绿地商务中心办公用房出租价格预测数据

办公用房的出租价格是有众多不同的特征组成。由于各个特征的数量和组合方式不同，使的办公用房的出租价格产生差异。如能将办公用房的出租价格影响因素分解，求出各影响因素所隐含的价格，在特征数量固定不变时，就能将办公用房的出租价格变动的品质因素拆离，以反映纯粹价格的变化。通过特征价格法可以预测绿地商务中心办公用房的出租价格。此计算方法并为办公出租房行业内出租价格预测提供数据支持。算法规则简介：
1、采集于历年企业办公用房的出租数据，经过降噪、清洗后建立模型。
2、将处理后的数据通过加权平均法：每平方日租金价格预测（元）=0.8*成本+0.05*楼层+0.05*朝向+0.1*装修，计算得出每平方日租金价格的预测值。楼层：总楼层的下1/3和上1/3收取10元；中间1/3层收取20元. 朝向：东4元、南4.6元、西3.8元、北3元. 装修：简装：0.8元，豪华1.2元

The rental prices of office spaces are determined by a wide range of distinct characteristics. Variations in the quantity and combination of these characteristics give rise to differences in office rental prices. If the influencing factors of office space rental prices can be decomposed and the implicit prices of each factor can be derived, when the number of characteristics remains fixed, the quality factors driving changes in office rental prices can be isolated to reflect changes in pure prices. The hedonic pricing method can be applied to predict the rental prices of office spaces in Lvdi Business Center, and this calculation method can also provide data support for rental price forecasting within the office rental industry. Brief introduction of the algorithm rules: 1. Rental data of corporate office spaces collected over multiple years are used to establish a model after noise reduction and data cleaning. 2. The processed data are used to calculate the predicted daily rental price per square meter (in RMB) via the weighted average method: Predicted daily rental price per square meter = 0.8 * cost + 0.05 * floor + 0.05 * orientation + 0.1 * decoration. Specific parameter settings are as follows: - Floor: A premium of 10 RMB is applied to the lower 1/3 and upper 1/3 of the total number of floors, while a premium of 20 RMB is applied to the middle 1/3 of the floors. - Orientation: A premium of 4 RMB for east-facing, 4.6 RMB for south-facing, 3.8 RMB for west-facing, and 3 RMB for north-facing. - Decoration: A premium of 0.8 RMB for lightly decorated offices, and 1.2 RMB for luxuriously decorated offices.