基于神经网络的南太平洋长鳍金枪鱼渔场预报

毛江美; 陈新军; 余景

基于神经网络的南太平洋长鳍金枪鱼渔场预报

1.
上海海洋大学海洋科学学院, 上海 201306;中国水产科学研究院南海水产研究所, 广东广州 510300
2.
上海海洋大学海洋科学学院, 上海 201306;上海海洋大学大洋渔业资源可持续开发省部共建教育部重点实验室, 上海 201306;国家远洋渔业工程技术研究中心, 上海 201306
3.
中国水产科学研究院南海水产研究所, 广东广州 510300

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

计量
- 文章访问数: 1341
- HTML全文浏览量: 34
- PDF下载量: 828
- 被引次数: 0
出版历程
- 收稿日期: 2016-05-08

Forecasting fishing ground of Thunnus alalunga based on BP neural network in the South Pacific Ocean

1.
College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China;South China Sea Fisheries Research Institute, Chinese Academy of Fishery Science, Guangzhou 510300, China
2.
College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China;The Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai Ocean University, Shanghai 201306, China;National Engineering Research Center for Oceanic Fisheries, Shanghai Ocean University, Shanghai 201306, China
3.
South China Sea Fisheries Research Institute, Chinese Academy of Fishery Science, Guangzhou 510300, China

摘要

摘要: 南太平洋长鳍金枪鱼是我国远洋渔业的重点捕捞对象；对南太平洋长鳍金枪鱼进行准确的渔场预报；可以提高捕捞效率；提高渔业的生产能力。本研究根据1993-2010年南太平洋长鳍金枪鱼的延绳钓生产数据以及海洋卫星遥感数据（海水表面温度；SST；海面高度；SSH）和ENSO（El Niño-Southern Oscillation）指标；采用DPS（data processing system）数据处理系统中的BP人工神经网络模型；以渔获产量（单位时间的渔获尾数）和单位捕捞努力量渔获量（CPUE；Catch per unit of effort）分别作为中心渔场的表征因子；并作为BP模型的输出因子；以月、经度、纬度、SST、SSH和ENSO指标等作为输入因子；分别构建4-3-1；5-4-1；5-3-1；6-5-1；6-4-1；6-3-1等BP模型结构；比较渔场预报模型优劣。研究结果表明；以CPUE作为输出因子的BP人工神经网络结构总体上较优；其中以6-4-1模型结构为最优；相对误差只有0.006 41。研究认为；以CPUE为输出因子的6-4-1结构的人工神经网络模型；能够准确预报南太平洋长鳍金枪鱼的渔场位置。
- 长鳍金枪鱼 /
- 神经网络 /
- CPUE /
- 中心渔场 /
- 南太平洋
Abstract: Albacore tuna (Thunnus alalunga) is an important target species for Chinese pelagic fishery in the South Pacific Ocean, and the accurate predicting of fishing ground can enhance catch efficiency and improve fishing operation. In this paper, we apply the BP artificial neural network model in the DPS (data processing system) to forecast fishing ground, according to the fishing yield statistics from longline, the sea surface temperature (SST), sea surface height (SST), and ENSO (El Niño-Southern Oscillation) index obtained by satellite remote sensing from 1993 to 2010. We consider the fishing yield (unit is the number of tuna) and CPUE (catch per unit of effort) as the character factors of fishing ground, the same as the output factors in BP artificial neural network respectively, and we take month, latitude, longitude, SST, SSH and ENSO index as the input factors, building the 4-3-1, 5-4-1, 5-3-1, 6-5-1, 6-4-1, 6-3-1 model and choosing the better results. It is found that the model used by CPUE is better than that model used by fishing yield, particularly the 6-4-1 model, and the relatively error is only 0.006 14, which can forecast the fishing ground of Thunnus alalunga in the South Pacific Ocean accurately.
- albacore tuna /
- artificial neural network /
- CPUE /
- fishing ground /
- South Pacific Ocean

HTML全文

参考文献(23)

闫敏, 张衡, 樊伟, 等. 南太平洋长鳍金枪鱼渔场CPUE时空分布及其与关键海洋环境因子的关系[J]. 生态学杂志, 2015, 34(11):3191-3197. Yan Min, Zhang Heng, Fan Wei, et al. Spatial-temporal CPUE profiles of the albacore tuna (Thunnus alalunga) and their relations to marine environmental factors in the South Pacific Ocean[J]. Chinese Journal of Ecology, 2015, 34(11):3191-3197.

