Comparison between different modeling techniques for assessing the role of environmental variables in predicting the catches of major pelagic fishes off India’s north-west coast

IF 0.5 4区 地球科学 Q4 Earth and Planetary Sciences
V. K. Yadav, S. Jahageerdar, J. Adinarayana
{"title":"Comparison between different modeling techniques for assessing the role of environmental variables in predicting the catches of major pelagic fishes off India’s north-west coast","authors":"V. K. Yadav, S. Jahageerdar, J. Adinarayana","doi":"10.56042/ijms.v51i02.66010","DOIUrl":null,"url":null,"abstract":"The contribution of four variables, namely Chlorophyll -a (Chl- a ), Sea Surface Temperature (SST), diffuse attenuation coefficient (Kd_490 or Kd), and Photosynthetically Active Radiation (PAR), in predicting the catches of major pelagic fish species (Indian mackerel, horse mackerel, Bombay duck, oil sardine, and other sardines) was evaluated using Canonical Correlation Analysis (CCA). The outcome of the analysis was compared with those obtained by using the following models and methods: the Generalized Linear Model (GLM), the Generalized Additive Model (GAM), connection weight methods, and the explanatory methods of Artificial Neural Networks (ANNs). Both the sets of results were in agreement. Neither the GAM nor the ANNs method showed any clear advantage over each other, although the GAM performed better than the GLM.","PeriodicalId":51062,"journal":{"name":"Indian Journal of Geo-Marine Sciences","volume":"47 1","pages":""},"PeriodicalIF":0.5000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Indian Journal of Geo-Marine Sciences","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.56042/ijms.v51i02.66010","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Earth and Planetary Sciences","Score":null,"Total":0}
引用次数: 0

Abstract

The contribution of four variables, namely Chlorophyll -a (Chl- a ), Sea Surface Temperature (SST), diffuse attenuation coefficient (Kd_490 or Kd), and Photosynthetically Active Radiation (PAR), in predicting the catches of major pelagic fish species (Indian mackerel, horse mackerel, Bombay duck, oil sardine, and other sardines) was evaluated using Canonical Correlation Analysis (CCA). The outcome of the analysis was compared with those obtained by using the following models and methods: the Generalized Linear Model (GLM), the Generalized Additive Model (GAM), connection weight methods, and the explanatory methods of Artificial Neural Networks (ANNs). Both the sets of results were in agreement. Neither the GAM nor the ANNs method showed any clear advantage over each other, although the GAM performed better than the GLM.
评估环境变量在预测印度西北海岸主要远洋鱼类捕获量中的作用的不同建模技术之间的比较
利用典型相关分析(CCA)评价了叶绿素a (Chl- a)、海面温度(SST)、扩散衰减系数(Kd_490或Kd)和光合有效辐射(PAR) 4个变量对主要远洋鱼类(印度鲭鱼、马鲛鱼、孟买鸭、油沙丁鱼和其他沙丁鱼)渔获量的预测作用。将分析结果与广义线性模型(GLM)、广义加性模型(GAM)、连接权法和人工神经网络(ANNs)解释方法得到的结果进行了比较。两组结果是一致的。GAM和人工神经网络方法都没有表现出明显的优势,尽管GAM比GLM表现得更好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
1.50
自引率
0.00%
发文量
0
审稿时长
1.7 months
期刊介绍: Started in 1972, this multi-disciplinary journal publishes full papers and short communications. The Indian Journal of Geo-Marine Sciences, issued monthly, is devoted to the publication of communications relating to various facets of research in (i) Marine sciences including marine engineering and marine pollution; (ii) Climate change & (iii) Geosciences i.e. geology, geography and geophysics. IJMS is a multidisciplinary journal in marine sciences and geosciences. Therefore, research and review papers and book reviews of general significance to marine sciences and geosciences which are written clearly and well organized will be given preference.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信