles A. Doswell, Andrew E. Mercer, Michael B. Richman, 2010 .