Adaptive neuro‐fuzzy inference system to estimate the predictability of visibility during fog over Delhi, India-Reference-Cited by-同舟云学术

Adaptive neuro‐fuzzy inference system to estimate the predictability of visibility during fog over Delhi, India

Published:2020-03 Issue:2 Volume:27 Page:
ISSN:1350-4827
Container-title:Meteorological Applications
language:en
Short-container-title:Meteorol Appl

Author:

Goswami S.¹²,Chaudhuri S.¹^ORCID,Das D.¹,Sarkar I.¹,Basu D.¹

Affiliation:

1. Department of Atmospheric SciencesUniversity of Calcutta Kolkata India

2. Department of Environmental Science, Amity University Kolkata Kolkata India

Publisher

Wiley

Subject

Atmospheric Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/met.1900

Reference47 articles.

1. Banacos C.P. (2011) Box and whisker plots for local climate datasets: interpretation and creation using Excel 2007/2010.Eastern Region Technical Attachment 1 January 2011. Burlington VT: NOAA/NWS.

2. Prediction of extreme precipitation using a neural network: application to summer flood occurrence in Moravia

3. Public transportation trip flow modeling with generalized regression neural networks

4. Multiple linear regression applications in real estate pricing;Ceyhun O.;International Journal of Mathematics and Statistics Invention.,2016

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