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       随着经济发达，采光开始成为体现人们日常生活品质中的一项主要技术指标，光照的强弱、采光范围的多少极大的影响着我们的生活。在当代，楼房的内部通风、采光和日照等问题已经成为了社会上越来越关心的课题之一。城市用地价值的增加、高楼大厦的增多，这些改变导致与采光和日照相关方面的问题也越来越多。因此，房屋市场价值贬值也成为了衡量采光权侵权补偿金额的一大重要依据。

       从相关文献中了解到，在我国现有的实践中，对于受采光权影响导致房屋贬值的测算还不够成熟。一方面缺少相关的具体条例来规定如何准确计算赔偿 金额，另一方面由于个人因素导致的赔偿金额往往带有主观色彩。在现行测算方法中，成本法对房屋由于受到采光影响导致多增加的费用进行计算从而确定赔偿金额，但这种方法会少算部分金额；而收益法测算中获得的收益难以测量。 基于以上背景，在学者研究的基础上，通过阅读大量文献，本文运用市场法来进行住宅贬值测算，在测算中，以丁香园小区采光被挡房屋为例，其中可比实例的选取与相关因素权重的测量利用机器学习中的模糊综合评判法与层次分析法来确定，进而获得适合的可比案例，计算住宅价值贬值金额。研究结果表明，（1）在对比了市场法、收益法、成本法之后，对于采光权造成的房屋贬值测算，采用改进后的市场法来计算是可行的。这一方法可为我国对于采光权缺失造成的赔偿纠纷提供新思路。（2）模糊数学法解决了对模糊变量的测算，通过模糊数学理论与层次分析的理论，确定了影响房屋采光的各因素权重，采用这种模型分析可以解决了市场法中可比案例的因素修正这一难题，采光受影响的房屋经过各因素的调整，得出的房屋价格低于正常房屋价格范围是合理的。

With the development of economy, daylighting has become a main technical index reflecting the quality of people's daily life. The intensity of light and the range of daylighting have a great impact on our life. In contemporary times, the internal ventilation, daylighting and sunshine of buildings have become one of the topics of increasing concern in the society. With the increase of urban land value and the increase of high-rise buildings, these changes lead to more and more problems related to daylighting and sunshine. Therefore, the depreciation of housing market value has also become an important basis to measure the amount of compensation for daylighting infringement.

According to the relevant literature, in China's existing practice, the calculation of house depreciation caused by the influence of daylighting right is not mature enough. On the one hand, there is a lack of relevant specific regulations to specify how to accurately calculate the amount of compensation. On the other hand, the amount of compensation caused by personal factors is often subjective. In the current calculation method, the cost method calculates the increased expenses of the house due to the influence of daylighting, so as to determine the amount of compensation, but this method will calculate part of the amount less； The income obtained in the income method is difficult to measure. Based on the above background, on the basis of scholars' research and reading a large number of documents, this paper uses the market method to calculate the housing depreciation. In the calculation, taking the daylighting blocked houses in dingxiangyuan community as an example, the selection of comparable examples and the measurement of the weight of relevant factors are determined by the fuzzy comprehensive evaluation method and analytic hierarchy process in machine learning, Then obtain suitable comparable cases and further calculate the depreciation amount of housing value. The results show that： （1） after comparing the market method, income method and cost method, it is feasible to use the improved market method to calculate the house depreciation caused by daylighting right. This method can provide new ideas for the compensation disputes caused by the lack of daylighting right in our country. （2） The fuzzy mathematics method solves the calculation of fuzzy variables. Through the theory of fuzzy mathematics and analytic hierarchy process, the weight of various factors affecting house daylighting is determined. This model analysis can solve the problem of factor correction of comparable cases in the market method. The houses affected by daylighting are adjusted by various factors, It is reasonable that the obtained house price is lower than the normal house price range.