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Titlebook: Machine Learning for Ecology and Sustainable Natural Resource Management; Grant Humphries,Dawn R. Magness,Falk Huettmann Book 2018 Springe

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書目名稱Machine Learning for Ecology and Sustainable Natural Resource Management
編輯Grant Humphries,Dawn R. Magness,Falk Huettmann
視頻videohttp://file.papertrans.cn/621/620615/620615.mp4
概述Shows ecologists cutting-edge methods that can help in understanding complex systems with multiple interacting variablesto and to form predictive hypotheses from large datasets.Provides practical exam
圖書封面Titlebook: Machine Learning for Ecology and Sustainable Natural Resource Management;  Grant Humphries,Dawn R. Magness,Falk Huettmann Book 2018 Springe
描述.Ecologists and natural resource managers are charged with making complex management decisions in the face of a rapidly changing environment resulting from climate change, energy development, urban sprawl, invasive species and globalization. Advances in Geographic Information System (GIS) technology, digitization, online data availability, historic legacy datasets, remote sensors and the ability to collect data on animal movements via satellite and GPS have given rise to large, highly complex datasets. These datasets could be utilized for making critical management decisions, but are often “messy” and difficult to interpret. Basic artificial intelligence algorithms (i.e., machine learning) are powerful tools that are shaping the world and must be taken advantage of in the life sciences. In ecology, machine learning algorithms are critical to helping resource managers synthesize information to better understand complex ecological systems.?Machine Learning has a wide variety of powerful applications, with three general uses that are of particular interest to ecologists: (1) data exploration to gain system knowledge and generate new hypotheses, (2) predicting ecological patterns in sp
出版日期Book 2018
關(guān)鍵詞Quantitative ecology; artificial intelligence; Statistics; data mining; machine learning; Wildlife biolog
版次1
doihttps://doi.org/10.1007/978-3-319-96978-7
isbn_ebook978-3-319-96978-7
copyrightSpringer Nature Switzerland AG 2018
The information of publication is updating

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Grant R. W. Humphries,Falk Huettmannere Aufmerksamkeit gewidmet...Das Lexikon der Informatik ist für jeden, der sich in die Welt der Informatik begrifflich sicher und kompetent bewegen will, ein unverzichtbarer Begleiter...Der Schwerpunkt der überarbeitung zur 14. Auflage lag auf dem Gebiet der Datensicherheit..978-3-540-72550-3
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From Data Mining with Machine Learning to Inference in Diverse and Highly Complex Data: Some Shared any contractors, governments, a lifestyle and subsequent belief system and society. However, the methodology employed in traditional statistical analyses are well-published and known to violate many of their required statistical assumptions to allow for valid inferences. Often, this topic becomes th
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