KRISHI
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Please use this identifier to cite or link to this item:
http://krishi.icar.gov.in/jspui/handle/123456789/81378
Full metadata record
DC Field | Value | Language |
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dc.contributor.author | D. Karunakaran | en_US |
dc.contributor.author | M. Balakrishnan | en_US |
dc.date.accessioned | 2024-02-15T16:58:22Z | - |
dc.date.available | 2024-02-15T16:58:22Z | - |
dc.date.issued | 2021-02-02 | - |
dc.identifier.citation | Not Available | en_US |
dc.identifier.issn | Not Available | - |
dc.identifier.uri | http://krishi.icar.gov.in/jspui/handle/123456789/81378 | - |
dc.description | Not Available | en_US |
dc.description.abstract | Fish is nutritious, cheap and healthy source of protein. Fishery sector plays a very important role for nation building by providing nutritional health security. India has very vast inland resources like rivers and canals (1,71,334 km), reservoirs (3.15 million ha), floodplain wetlands (0.24 million ha), estuaries (0.27 million ha) and ponds and tanks (2.25 million ha)[15]. Fourteen million inland farmers are getting employment and livelihood support from these resources. Among Inland resources, reservoirs are considered a main resource both in terms of surface area and offer immense scope for increasing fish production. More than 3 million ha of manmade reservoirs in the country has a potential for increase the fish production. As populations are increasing in many fold there is a greater need to obtain as much fish as possible from these resources to meet the demand. Estimation of reservoir yield is a critical component for fisheries managers to adopt suitable scientific management practices to enhance the fishery production in these resources. | en_US |
dc.description.sponsorship | Not Available | en_US |
dc.language.iso | English | en_US |
dc.publisher | Not Available | en_US |
dc.relation.ispartofseries | Not Available; | - |
dc.subject | Artificial Neural Network, Inland Fisheries, Reservoir | en_US |
dc.title | Prediction of Fish Production in Tamil Nadu Reservoirs Using Artificial Neural Network (ANN) | en_US |
dc.title.alternative | Not Available | en_US |
dc.type | Research Paper | en_US |
dc.publication.projectcode | Not Available | en_US |
dc.publication.journalname | International Journal of Advanced Research in Computer and Communication Engineering | en_US |
dc.publication.volumeno | 10(2) | en_US |
dc.publication.pagenumber | 44-52 | en_US |
dc.publication.divisionUnit | Not Available | en_US |
dc.publication.sourceUrl | DOI 10.17148/IJARCCE.2021.10205 | en_US |
dc.publication.authorAffiliation | ICAR-National Academy of Agricultural Research Management | en_US |
dc.publication.authorAffiliation | Bharathiar University, Coimbatore | en_US |
dc.ICARdataUseLicence | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf | en_US |
dc.publication.journaltype | Not Available | en_US |
dc.publication.naasrating | Not Available | en_US |
dc.publication.impactfactor | Not Available | en_US |
Appears in Collections: | AEdu-NAARM-Publication |
Files in This Item:
File | Description | Size | Format | |
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IJARCCE.2021.10205.pdf | 364.26 kB | Adobe PDF | View/Open |
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