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Spatial distribution of urban trips in recently expanded Surat city through Fuzzy Logic with various clustering Techniques: A case study of typical metropolitan city in India

机译:基于模糊逻辑和多种聚类技术的最近苏拉特市城市旅行的空间分布:以印度典型的大都市为例

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Trip distribution finds prime place after trip generation in sequential modelling of travel demand to cover the spatial dimensions in a geographical area, to reflect on trip length and frequency. It provides the basis for strategic land use and transport infrastructure development both at local and regional levels. Trip distribution problems in the real world are quite complex with association of uncertainty in the decision making and therefore calls for an unorthodox approach to deal with the concerned issue. Soft computing technique - Fuzzy Logic (FL) is believed to be capable of addressing the uncertainty lying in the travellers’ behaviour and has been sought to develop realistic behavioural models in the recent years. FL takes into account linguistic variables and is based on simple and logical “IF-THEN” rules which closely resemble human thought process. Fuzzy Logic based trip distribution models are developed employing Fuzzy C-mean (FCM) clustering, and are compared for their performance with the Genfis based approach, where a Sugeno-type Fuzzy Inference System (FIS) is generated using Subtractive clustering. Surat, a fast growing metropolitan city in India is considered to realize the study. The models developed here, find applications in strategic land-use and transport planning for developing Indian cities.
机译:出行分布在出行需求的顺序建模中找到出行后的主要位置,以覆盖地理区域中的空间维度,以反映出出行的长度和频率。它为地方和区域层面的战略性土地利用和交通基础设施发展提供了基础。现实世界中的行程分布问题非常复杂,决策过程中存在不确定性,因此需要一种非常规的方法来处理相关问题。软计算技术-模糊逻辑(FL)被认为能够解决旅行者行为中的不确定性,并且近年来人们一直在寻求开发现实的行为模型。 FL考虑到语言变量,并基于与人类思维过程非常相似的简单逻辑“ IF-THEN”规则。基于模糊逻辑的行程分布模型是使用模糊C均值(FCM)聚类开发的,并且将其性能与基于Genfis的方法进行了比较,基于Genfis的方法使用减法聚类生成Sugeno型模糊推理系统(FIS)。苏拉特(Surat)是印度快速发展的都会城市,被认为可以实现这项研究。此处开发的模型可用于发展中印度城市的战略土地使用和运输规划中。

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