Using Fuzzy Synthesis Approach to Extract Fishing Efforts Directed on Albacore for Taiwanese Longline Fleets in the Indian Ocean

以模糊綜合評判法分離臺灣鮪延繩釣漁船在印度洋捕撈長鰭鮪的漁獲努力量

汪淑慧(Shu-Hwei Wang) ； 許建宗(Chien-Chung Hsu) ； 劉錫江(Hsi-Chiang Liu)

《臺灣水產學會刊》 28卷2期 (2001/06) Pp. 105-117

https://doi.org/10.29822/JFST.200106.0004

摘要

印度洋長鰭鮪漁業是臺灣鮪延繩釣漁船最重要的鮪漁業之一。印度洋長鰭鮪系群評估通常應用臺灣鮪延繩鈞漁船所提送的漁業資料。然而，這些漁業資料可能包含有兩種造成標準化單位努力漁獲量困難的漁業型態。因此，本研究以1979-1997年的作業報表單日漁獲資訊做分析的基本資料，使用模糊綜合評判法來分離不同漁業型態的漁獲努力量。模糊轉換包含權重向量和因子函數矩陣，權重向量使用非等值真值，和因子函數矩陣使用在漁船噸位級別、漁撈區域、使用鉤數和海表層水溫定義下之捕獲長鰭鮪、大目鮪和黃鰭鮪之長鰭鮪比值分布。由模糊轉換的運算所得到的結果，可連續獲得新的漁獲量。漁獲努力量和單位努力漁獲量序列。本研究結果可初步証實模糊綜合評判法是可以用於分離不同漁業型態的漁獲努力量方法之一。

並列摘要

Indian albacore fishery is one of the most important tuna fisheries for Taiwanese long-line fleets. The assessment of the Indian albacore stock is usually based on fishery-dependent data submitted from Taiwanese longline vessels. Moreover, those fishery data may contain two fishing types that are able to make standardizing catch per unit effort difficult. Therefore, in the present study, an alternative approach of fuzzy synthesis clustering is used to partition the fishing efforts from different fishing types, and the daily set catch information of logbooks from 1979 to 1997 is used as the fundamental data for this purpose. A fuzzy transformation is composed of weighting vector and membership function, in which the weighting vector used an unequal crisp value and the membership function used the distribution of percent catch of albacore in total of albacore, bigeye tuna, and yellowf in tuna under the factors of vessels' tonnage categories, fishing area, the number of hooks used and sea surface temperature. Subsequently, the result is obtained from the computation of fuzzy transformation, then, new catch, fishing effort and catch per unit effort series were obtained. The fuzzy synthesis is evidenced as on of the methods using for partitioning fishing efforts from different fishing types in preliminary.

並列關鍵字

Albacore ； Fuzzy Synthesis ； Fishing Effort ； Longline ； Membership Function