李娜,陆化杰,陈新军

• 1:上海海洋大学海洋科学学院
• 2:大洋渔业资源可持续开发省部共建教育部重点实验室
• 3:国家远洋渔业工程技术研究中心
• 4:远洋渔业协同创新中心

摘要(Abstract)：

根据2003-2011年渔汛期间我国鱿钓船在西南大西洋海域的生产统计数据,结合海洋遥感获得的海表温度(SST)和海面高度(SSH)等数据,以单位捕捞努力量渔获量(CPUE)和作业次数作为中心渔场指标,以月份、经度、纬度、SST和SSH为输入因子,利用BP神经网络方法构建西南大西洋阿根廷滑柔鱼中心渔场预报模型。比较14种不同结构的BP神经网络模型,以CPUE作为中心渔场预报指标的BP模型均较佳,其拟合残差范围为0.004 0~0.005 5,平均值为0.004 7;而以作业次数作为中心渔场预报指标的BP模型,其拟合残差范围为0.009 3~0.011 6,平均值为0.010 4。输入因子为月份、经度、纬度、SST和SSH,输出因子为初值化后的CPUE,网络结构为5-4-1时的BP神经网络模型为最佳,其拟合残差为0.004 025,该模型可用于阿根廷滑柔鱼中心渔场的预报。BP神经网络方法可为准确渔场预报提供新途径。

关键词(KeyWords)： 西南大西洋;阿根廷滑柔鱼;BP神经网络;渔场预报

Abstract:

Keywords:

基金项目(Foundation): 海洋局公益性行业专项(20155014);; 国家科技支撑计划(2013BAD13B01)

作者(Author): 李娜,陆化杰,陈新军

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