Murray T. A review of the biology and fisheries for albacore, Thunnus alalunga, in the South Pacific Ocean[R]. FAO Fisheries Technical Paper. Rome:FAO, 1994.

陈锋, 郭爱, 周永东, 等. 南太平洋所罗门群岛海域长鳍金枪鱼的生物学特征[J]. 浙江海洋学院学报(自然科学版), 2012, 31(2):123-128. Chen Feng, Guo Ai, Zhou Yongdong, et al. Preliminary study of fishery biology of Albacore, Thunnus alalunga, in Solomon Islands of the South Pacific Ocean[J]. Journal of Zhejiang Ocean University (Nature Science), 2012, 31(2):123-128.

樊伟, 张晶, 周为峰. 南太平洋长鳍金枪鱼延绳钓渔场与海水表层温度的关系分析[J]. 大连水产学院学报, 2007, 22(5):366-371. Fan Wei, Zhang Jing, Zhou Weifeng. The relationship between longline albacore Thunnus alalunga and sea surface temperature in the South Pacific Ocean[J]. Journal of Dalian Fisheries University, 2007, 22(5):366-371.

徐洁, 陈新军, 杨铭霞. 基于神经网络的北太平洋柔鱼渔场预报[J]. 上海海洋大学学报, 2013, 22(3):432-438. Xu Jie, Chen Xinjun, Yang Mingxia. Forecasting on fishing ground of red flying squid (ommastrephes bartramii) in the North Pacific Ocean based on artificial neural net[J]. Journal of Shanghai Ocean University, 2013, 22(3):432-438.

Hagan M T, Demuth H B, Beale M H. Neural Network Design[M]. Boston:PWS Publishing, 1996.

蒋宗礼. 人工神经网络导论[M]. 北京:高等教育出版社, 2001:1-250. Jiang Zongli. Introduction to Aritificial Neural Networks[M]. Beijing:China Higher Education Press, 2001:1-250.

汪金涛, 高峰, 雷林, 等. 基于主成分和BP神经网络的智利竹筴鱼渔场预报模型研究[J]. 海洋学报, 2014, 36(8):65-71. Wang Jintao, Gao Feng, Lei Lin, et al. Application of BP neural network based on principal component analysis in fishing grounds of Chilean jack mackerel (Trachurus murphyi) in the southeast Pacific Ocean[J]. Haiyang Xuebao, 2014, 36(8):65-71.

范江涛. 南太平洋长鳍金枪鱼延绳钓渔业渔情预报研究[D]. 上海:上海海洋大学, 2011. Fan Jiangtao. Forecasting of fishing ground for Ablacore (Thunnus alalunga) in the South Pacific Ocean[D]. Shanghai:Shanghai Ocean University, 2011.

陈新军. 渔业资源与渔场学[M]. 北京:海洋出版社, 2004. Chen Xinjun. Fishery Resource Biology and Fishing[M]. Beijing:China Ocean Press, 2004.

闫敏, 张衡, 伍玉梅, 等. 2011年南太平洋长鳍金枪鱼渔场时空分布及其与主要海洋环境变化特征[J]. 渔业信息与战略, 2015, 30(2):119-127. Yan Min, Zhang Heng, Wu Yumei, et al. Spatial-temporal distribution of CPUE and relations with marine environment for albacore (Thunnus alalunga) in the South Pacific in 2011[J]. Fishery Information & Strategy, 2015, 30(2):119-127.

