港口交通事故与环境要素关系

郑中义; 黄忠国; 吴兆麟

港口交通事故与环境要素关系

大连海事大学交通工程与物流学院, 辽宁大连 116026

基金项目:

国家自然科学基金项目 60172044

详细信息

作者简介:
郑中义(1964-), 男, 河北安国人, 大连海事大学教授, 从事海上交通安全保障与防护技术研究

中图分类号: U698.6
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- 被引次数: 0
出版历程
- 收稿日期: 2005-10-25
- 刊出日期: 2006-03-25

Relationship Analysis of Port Traffic Accidents and Port Environment Factors

School of Traffic Engineering and Logistics, Dalian Maritime University, Dalian 116026, Liaoning, China

More Information

Author Bio:
ZHENG Zhong-yi(1964-), male, PhD, professor, 86-411-84728381, dlzzyi@sina.com

摘要

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。
- 海上交通安全 /
- 港口交通事故 /
- 港口环境要素 /
- 因子分析方法 /
- 主因子
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.
- marine traffic safety /
- port traffic accidents /
- port environment factors /
- factor analysis method /
- principal factor

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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

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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

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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

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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

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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

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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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参考文献(8)

[1]	何晖光, 吴兆麟, 方祥麟. 海上交通环境的综合评价方法[J]. 大连海事大学学报, 1997, 23 (3): 36-41. https://www.cnki.com.cn/Article/CJFDTOTAL-DLHS703.008.htm HE Hui-guang, WUZhao-lin, FANG Xiang-lin. Integrated Assessment Method of Marine Traffic Environment[J]. Journal of Dalian Maritime University, 1997, 23 (3): 36-41. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-DLHS703.008.htm
[2]	王芳. 主成分分析与因子分析的异同比较及应用[J]. 统计教育, 2003, 5 (5): 14-17. https://www.cnki.com.cn/Article/CJFDTOTAL-TJJY200305005.htm WANG Fang. Comparison and Application of Principal Component Analysis and Factor Analysis[J]. Statistical Education, 2003, 5 (5): 14-17. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-TJJY200305005.htm
[3]	于建英, 何旭宏. 数据统计分析与Spss应用[M]. 北京: 人民邮政出版社, 2004.
[4]	任中奇. 多元统计分析在多指标综合评价问题中的应用[J]. 辽宁工程技术大学学报: 自然科学版, 1994, 13 (1): 97-100. https://www.cnki.com.cn/Article/CJFDTOTAL-FXKY401.026.htm REN Zhong-qi. The Application of Multiple Statistics Analysisin Multiple Indexes Comprehensive Evaluation[J]. Journal of Liaoning Technology University: Natural Science Edition, 1994, 13 (1): 97-100. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-FXKY401.026.htm
[5]	岑况. 因子分析中变量和样本空间的统一[J]. 地质科技情报, 1994, 13 (4): 93-97. CEN Kuang. Combination of Variable and Object Spacein Factor Analysis[J]. Geological Science and Technology Information, 1994, 13 (4): 93-97. (in Chinese)
[6]	郑士源. 国际干散货航运市场的评价[J]. 交通运输工程学报, 2004, 4 (4): 89-92. http://transport.chd.edu.cn/article/id/200404022 ZHENG Shi-yuan. Evaluation of International Dry Bulk Shipping Market[J]. Journal of Traffic and Transportation Engineering, 2004, 4 (4): 89-92. (in Chinese) http://transport.chd.edu.cn/article/id/200404022
[7]	藤井弥平. 海上交通工学[M]. 东京: 海文堂, 1981.
[8]	郑中义, 吴兆麟, 杨丹. 港口船舶事故致因的灰色关联分析模型[J]. 大连海事大学学报, 1997, 23 (2): 61-64. https://www.cnki.com.cn/Article/CJFDTOTAL-DLHS702.014.htm ZHENG Zhong-yi, WU Zhao-lin, YANG Dan. Analysis Model of Accident's Main Causes on Port Vessels Incidence by Grey System Theory[J]. Journal of Dalian Maritime University, 1997, 23 (2): 61-64. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-DLHS702.014.htm