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Machine Learning Algorithms for Environmental Applications

Dear Colleagues

I am pleased to announce the call for papers for Special Session on “Machine Learning Algorithms for Environmental Applications” to be published in the proceedings of the 14th International Conference on Machine Learning and Applications (IEEE ICMLA'15) held in Miami, Florida, USA, December 9-11, 2015.

Focus is on application of machine learning tools in atmospheric sciences, applied mathematics, computing, environmental, climate and hydrology areas. Original papers or reviews with state-of knowledge of machine learning algorithms in environmental modelling are welcome.

The web address is

http://www.icmla-conference.org/icmla15/files/ML_Environmental-DrRavineshDeo.pdf

Please select session # 9 for papers on “Environmental Applications”.

The Special Session on Machine Learning Algorithms for Environmental Applications will accommodate cutting-edge research to bring scientists with interdisciplinary expertise in atmospheric science, meteorology, mathematics, computing, environmental, climate sciences, hydrology, civil and fluid engineering to a single platform and discuss and/or investigate the applications of machine learning in agriculture, atmospheric and environmental areas.

Interesting contributions in the form of original research papers, review papers with current state-of knowledge, advanced or preliminary results and exhibitions and presentations of applications of machine learning algorithms are welcome.

Papers are sought on a range of topics that include, but are not limited to:

Downscaling of Global Climate Model outputs using machine learning (data-driven) algorithms
Modeling of rainfall, floods, streamflow, drought, heatwaves, flood and other natural disasters using machine learning
Application of machine learning to agriculture, hydrology and atmospheric modeling
Applications of extreme learning machines, gaussian process regression models, genetic programming algorithms, support vector regressions and neural networks
Comparison of dynamic (physical) models versus other machine learning models for predictive modeling
Comparison of hydrological models with machine learning models
Training, testing and error assessment issues in predictive modeling for environmental applications

IMPORTANT DATES

Paper submission deadline for this session: August 31st, 2015

Notification of Acceptance: September 20, 2015

Camera-ready Papers & Pre-registration: October 1, 2015

The ICMLA Conference: December 9-11, 2015

All papers submitted by August 31, 2015, at regular paper submission website ( http://www.icmla-conference.org/icmla15/) will undergo the blind peer review process. For detailed instructions please see the guidelines on the conference website.

Accepted papers will be published in the conference proceedings, as a hardcopy. All accepted papers must be presented by one of the authors in order to be published in the conference proceedings.

All accepted papers will be invited for inclusion in an expanded and revised form, in a journal special issue (Springer), may also be published in a Book on “Machine Learning Applications” in early 2016.

For further information, see this mirror link (original website)

14th International Conference on Machine Learning and Applications

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