刘洪生, 蒋汉凌, 戴小杰. 中西太平洋长鳍金枪鱼渔场与海温的关系[J]. 上海海洋大学学报, 2014, 23(4):602-607. Liu Hongsheng, Jiang Hanling, Dai Xiaojie. Relationship between albacore (Thunnus alalunga) fishing grounds in the western and central Pacific and sea surface temperature[J]. Journal of Shanghai Ocean University, 2014, 23(4):602-607.

Sundermeyer M A, Rothschild B J, Robinson A R. Assessment of environmental correlates with the distribution of fish stocks using a spatially explicit model[J]. Ecological Modelling, 2006, 197(1/2):116-132.

龙华. 温度对鱼类生存的影响[J]. 中山大学学报(自然科学版), 2005, 44(S1):254-257. Long Hua. The effect of temperature on fish survival[J]. Acta Scientiarum Naturalium Universitatis Sunyatseni, 2005, 44(S1):254-257.

Wang N, Xu X L, Kestemont P. Effect of temperature and feeding frequency on growth performances, feed efficiency and body composition of pikeperch juveniles (Sander lucioperca)[J]. Aquaculture, 2009, 289(1/2):70-73.

苏艳莉. 环境温度对鱼类的影响及预防研究[J]. 农技服务, 2015, 32(7):191-192, 181. Su Yanli. Influence and prevention study of ambient temperature on fish[J]. Agricultural Technology Service, 2015, 32(7):191-192, 181.

Lu H J, Lee K T, Liao C H. On the relationship between El Niño/Southern oscillation and South Pacific albacore[J]. Fisheries Research, 1998, 39(1):1-7.

郭爱, 陈新军. ENSO与中西太平洋金枪鱼围网资源丰度及其渔场变动的关系[J]. 海洋渔业, 2005, 27(4):338-342. Guo Ai, Chen Xinjun. The relationship between ENSO and tuna purse-seine resource abundance and fishing grounds distribution in the western and central Pacific Ocean[J]. Marine Fisheries, 2005, 27(4):338-342.

吕俊梅, 琚建华, 张庆云, 等. 太平洋年代际振荡冷、暖背景下ENSO循环的特征[J]. 气候与环境研究, 2005, 10(2):238-249. Lü Junmei, Ju Jianhua, Zhang Qingyun, et al. The characteristics of ENSO cycle in different phases of Pacific decadal oscillation[J]. Climatic and Environmental Research, 2005, 10(2):238-249.

李崇银, 朱锦红, 孙照渤. 年代际气候变化研究[J]. 气候与环境研究, 2002, 7(2):209-219. Li Chongyin, Zhu Jinhong, Sun Zhaobo. The study interdecadel climate variation[J]. Climatic and Environmental Research, 2002, 7(2):209-219.

Zagaglia C R, Lorenzzetti J A, Stech J L, et al. Remote sensing data and longline catches of yellowfin tuna (Thunnus albacares) in the equatorial Atlantic[J]. Remote Sensing of Environment, 2004, 93(1/2):267-281.

宋婷婷, 樊伟, 伍玉梅. 卫星遥感海面高度数据在渔场分析中的应用综述[J]. 海洋通报, 2013, 32(4):474-480. Song Tingting, Fan Wei, Wu Yumei. Review on the fishery analysis with satellite remote sensing sea surface height data[J]. Marine Science Bulletin, 2013, 32(4):474-480.

徐冰, 陈新军, 田思泉, 等. 厄尔尼诺和拉尼娜事件对秘鲁外海茎柔鱼渔场分布的影响[J]. 水产学报, 2012, 36(5):696-707. Xu Bing, Chen Xinjun, Tian Siquan, et al. Effects of EI Niño/La Niño on distribution of fishing ground of Dosidicus gigas off Peru waters[J]. Journal of Fisheries of China, 2012, 36(5):696-707.

施引文献

资源附件(0)

访问统计