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http://krishi.icar.gov.in/jspui/handle/123456789/72889
Title: | Soft computing and statistical technique-application to eutrophication potential modelling of Mumbai coastal area |
Other Titles: | Not Available |
Authors: | Bharti VS, Inamdar AB, Purusothaman CS, Yadav VK |
ICAR Data Use Licennce: | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf |
Author's Affiliated institute: | ICAR: Central Institute of Fisheries Education |
Published/ Complete Date: | 2018-02-01 |
Project Code: | Not Available |
Keywords: | Soft computing, statistical technique, potential modelling, coastal area, quality parameters |
Publisher: | Not Available |
Citation: | Not Available |
Series/Report no.: | Not Available; |
Abstract/Description: | Three water quality parameters – dissolved oxygen (DO), coloured dissolved organic matter (CDOM) and Chlorophyll a loaded on the first principal component under the dimensional reduction method were used for deriving the Eutrophication Index (EI). Fuzzy logic (Mamdani) method of EI estimation is smoother than the Principal Component Analysis (PCA) method. Eutrophication potential obtained from the rule-based fuzzy approach and the multiple regressions derived from the first principal component were selected as the target variables for the artificial neural network (ANN) model in training and prediction. The performance of the ANN models with PCA-derived target and fuzzy-derived target was compared through the mean absolute error, root mean square error, and correlation coefficient computed from the measured and model-simulated EI values. EI predictions of this model has positive, high correlation (r = 0.968) with the measured EI values derived from the fuzzy approach as compared to the PCA-derived EI (r = 0.851) implying that the model predictions explain around 93.7% of the variation in the measured EI values derived by fuzzy approach as compared to 72.4% in the case of PCA-derived measured value |
Description: | Not Available |
ISSN: | Not Available |
Type(s) of content: | Research Paper |
Sponsors: | Not Available |
Language: | English |
Name of Journal: | Indian Journal of Geo-Marine Sciences |
Journal Type: | Indian |
NAAS Rating: | 6.17 |
Impact Factor: | 0.289 |
Volume No.: | 47(02) |
Page Number: | 365-377 |
Name of the Division/Regional Station: | Not Available |
Source, DOI or any other URL: | Not Available |
URI: | http://krishi.icar.gov.in/jspui/handle/123456789/72889 |
Appears in Collections: | FS-CIFE-Publication |
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