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摘要: 为解决对同一事物采用不同的安全评价方法而产生的结论多样性问题, 提出了组合评价模式。以中国沿海10个港口的航行环境安全程度为例, 采用主成分分析法、因子分析法、TOPSIS法、模糊综合评价法和灰色综合评价法, 得到了5组不同的排序结果, 再用序号总和理论与众数理论对这5种方法所得结果作组合处理, 得到惟一排序结论。该结论与客观实际相符, 优于任何单一方法的排序结果, 得到了船长们的认可, 表明使用组合评价模式, 有助于弥补单一评价方法的缺陷。Abstract: In order to solve the assessment diversity on the same thing caused by different assessment methods, combined assessment model(CAM) was proposed. 10 seaports of China were used as a sample case of safety level ordering assessment of navigation environment. The methods of principal component analysis(PCA), factor analysis, TOPSIS, fuzzy aggregate assessment, gray aggregate assessment were employed to the case separately, and 5 different group results were obtained. The theory of serial number summation and mode theory were adopted to coordinate the results of the 5 methods, and come to an only ordering conclusion. The conclusion based on CAM is much close to the fact, excelled to any result of single method, and generally accepted by senior master mariners.
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Key words:
- maritime safety /
- CAM /
- theory of serial number summation /
- mode theory
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表 1 港口航行环境指标
Table 1. Navigation environment indices of harbours
编号 港口 能见度(1)/(d·a-1) 大风(2)/(d·a-1) 最大流速/kn 航道长/n mile 交叉点数 船宽/航道宽 密度 加权交通量 1 大连港 27.0 40.4 3.0 9.5 5 0.100 1.50 57.86 2 秦皇岛 11.3 8.6 3.0 14.0 2 0.250 1.20 30.74 3 天津港 9.8 80.2 1.5 20.2 1 0.140 1.60 41.20 4 烟台港 24.2 77.4 0.5 4.2 2 0.240 2.10 13.98 5 青岛港 54.0 94.8 3.0 7.4 8 0.065 8.10 45.70 6 连云港 16.1 139.0 2.9 3.6 7 0.360 0.68 14.00 7 上海港 24.7 51.1 6.0 85.5 29 0.120 24.30 76.24 8 宁波港 28.0 21.4 5.0 13.6 6 0.200 17.60 21.80 9 黄埔港 25.0 73.3 3.5 63.7 1 0.200 2.90 42.00 10 湛江港 13.3 11.3 3.5 40.8 18 0.100 0.50 32.80 注: (1)能见度: 该港口近5 a来能见度低于1 km的年平均天数; (2)大风: 该港口近5 a风力达6级(蒲氏风级)及以上的年平均天数。 表 2 经标准化处理的港口航行环境指标
Table 2. Standardized Navigation environment indices of harbours
编号 港口 能见度/(d·a-1) 大风/(d·a-1) 最大流速/kn 航道长/n mile 交叉点数 船宽/航道宽 密度 加权交通量 1 大连港 0.287 0 0.469 0.122 0.596 0.327 0.861 0.547 -1.035 2 秦皇岛 -0.944 0 1.240 0.122 0.436 0.662 -0.805 0.584 0.352 3 天津港 -1.062 0 -0.495 1.089 0.215 0.774 0.416 0.535 -0.182 4 烟台港 0.067 5 -0.427 1.734 0.784 0.662 -0.694 0.475 1.210 5 青岛港 2.405 0 -0.849 0.122 0.670 -0.007 1.250 -0.247 -0.412 6 连云港 -0.567 0 -1.921 0.187 0.806 0.103 -2.028 0.646 1.209 7 上海港 0.106 0 0.209 -1.811 -2.108 -2.354 0.639 -2.199 -1.976 8 宁波港 0.365 0 0.929 -1.166 0.450 0.215 -0.249 -1.391 0.810 9 黄埔港 0.130 3 -0.328 -0.199 -1.332 0.740 -0.249 0.379 -0.223 10 湛江港 -0.780 0 1.174 -0.190 -0.517 -1.125 0.861 0.668 0.247 表 3 评价结果
Table 3. Assessment results
港口 主成分分析法 因子分析法 TOPSIS法 模糊综合评价法 灰色综合评价法 组合评价法 得分 排序 得分 排序 得分 排序 得分 排序 得分 排序 结论 排序 大连港 -0.60 6 0.50 5 0.642 3 0.475 3 0.490 2 19 3 秦皇岛 1.67 4 0.36 6 0.603 4 0.480 4 0.497 3 21 4 天津港 2.17 3 0.87 2 0.602 5 0.453 1 0.516 4 15 2 烟台港 4.32 2 1.59 1 0.676 1 0.460 2 0.394 1 7 1 青岛港 -1.04 7 0.75 4 0.673 2 0.550 6 0.567 6 25 5 连云港 5.06 1 0.76 3 0.516 9 0.521 5 0.600 8 26 6 上海港 -8.29 10 -3.43 10 0.325 10 0.634 9 0.782 10 49 10 宁波港 -1.29 8 -0.63 9 0.572 7 0.671 10 0.597 7 41 9 黄埔港 -0.15 5 -0.20 7 0.546 8 0.590 8 0.710 9 37 8 湛江港 -1.84 9 -0.59 8 0.576 6 0.564 7 0.562 5 35 7 -
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