Application of combined empowerment cloud model to expressway channel adaptability assessments
Article Text (Baidu Translation)
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摘要: 为了科学评价高速公路通道与区域发展之间的适应性，分析了高速公路通道对区域经济的影响因素；利用反映像相关矩阵的评价指标筛选方法进行指标降维，建立了区域高速公路通道适应性评价指标体系；通过灰色关联度进行客观赋权，计算了模型各评价指标的权重，并在算法中弥补因层次分析法(AHP)主观判断造成的误差；建立了AHP-灰色关联度混合约束锥的云模型，并对2019年沈海高速公路通道46个路段进行评价；针对不适应路段在扩容改造、差异化收费和主动交通管理等方面的问题，提出了相关改进意见和具体措施。研究结果表明：将高速公路适应性评价指标由18个降为9个，在不影响模型精度的同时，可以大幅度降低模型复杂度；沈海高速公路的适度超前路段、总体适应路段、初步适应路段、相对滞后路段、严重制约路段占比分别为6.52%、21.74%、43.48%、21.74%、6.52%；与传统数据包络分析(DEA)模型相比，AHP-灰色关联度混合约束锥的云模型评估出的适度超前路段减小17.39%，初步适应路段增加43.48%，严重制约路段增加6.52%，并以福州市内路段、泉州市内路段、晋江市内路段和厦门市内路段不适应程度最为严重，这些严重制约路段在传统DEA模型中并未评价出来。可见，使用AHP-灰色关联度组合赋权的云模型可以提高评价结果的准确性和科学性，是解决高速公路通道适应性评价问题的一种有效方法。Abstract: In order to scientifically assessment the adaptability between expressway channels and regional development, the influencing factors of expressway channels on the regional economy were analyzed. The evaluation index screening method of the anti-image correlation matrix was used for index dimensionality reduction, and the evaluation index system of expressway adaptability of regional channels was established. The weights of each evaluation index of the model were calculated by the objective assignment through the gray correlation, and the errors caused by the subjective judgment of the analytic hierarchy process (AHP) were compensated in the algorithm. A cloud model with a hybrid AHP-gray correlation degree constrained cone was developed, and 46 road sections of the Shenhai Expressway channel in 2019 were evaluated. Relevant improvement opinions and specific measures were proposed to address the problems of the non-adaptive road sections in terms of capacity expansion and reconstruction, differentiated charging, and active traffic management. Research results show that the model complexity can reduces substantially without affecting the model accuracy by reducing the expressway adaptability evaluation indexes from 18 to 9. By evaluating the Shenhai Expressway, the moderately over-adapted road sections, the overall adaptive road sections, the preliminary adaptive road sections, the relative lagging road sections and the seriously constrained road sections account for 6.52%, 21.74%, 43.48%, 21.74% and 6.52%, respectively. Compared with the traditional data enveloping analysis (DEA) model, the cloud model with AHP-grey correlation degree constraint cone has 17.39% fewer moderately over-adapted road sections, 43.48% more preliminary adaptive road sections, and 6.52% more seriously constrained road sections. In particular, the degree of maladaptation is the most serious in the inner sections of Fuzhou City, Quanzhou City, Jinjiang City, and Xiamen City, which are not evaluated by the traditional DEA model. It can be seen that the accuracy and scientificity of the evaluation results can be improved by the cloud model using the AHP-gray correlation degree combination assignment, and it is an effective method to solve the problem of expressway channel adaptability assessment.
