考虑多影响因素的渔船单船捕捞能力评估方法
S11+3%S11+5; 针对以往海洋机动渔船捕捞能力评估研究中考虑影响因素较少,对各影响因素的主观权重值和客观权重值综合分析不足,不能给出渔船单船捕捞能力量化值等问题,该研究提出了考虑多影响因素的渔船单船捕捞能力评估模型.首先,考虑多种影响渔船捕捞能力的因素,建立单船捕捞能力评估指标体系,将其分为可量化指标和不可量化指标,并初步制定了不可量化指标评估标准.其次,利用专家、渔民调查问卷中的数据,运用层次分析法计算各指标主观权重值,结果表明各指标权重依次为:捕捞装备(0.108)、功率(0.094)、拖网(0.074)、作业时长(0.071)、总吨(0.049)、探鱼仪器(0.047)、刺网(0...
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| Published in | 农业工程学报 Vol. 40; no. 5; pp. 90 - 98 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | Chinese |
| Published |
上海海洋大学工程学院,上海 201306%上海海洋大学经济管理学院,上海 201306
01.03.2024
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1002-6819 |
| DOI | 10.11975/j.issn.1002-6819.202308193 |
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| Abstract | S11+3%S11+5; 针对以往海洋机动渔船捕捞能力评估研究中考虑影响因素较少,对各影响因素的主观权重值和客观权重值综合分析不足,不能给出渔船单船捕捞能力量化值等问题,该研究提出了考虑多影响因素的渔船单船捕捞能力评估模型.首先,考虑多种影响渔船捕捞能力的因素,建立单船捕捞能力评估指标体系,将其分为可量化指标和不可量化指标,并初步制定了不可量化指标评估标准.其次,利用专家、渔民调查问卷中的数据,运用层次分析法计算各指标主观权重值,结果表明各指标权重依次为:捕捞装备(0.108)、功率(0.094)、拖网(0.074)、作业时长(0.071)、总吨(0.049)、探鱼仪器(0.047)、刺网(0.040)、船长(0.032)、张网(0.028)、围网(0.024)、钓业(0.021)、作业环境(0.019)、钢质材质(0.019)、罩网(0.017)、玻璃钢材质(0.016)、船龄(0.013)、木制材质(0.012);渔具相关指标权重依次为:网具主尺寸(0.402)、网具结构(0.149)、装配技术(0.093)、制造材料(0.051).最后,为兼顾主客观权重优点,基于加法合成法、博弈论法、最小鉴别信息法对各指标权重值进行组合计算,以获得目标权重值,并根据某省渔船数据对建立的模型进行验证分析,通过Spearman等级相关系数法计算捕捞能力评估值与实际渔获量之间的等级相关系数,结果表明基于博弈论法得到的结果相关性最高,相关系数为0.937,证实了组合权重值和评估模型的科学性和合理性.研究结果可为渔业管理部门制定科学合理的渔业资源调控政策提供依据. |
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| AbstractList | S11+3%S11+5; 针对以往海洋机动渔船捕捞能力评估研究中考虑影响因素较少,对各影响因素的主观权重值和客观权重值综合分析不足,不能给出渔船单船捕捞能力量化值等问题,该研究提出了考虑多影响因素的渔船单船捕捞能力评估模型.首先,考虑多种影响渔船捕捞能力的因素,建立单船捕捞能力评估指标体系,将其分为可量化指标和不可量化指标,并初步制定了不可量化指标评估标准.其次,利用专家、渔民调查问卷中的数据,运用层次分析法计算各指标主观权重值,结果表明各指标权重依次为:捕捞装备(0.108)、功率(0.094)、拖网(0.074)、作业时长(0.071)、总吨(0.049)、探鱼仪器(0.047)、刺网(0.040)、船长(0.032)、张网(0.028)、围网(0.024)、钓业(0.021)、作业环境(0.019)、钢质材质(0.019)、罩网(0.017)、玻璃钢材质(0.016)、船龄(0.013)、木制材质(0.012);渔具相关指标权重依次为:网具主尺寸(0.402)、网具结构(0.149)、装配技术(0.093)、制造材料(0.051).最后,为兼顾主客观权重优点,基于加法合成法、博弈论法、最小鉴别信息法对各指标权重值进行组合计算,以获得目标权重值,并根据某省渔船数据对建立的模型进行验证分析,通过Spearman等级相关系数法计算捕捞能力评估值与实际渔获量之间的等级相关系数,结果表明基于博弈论法得到的结果相关性最高,相关系数为0.937,证实了组合权重值和评估模型的科学性和合理性.研究结果可为渔业管理部门制定科学合理的渔业资源调控政策提供依据. |
| Abstract_FL | A monitoring system is required for the offshore fishing capacity.Mathematical modelling can also be applied to analyze the impact of fishing vessel parameters on fishing capacity,from the perspectives of fishery engineering and ship design.However,it is still lacking in the fishing capacity of a single vessel.Only a few influencing factors have been considered,leading to the insufficient analysis of the subjective and objective weights of each influencing factor.Consequently,there is a high demand for the quantitative fishing capacity of a fishing vessel.In this study,an assessment model of single-vessel fishing capacity was proposed to consider the multiple influencing factors.The fishing data was also collected to conduct modelling analysis.Firstly,a comprehensive analysis was made to determine the impact of each fishing vessel parameter on fishing capacity.An evaluation index system of single-vessel fishing capacity was