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Probabilistic flows of inhabitants in urban areas and self-organization in housing markets

机译:城市居民的概率流动与住房市场的自我组织

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We propose a very simple probabilistic model to explain the spatial structure of the rent distribution of housing market in city of Sapporo. Here we modify the mathematical model proposed by Gauvin et. al. [1]. In their mathematical modeling, they utilized several assumptions to describe the decision making of each inhabitant in Paris. Namely, they assumed that the intrinsic attractiveness of a city depends on the location and there exists a single peak at the center. They also used the assumption that each inhabitant tends to choose the place where the other inhabitants having the similar or superior income to himself/herself are living. In order to find the best possible (desirable) place to live, each buyer in the system moves from one place to the other according to the transition (aggregation) probability described by the above two assumption, and he/she makes a deal with the seller who presents the best possible condition for the buyer. They concluded that the resultant self-organized rent distribution is consistent with the corresponding empirical evidence in Paris. However, it is hard for us to apply their model directly to the other cities having plural centers (not only a single center as in Paris). Hence, here we shall modify the Gauvin's model to include the much more detail structure of the attractiveness by taking into account the empirical data concerning the housing situation in city of Sapporo. We also consider the competition between two distances, namely, the distance between house and center, and the distance between house and office. Computer simulations are carried out to reveal the self-organized spatial structure appearing in the rent distribution. We also compare the resulting distribution with empirical rent distribution in Sapporo as an example of cities designated by ordinance.
机译:我们提出了一个非常简单的概率模型来解释札幌市住房市场租金分布的空间结构。在这里,我们修改了Gauvin等人提出的数学模型。 al。 [1]。在数学建模中,他们利用了几种假设来描述巴黎每个居民的决策。即,他们假设城市的内在吸引力取决于位置,并且在中心只有一个高峰。他们还假设每个居民都倾向于选择其他收入与自己相似或较高的居民居住的地方。为了找到可能的最佳(理想)居住地,系统中的每个买方都根据上述两个假设所描述的过渡(集合)概率从一个地方移动到另一个地方,然后他/她与为买方提供最佳条件的卖方。他们得出的结论是,由此产生的自组织租金分配与巴黎相应的经验证据相一致。但是,我们很难将其模型直接应用于其他具有多个中心的城市(不仅像巴黎那样只有一个中心)。因此,在这里,我们将通过考虑有关札幌市住房状况的经验数据,修改高文模型,以包括吸引力的更多详细结构。我们还考虑了两个距离之间的竞争,即房屋与中心之间的距离以及房屋与办公室之间的距离。进行计算机模拟以揭示租金分布中出现的自组织空间结构。我们还将结果分配与札幌的经验租金分配进行了比较,以该条例指定的城市为例。

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