公开(公告)号：US09519912B2

公开(公告)日：2016-12-13

申请号：US14032476

申请日：2013-09-20

Applicant: Xerox Corporation

Inventor： Boris Chidlovskii ,  Mohammad Ghufran

IPC: G06F15/18 ,  G06Q30/02 ,  G06N99/00 ,  G06Q10/06

CPC classification number: G06Q30/0202 ,  G06N99/005 ,  G06Q10/0631

Abstract: In demand prediction, a history of demand for a resource is modeled to generate a baseline model of the demand, and demand for the resource at a prediction time is predicted by evaluating a regression function of depth k operating on an input data set including at least the demand for the resource at the prediction time output by the baseline model and measured demand for the resource measured at k times prior to the prediction time. The resource may be off-street parking, and the input data set may further include weather data. The regression function may comprise a support vector regression (SVR) function that is trained on the history of demand for the resource. The baseline model suitably comprises a Fourier model of the history of demand for the resource.

Abstract translation: 在需求预测中，对资源的需求历史进行建模以生成需求的基准模型，并且通过评估在包括至少包括在内的输入数据集上操作的深度k的回归函数来预测在预测时间对资源的需求 在基准模型输出的预测时间内对资源的需求和在预测时间之前k次测量的资源的测量需求。 资源可以是路边停车场，并且输入数据集还可以包括天气数据。 回归函数可以包括对资源的需求历史训练的支持向量回归（SVR）函数。 基线模型适当地包括资源需求历史的傅里叶模型。

公开(公告)号：US20150088790A1

公开(公告)日：2015-03-26

申请号：US14032476

申请日：2013-09-20

Applicant: Xerox Corporation

Inventor： Boris Chidlovskii ,  Mohammad Ghufran

IPC: G06Q30/02 ,  G06N99/00

CPC classification number: G06Q30/0202 ,  G06N99/005 ,  G06Q10/0631

Abstract: In demand prediction, a history of demand for a resource is modeled to generate a baseline model of the demand, and demand for the resource at a prediction time is predicted by evaluating a regression function of depth k operating on an input data set including at least the demand for the resource at the prediction time output by the baseline model and measured demand for the resource measured at k times prior to the prediction time. The resource may be off-street parking, and the input data set may further include weather data. The regression function may comprise a support vector regression (SVR) function that is trained on the history of demand for the resource. The baseline model suitably comprises a Fourier model of the history of demand for the resource.

Abstract translation: 在需求预测中，对资源的需求历史进行建模以生成需求的基准模型，并且通过评估在包括至少包括在内的输入数据集上操作的深度k的回归函数来预测在预测时间对资源的需求 在基准模型输出的预测时间内对资源的需求和在预测时间之前k次测量的资源的测量需求。 资源可以是路边停车场，并且输入数据集还可以包括天气数据。 回归函数可以包括对资源的需求历史训练的支持向量回归（SVR）函数。 基线模型适当地包括资源需求历史的傅里叶模型。