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摘要: 为了评价港口交通环境的安全性, 合理确定各环境要素的权重, 在应用因子分析方法分析全国九个港口环境要素数据的基础上, 对各港口的综合因子得分与港口事故数进行线性回归, 得到回归方程, 通过回归方程中各要素系数确定各环境要素对港口交通事故的影响程度。分析结果表明: 能见度、助航标志、VTS管理程度和分道通航程度对交通安全影响较大, 航道长度和交叉点数影响较小, 基本上反映了各环境要素对港口交通事故的影响程度, 可见因子分析方法可定量确定各环境要素对交通安全的影响, 可用于港口交通事故的原因分析与评价。Abstract: In order to evaluate the safety of port traffic environment and determine the weighting of each environment factor, the environment factors data of nine ports were analyzed by factor analysis method, the relationship of port integrated factor scores and port traffic accident numbers was studied, their regression equation was deduced, each factor effect degree on port traffic accidents were determined by each factor coefficient in regression equation.Analysis result indicates that visibility, navigational aids, VTS management degree and traffic separation degree have greater effect on traffic safety, the length of channel and the number of turning points have less effect on traffic safety, which basically reflects the effect degrees of environment factors on port traffic accidents.It is shown that factor analysis method can quantitatively determine the effect degree of each environment factor on traffic accidents, it can be applied to the relationship analysis and assessment of port traffic accidents.
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表 1 原始数据
Table 1. Primal Data
港口序号 x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 x11 Y 1 27.00 40.40 3.00 9.50 5.00 0.10 1.50 57.86 5.00 5.00 99.98 29.20 2 11.30 8.60 3.00 14.00 2.00 0.25 1.20 30.74 4.70 4.18 99.98 3.20 3 9.80 80.20 1.50 20.20 1.00 0.14 1.60 41.20 5.00 4.55 99.98 4.80 4 24.20 77.40 0.50 4.20 2.00 0.24 2.10 13.98 4.50 4.06 99.98 6.40 5 54.00 94.80 3.00 7.40 8.00 0.07 8.10 45.70 4.90 4.44 99.92 39.00 6 16.10 139.00 2.90 3.60 7.00 0.36 0.68 14.00 4.80 4.50 99.92 23.00 7 28.00 21.40 5.00 13.60 6.00 0.20 17.60 21.80 5.00 4.21 99.92 3.00 8 25.00 73.30 3.50 63.70 1.30 0.20 2.90 42.00 5.00 5.00 99.90 37.00 9 13.30 11.30 3.50 40.80 18.00 0.10 0.50 32.80 4.60 4.11 99.90 40.00 表 2 旋转后因子贡献及贡献率
Table 2. Contributivenesses and Contributiveness Ratios of Factors
1 2 3 4 5 特征值 2.434 3 2.151 0 2.054 2 2.027 3 1.483 6 贡献率 22.129 7 19.554 3 18.674 6 18.430 0 13.487 7 累计贡献率 22.129 7 41.684 0 60.358 6 78.788 6 92.276 3 表 3 载荷矩阵
Table 3. Load Matrix
x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 x11 1 0.032 2 0.181 9 0.196 8 0.399 2 -0.541 3 -0.072 5 -0.013 0 0.591 3 0.847 8 0.913 9 0.008 3 2 0.031 0 -0.030 9 0.583 5 0.680 8 0.666 1 -0.079 5 0.040 6 -0.012 1 0.023 6 0.089 8 -0.940 6 3 0.528 2 -0.274 8 0.009 5 0.035 4 0.349 4 -0.955 6 0.011 5 0.776 5 0.151 7 0.187 4 0.042 1 4 0.522 5 -0.176 3 0.652 3 -0.265 7 0.008 9 -0.071 6 0.971 0 -0.103 1 0.421 5 -0.153 4 -0.259 4 5 0.576 7 0.909 2 -0.318 5 -0.336 3 -0.058 6 0.136 0 -0.026 1 -0.122 9 0.034 6 0.180 5 -0.195 9 表 4 因子得分矩阵
Table 4. Factor Score Matrix
x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 x11 1 -0.095 2 0.069 6 0.096 8 0.190 1 -0.294 2 0.093 5 -0.012 3 0.166 0 0.355 8 0.375 2 0.018 1 2 -0.023 0 0.102 6 0.188 9 0.346 8 0.322 0 0.031 5 -0.100 9 -0.050 7 -0.051 0 0.064 5 -0.472 6 3 0.289 7 -0.099 9 -0.122 9 -0.075 9 0.229 4 -0.502 2 -0.066 8 0.349 1 -0.063 1 -0.003 7 0.077 2 4 0.213 0 -0.112 3 0.291 7 -0.216 5 -0.096 4 0.035 5 0.518 0 -0.109 0 0.206 1 -0.120 8 -0.018 9 5 0.421 7 0.616 7 -0.210 2 -0.182 9 0.075 0 0.029 0 -0.056 1 -0.062 6 -0.029 7 0.103 5 -0.211 0 表 5 因子得分
Table 5. Factor Scores
港口序号 1 2 3 4 5 6 7 8 9 F1 0.984 1 -0.312 9 0.757 3 -1.270 2 -0.292 8 -0.104 4 -0.114 5 1.689 1 -1.335 6 F2 -0.745 4 -0.817 4 -0.914 9 -1.151 2 0.090 0 0.496 6 0.133 6 1.218 9 1.689 9 F3 1.206 2 -0.538 7 0.076 5 -0.422 9 1.535 0 -1.612 1 -0.590 0 -0.421 6 0.767 5 F4 -0.212 3 -0.186 0 -0.675 5 -0.598 7 0.843 7 -0.302 0 2.343 0 -0.407 8 -0.804 3 F5 -0.290 8 -1.342 2 -0.219 8 0.591 0 1.554 2 1.365 5 -0.746 2 0.025 7 -0.937 4 表 6 综合因子得分
Table 6. Integrated Factor Score
港口序号 1 2 3 4 5 6 7 8 9 综合因子得分F 0.237 3 -0.590 6 -0.163 8 -0.667 3 0.655 2 -0.106 8 0.240 3 0.500 4 -0.104 6 事故数Y 29.20 3.20 4.80 6.40 39.00 23.00 3.00 37.00 40.00 -
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