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Key words:
- transportation /
- expressway /
- channel adaptability /
- cloud model /
- roadway congestion /
- income distribution coefficient
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图 2 福建省2019年高速公路运输情况
Figure 2. Expressway transportation situation in Fujian Province in 2019
图 5 沈海高速路段适应性评价等级
Figure 5. Adaptability assessment grades of Shenhai Expressway sections
表 1 筛选后适应性评价指标
Table 1. Adaptability assessment indicators after screening
指标构成 指标类型 单项指标 高速公路技术指标 技术特征 节点可达性系数 服务水平 道路拥挤度 运输能力 日均客运密度 日均货运密度 人均地区生产总值 高速公路经济效益指标 直接经济效益 第二、三产业占地区生产总值比例 恩格尔系数 间接经济效益 第二、三产业就业人数 收入分配系数 
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表 2 评价指标因子划分标准
Table 2. Division standards of assessment index factors
一级指标 二级指标 适度超前 总体适应 初步适应 相对滞后 严重制约 技术特征 节点可达性系数 0~0.4 0.4~0.6 0.6~1.0 1.0~1.6 ＞1.6 服务水平 道路拥挤度 0~0.3 0.3~0.5 0.5~0.7 0.7~0.9 ＞0.9 运输能力 日均客运密度/(万人·km·km-1) ＞1.4 1.2~1.4 0.9~1.2 0.6~0.9 ＜0.6 日均货运密度/(104 t·km·km-1) ＞3.2 2.7~3.2 1.8~2.7 0.8~1.8 ＜0.8 直接经济效益 人均地区生产总值/万元 ＜7.0 7.0~8.7 8.7~11.6 11.6~15.0 ＞15.0 第二、三产业占地区生产总值比例 ＜0.85 0.85~0.87 0.87~0.91 0.91~0.95 ＞0.95 恩格尔系数 ＞0.50 0.44~0.50 0.33~0.44 0.20~0.33 0~0.20 间接经济效益 第二、三产业就业人数/万人 ＜20.0 20.0~41.4 41.4~77.0 77.0~120.0 ＞120.0 收入分配系数 ＜0.80 0.80~0.86 0.86~0.97 0.97~1.10 ＞1.10
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表 3 不同等级云模型数字特征
Table 3. Digital characteristics of different levels of cloud models
指标 适度超前 总体适应 初步适应 相对滞后 严重制约 节点可达性系数 (0.200, 0.170, 0.030) (0.500, 0.090, 0.020) (0.800, 0.170, 0.020) (1.300, 0.260, 0.030) (1.800, 0.170, 0.030) 道路拥挤度 (0.150, 0.100, 0.020) (0.400, 0.090, 0.030) (0.600, 0.090, 0.030) (0.800, 0.090, 0.020) (1.100, 0.120, 0.030) 日均客运密度/(万人·km·km-1) (1.600, 0.140, 0.030) (1.300, 0.090, 0.030) (1.100, 0.130, 0.040) (0.750, 0.130, 0.030) (0.460, 0.120, 0.030) 日均货运密度/(104 t·km·km-1) (3.400, 1.450, 0.030) (2.900, 0.210, 0.040) (2.300, 0.380, 0.050) (1.300, 0.420, 0.040) (0.450, 0.300, 0.050) 人均地区生产总值/万元 (5.600, 1.210, 0.090) (7.800, 0.730, 0.090) (10.200, 2.900, 0.090) (13.300, 1.500, 0.090) (16.000, 0.970, 0.080) 第二、三产业地区生产总值占比 (0.840, 0.006, 0.002) (0.860, 0.009, 0.003) (0.890, 0.017, 0.002) (0.930, 0.017, 0.003) (0.970, 0.015, 0.004) 恩格尔系数 (0.600, 0.040, 0.010) (0.500, 0.030, 0.010) (0.400, 0.050, 0.010) (0.300, 0.050, 0.010) (0.100, 0.090, 0.010) 第二、三产业就业人数/万人 (12.430, 6.430, 0.080 (30.720, 9.090, 0.070) (59.220, 15.100, 0.080) (98.500, 18.260, 0.080) (123.450, 2.930, 0.100) 收入分配系数 (0.779, 0.018, 0.006) (0.830, 0.025, 0.007) (0.920, 0.047, 0.008) (1.040, 0.055, 0.008) (1.145, 0.083, 0.008)
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表 4 组合云模型与DEA模型对比
Table 4. Comparation between combined empowerment cloud model and DEA model
% 模型 适度超前 总体适应 初步适应 相对滞后 严重制约 组合云模型 6.52 21.74 43.48 21.74 6.52 DEA模型 23.91 36.96 0.00 39.13 0.00
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