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作 者:方铖 黄远春[1] 朱琳[1] FANG Cheng;HUANG Yuanchun;ZHU Lin(School of Urban Railway Transportation,Shanghai University of Engineering Science,201620,Shanghai,China)
机构地区:[1]上海工程技术大学城市轨道交通学院,上海201620
出 处:《城市轨道交通研究》2022年第12期138-142,147,共6页Urban Mass Transit
基 金:国家自然科学基金项目(71701124)。
摘 要:为全面直观了解轨道交通整体运营调度员的认知能力,减小认知能力评估过程中的模糊性和随机性,提出基于云模型和改进CRITIC权重法相结合的运营调度员认知能力评估模型。以随机抽取的202名运营调度员认知能力评估为例,基于运营调度员作业特征分析,选取13个反应认知能力指标作为云模型变量,结合改进的CRITIC权重法计算每个指标的云模型数字特征;通过对评价云模型和综合结果云模型分布的比较,得到所分析的运营调度员认知能力等级介于“正常”和“较强”之间,验证了模型的有效性和合理性。To understand the cognitive ability of the rail transit overall operation dispatcher comprehensively and intuitively,and to reduce the fuzziness and randomness in the process of cognitive ability evaluation,a cognitive ability evaluation model of operation dispatcher based on combination of cloud model and modified CRITIC weight method is proposed.Taking the cognitive ability evaluation cases of the randomly selected 202 operational dispatchers,based on the analysis of operational characteristics of dispatchers,13 response cognitive ability indicators are selected as cloud model variables.Then combined with the modified CRITIC weight method,the cloud model digital characteristics of each index are calculated.Through a comparison of the evaluation cloud model and the comprehensive result cloud model distribution,it is concluded that the cognitive ability level of the analyzed operation dispatchers is between′normal′and′strong′.It verifies the validity and rationality of the model.
分 类 号:U292.22[交通运输工程—交通运输规划与管理]
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