基于熵权TOPSIS模型的航道引航环境风险评价

Pilotage environment risk evaluation of waterways based on entropy weight and TOPSIS model

为对航道引航环境相对风险进行定量评价,建立了基于TOPSIS法的航道引航环境风险评价模型,并采用熵权法确定指标权重。选取长江江苏段4段航道作为实例,运用熵权TOPSIS模型,求得各评价对象的风险贴近度并进行排序,以此为依据评判各段航道引航环境风险,并与引航员主观评价结果进行比较,验证了模型的有效性。

The paper is intended to establish a model based on the entropy weight and TOPSIS in hoping to make a quantitative evaluation of the relative risk of different waterways＇ pilotage environment by taking the four waterways of the Yangtze River as a case study sample.To illustrate the application of the model to the high risks of navigation and pilotage faced by the river,first of all,we have taken into account the previous research outcomes and the specific circumstances of the waterway for the purpose by setting up an environment risk evaluation index table for pilotage.And,then,we have further established a risk assessment matrixin accordance with the evaluation index data of the 4 waterways of the River by standardizing the risk assessment matrix.As a step further,the weights of the risk assessment index can then be identified and determined with the entropy weight theory,with the weighted standard risk judgment matrix being set up.In so doing,we have worked out the distance between the target vector and the maximum risk value with the TOPSIS model,at the same time we have also obtained the distance between the target vector and the smallest risk value set by following the risk degree of each evaluation object.What is more,the relative risk of the evaluation objects can thus be determined by ranking the risk degrees of all the evaluation objects.Since it is impossible for the effectiveness of the model to be testified,the entropy weight and TOPSIS model can only be detected through comparison and the risk objects of the evaluation can only be ranked based on the objective data.Therefore,we have chosen forty pilots to evaluate the pilotage risk degrees about the four waterways of the River on the basis of their subjective judgments and feelings.The practicability of the model can thus be verified through comparison of the subjective inductions and the data calculated.