Bridging the gap between artificial intelligence and statistics in applications to environmental science
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This session invites papers discussing existing and proposed applications of artificial intelligence (AI) and probability and statistics (ProbStats) in the environmental sciences. A special interest of the session will be the technologic, computational, programmatic, and communication tools and methods that promote successful use of AI and/or ProbStats.
Existing and new societal demand for environmental information, such as in agriculture and agribusiness, renewable energy, health care, water resources and wildlife management, brings new challenges to scientific community such as providing technologically-advanced and easy-to-understand products and services with real-time and highly reliable information. The session invites producers and users of climate, water, and weather information to share their latest scientific advances and ready or near-ready technologies for addressing such challenges. AI and ProbStats methods are both technologies and enablers for the development and evaluation of technological systems. For instance, AI and ProbStats include techniques that make analysis and knowledge discovery from very large datasets possible, and they allow development, evaluation and optimization of empirical algorithms that support a huge variety of observing platforms and decision support systems. The session will focus on AI and ProbStats tools and methods for various applications; assessment of performance, quality and effectiveness; and evaluating the commonalities and differences between the various approaches used by these two AMS communities.
21st Conference on Probability and Statistics in the Atmospheric Sciences
10th Conference on Artificial Intelligence and its Applications to Environmental Science