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A two-stage recreational destination choice study incorporating fuzzy logic in discrete choice modelling

机译:在离散选择建模中纳入模糊逻辑的两阶段休闲目的地选择研究

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A major challenge in developing discrete choice models when the feasible choice set is extensively large is to find an appropriate choice set that is computationally manageable for being integrated into the choice modelling specification while it also reflects the behaviour of the decision-maker. This study aims to develop a new sampling method for choice set formation which is then used to improve the knowledge about recreational destination choice behaviour. The study proposes a two-stage framework where in the first stage a rule-based fuzzy logic model is used to form a latent choice set. The second stage incorporates the set in a discrete choice model to estimate destination selection behaviour. In the travel demand modelling literature, there has been little research into modelling recreational activity destination choices. In this area, the primary focus has been on other activities, such as work, study and shopping. In this context, the sampling methods used to form the choice set using the large set of possible options in the universal set are unconvincing. The proposed two-stage approach is examined using a household travel survey from Victoria, Australia, where nine different recreational destination choice models are developed. Compared to the conventional modelling framework, these models show impressive model fit and prediction potential. (C) 2019 Elsevier Ltd. All rights reserved.
机译:当可行的选择集非常大时,开发离散选择模型的主要挑战是找到一个合适的选择集,该选择集在计算上可管理以集成到选择建模规范中,同时还反映了决策者的行为。这项研究的目的是为选择集的形成开发一种新的抽样方法,然后将其用于增进有关休闲目的地选择行为的知识。这项研究提出了一个两阶段的框架,在第一阶段,一个基于规则的模糊逻辑模型被用来形成一个潜在选择集。第二阶段将集合合并到离散选择模型中,以估计目标选择行为。在旅行需求建模文献中,很少有关于对娱乐活动目的地选择进行建模的研究。在这方面,主要重点是其他活动,例如工作,学习和购物。在这种情况下,使用通用集中的大量可能选项形成选择集的抽样方法令人信服。拟议的两阶段方法是使用澳大利亚维多利亚州的一项家庭旅行调查进行研究的,在那里开发了九种不同的娱乐目的地选择模型。与常规建模框架相比,这些模型显示出令人印象深刻的模型拟合和预测潜力。 (C)2019 Elsevier Ltd.保留所有权利。

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