Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
Neural Networks and Rules-based Systems used to Find Rational and
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Assessment of length-weight relationship and condition factor of a commercially important mollusc species, Periwinkle, Tympanotonus fuscatus, from Okrika estuary was conducted from October, 2015 to February, 2016. A total of 120 samples of the species were hand-picked from the mangrove ecosystem of Okrika. The results obtained showed that the gastropod species had negative allometric growth patterns with a growth exponent, b value of 2.18. This value was confirmed as negative allometric, because it was significantly different (p
Ogunola Oluniyi Solomon. 2017. \u201cPreliminary Investigation of Some Biological Aspects of Length-Weight Relationship and Condition Factor of Periwinkle (Tympanotonus Fuscatus, Linnaeus 1758) From Okrika Estuary\u201d. Global Journal of Science Frontier Research - E: Marine Science GJSFR-E Volume 17 (GJSFR Volume 17 Issue E1): .
Crossref Journal DOI 10.17406/GJSFR
Print ISSN 0975-5896
e-ISSN 2249-4626
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Total Score: 113
Country: Germany
Subject: Global Journal of Science Frontier Research - E: Marine Science
Authors: Ogunola Oluniyi Solomon, Andreas Kunzmann, Onada Olawale Ahmed (PhD/Dr. count: 0)
View Count (all-time): 120
Total Views (Real + Logic): 3305
Total Downloads (simulated): 1666
Publish Date: 2017 09, Sat
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Neural Networks and Rules-based Systems used to Find Rational and
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Assessment of length-weight relationship and condition factor of a commercially important mollusc species, Periwinkle, Tympanotonus fuscatus, from Okrika estuary was conducted from October, 2015 to February, 2016. A total of 120 samples of the species were hand-picked from the mangrove ecosystem of Okrika. The results obtained showed that the gastropod species had negative allometric growth patterns with a growth exponent, b value of 2.18. This value was confirmed as negative allometric, because it was significantly different (p
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