then established to combine the opinions of experts and fishermen in the fields.The indicators were divided into the quantifiable and non-quantifiable ones.Preliminary evaluation criteria were also formulated for the non-quantifiable indicators.Secondly,a questionnaire titled"Questionnaire on the Weight of Factors Affecting the Fishing Capacity of China's Offshore Fishing Vessels"was distributed to collect the scoring data from experts and fishermen.The analytic hierarchy was used to calculate the weights of each indicator.The results indicated that the weights of each indicator were as follows:fishing equipment(0.108),power(0.094),trawl(0.074),operating time(0.071),total tonnage(0.049),fish detection equipment(0.047),gillnet(0.040),captain(0.032),net(0.028),purse seine(0.024),fishing(0.021),operating environment(0.019),steel material(0.019),cover net(0.017),fiberglass material(0.016),ship age(0.013),wooden material(0.012).The weights of fishing gear-related indicators were:main size of net gear(0.402),net structure(0.149),assembly technology(0.093),and manufacturing materials(0.051).Finally,the advantages of subjective and objective weights were given to combine the subjective weights from the analytic hierarchy process(AHP)and the objective weights from the Random Forest using the additive synthesis,and game theory.The minimum discriminant information was obtained from the target weights,in order to facilitate further analysis and calculations in the following sections.A validation analysis was then conducted.Given that the fishing vessel capacity assessment model was suitable for the motorized fishing vessels,a random sample of data from 12 motorized fishing vessels was collected for validation.Spearman rank correlation coefficient was used to calculate the graded correlation coefficient between the fishing capacity evaluation and the actual catch.The results revealed that the outcomes with the game theory shared the highest correlation,with a correlation coefficient as high as 0.937.Therefore,the combined weights were used as the target for the evaluation indicators.The finding can greatly contribute to the scientific management of offshore fisheries,in order to alleviate the overfishing in the sustainable marine industry. |
| Author | 崔修杰 吕超 刘爽 |
| AuthorAffiliation | 上海海洋大学工程学院,上海 201306%上海海洋大学经济管理学院,上海 201306 |
| AuthorAffiliation_xml | – name: 上海海洋大学工程学院,上海 201306%上海海洋大学经济管理学院,上海 201306 |
| Author_FL | LIU Shuang CUI Xiujie LYU Chao |
| Author_FL_xml | – sequence: 1 fullname: LIU Shuang – sequence: 2 fullname: CUI Xiujie – sequence: 3 fullname: LYU Chao |
| Author_xml | – sequence: 1 fullname: 刘爽 – sequence: 2 fullname: 崔修杰 – sequence: 3 fullname: 吕超 |
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| DocumentTitle_FL | Method for assessing single-vessel fishing capacity considering multiple influencing factors |
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| Keywords | composite weights analytic hierarchy process 层次分析法 组合权重 fishing vessel multi-factor analysis 渔船 多因素分析 单船捕捞能力 single-vessel fishing capacity |
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