Decision support: using machine learning through MATLAB to analyze environmental data
| Autor: | David W. Nadler |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Information Age
Decision support system Variables 010504 meteorology & atmospheric sciences Artificial neural network business.industry Computer science media_common.quotation_subject Geography Planning and Development 010501 environmental sciences Machine learning computer.software_genre 01 natural sciences Environmental data Software Resource (project management) Artificial intelligence business Cluster analysis computer 0105 earth and related environmental sciences General Environmental Science media_common |
| Zdroj: | Journal of Environmental Studies and Sciences. 9:419-428 |
| ISSN: | 2190-6491 2190-6483 |
| DOI: | 10.1007/s13412-019-00558-9 |
| Popis: | Machine learning is not a tool that is available for use by computer scientists, but one that can and should be used by all researchers in this technological era. Gone are the days of humans solely relying on older techniques for decision support. The age of information we live in is filled with countless pieces of data and we need to use the correct tools to help make sense of it all. Using MATLAB and its machine learning tools is an excellent resource for environmental scientists to conduct deep-dives into their data. We use this software title to demonstrate some of its capabilities to enhance our research projects. Regression learning examines the capability of developing the best linear regression model based upon the selected independent and dependent variables. Clustering analysis displays how data can be grouped by similar characteristics and how distant they are from one another. Classification analysis can predict future outcomes depending upon historical input data, a crucial tool in developing models for impending environmental events. It is suggested that environmental scientists who have not incorporated machine learning into their research to begin to add it to their data analyses. |
| Databáze: | OpenAIRE |
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