利索-全球专利检索

  1. 登录
  2. 注册

搜索结果

58 条记录 (耗时 0.03 秒)

    PROGRAMMABLE TICKETING SYSTEM
    23.
    发明申请
    PROGRAMMABLE TICKETING SYSTEM 有权
    可程式制作系统

    公开(公告)号：US20100320268A1

    公开(公告)日：2010-12-23

    申请号：US12825183

    申请日：2010-06-28

    申请人： Tyler Brooks ,  Kevin McLaughlin ,  Helga Cecilia Dahl ,  Edward Kim

    发明人： Tyler Brooks ,  Kevin McLaughlin ,  Helga Cecilia Dahl ,  Edward Kim

    IPC分类号： G06K5/00

    CPC分类号： G06Q30/00 ,  G06Q30/0601 ,  G07C9/00007 ,  G07C11/00 ,  G07C2011/02 ,  G07C2011/04

    摘要： A smart-card based system and methods to control access to a plurality of attractions within a geographical area. The system may include one or more reward terminals that are located at attractions and are configured to read smart cards presented to them and, assuming the card is valid for that location, allow the card holder to access the attraction. Each smart card may be programmed with a product code that defines the attractions at which the card may be used. Product codes may be stored in a central database along with a list of the attractions associated with the each product code. The list of attractions may be updated as desired, thereby updating and changing the attractions at which any given card may be used.

    摘要翻译： 一种基于智能卡的系统和方法来控制对地理区域内的多个景点的访问。 该系统可以包括位于景点的一个或多个奖励终端，并被配置为读取呈现给他们的智能卡，并且假定该卡对于该位置有效，允许该卡座访问该吸引力。 每个智能卡可以用定义可以使用卡的吸引力的产品代码进行编程。 产品代码可以与每个产品代码相关联的景点列表一起存储在中央数据库中。 可以根据需要更新景点列表，从而更新和改变可以使用任何给定的卡的景点。

    Navigation configuration for a motor vehicle, motor vehicle having a navigation system, and method for determining a route
    24.
    发明申请
    Navigation configuration for a motor vehicle, motor vehicle having a navigation system, and method for determining a route 审中-公开
    用于机动车辆的导航配置，具有导航系统的机动车辆，以及用于确定路线的方法

    公开(公告)号：US20090271106A1

    公开(公告)日：2009-10-29

    申请号：US12108264

    申请日：2008-04-23

    申请人： Rohit Mishra ,  Edward Kim ,  Zhaoxia Zhang ,  Arati Gerdes

    发明人： Rohit Mishra ,  Edward Kim ,  Zhaoxia Zhang ,  Arati Gerdes

    IPC分类号： G01C21/34 ,  G06F17/30

    CPC分类号： G01C21/3608

    摘要： A navigation configuration includes a microphone, disposed in a motor vehicle, for acoustically inputting a location designation. A server, disposed outside the motor vehicle, performs a speech recognition of an acoustically input location designation and converts the acoustically input location designation into a location designation of a database. A communication system transmits the acoustically input location designation from the motor vehicle to the server and transmits the location designation of the database from the server to the motor vehicle. A navigation system, disposed in the motor vehicle, determines a route from a location of the motor vehicle to a destination as a function of the location designation of the database. A motor vehicle having a navigation system for determining a route and a method for determining a route from a location of the motor vehicle to a destination are also provided.

    摘要翻译： 导航配置包括设置在机动车辆中的用于声学地输入位置指定的麦克风。 设置在机动车辆外部的服务器执行声输入位置指定的语音识别，并将声输入位置指定转换为数据库的位置指定。 通信系统将声学输入的位置指定从机动车辆发送到服务器，并将数据库的位置指定从服务器发送到机动车辆。 设置在机动车辆中的导航系统根据数据库的位置指定确定从机动车辆的位置到目的地的路线。 还提供了具有用于确定路线的导航系统和用于确定从机动车辆的位置到目的地的路线的方法的机动车辆。

    METHOD AND SYSTEM FOR FORECASTING FUTURE ORDER REQUIREMENTS
    25.
    发明申请
    METHOD AND SYSTEM FOR FORECASTING FUTURE ORDER REQUIREMENTS 审中-公开
    预测未来订单要求的方法和系统

    公开(公告)号：US20080162270A1

    公开(公告)日：2008-07-03

    申请号：US11951364

    申请日：2007-12-06

    申请人： Edward Kim ,  Jean-Philippe Vorsanger ,  Zhenrong Michael Li ,  Ejaz Haider

    发明人： Edward Kim ,  Jean-Philippe Vorsanger ,  Zhenrong Michael Li ,  Ejaz Haider

    IPC分类号： G06Q10/00

    CPC分类号： G06Q10/087 ,  G06Q30/0202

    摘要： A method and system for forecasting distribution center (DC) or warehouse product suggested order quantities required to meet future product demands for a retailer. In determining DC/warehouse order quantities, a bias factor and Adaptive Forecast Error (AFE) are calculated from prior product demand and sales data and applied to DC/warehouse effective inventory calculations to account for forecast errors in DC/warehouse suggested order quantities. If the bias indicates a forecast that is too high, the method and system will attempt to compensate by increasing the suggested order quantity. If the bias indicates a forecast that is too low, the method and system will attempt to compensate by decreasing the suggested order quantity.

    摘要翻译： 用于预测配送中心（DC）或仓库产品的方法和系统，建议满足零售商未来产品需求所需的订单数量。 在确定DC /仓库订单数量时，根据先前的产品需求和销售数据计算偏差因子和自适应预测误差（AFE），并应用于DC /仓库有效库存计算，以解决DC /仓库建议订单数量中的预测误差。 如果偏差指示太高的预测，则方法和系统将尝试通过增加建议的订单数量进行补偿。 如果偏差表示太低的预测，则方法和系统将通过减少建议的订单数量来尝试进行补偿。

    Method for determining daily weighting factors for use in forecasting daily product sales
    26.
    发明授权
    Method for determining daily weighting factors for use in forecasting daily product sales 有权
    确定用于预测日常产品销售的日常加权因子的方法

    公开(公告)号：US08560374B2

    公开(公告)日：2013-10-15

    申请号：US12326145

    申请日：2008-12-02

    申请人： Arash Bateni ,  Edward Kim

    发明人： Arash Bateni ,  Edward Kim

    IPC分类号： G06Q30/02

    CPC分类号： G06Q30/02 ,  G06Q10/04 ,  G06Q30/0202

    摘要： A product demand forecasting methodology is presented that applies daily weight values to a weekly forecast to determine daily forecasts for a product or service. The method determines daily weight values for use in forecasting current product sales by blending daily weight values calculated from historical demand data for both recent weeks and year-prior weeks. Recent weeks are used to account for recent correlations and alternation effects, and year-prior weeks are used to account for seasonality effects. The method automatically calculates a measure of significance for the daily weights calculated from the recent weeks and year-prior weeks. The significance of each week is applied as a weighting factor during the blending of recent weeks and year-prior daily weight values.

    摘要翻译： 提出了一种产品需求预测方法，将每日重量值应用于每周预测，以确定产品或服务的每日预测。 该方法通过混合最近几周和前一周的历史需求数据计算的每日重量值，确定用于预测当前产品销售的每日重量值。 最近几周用于说明最近的相关性和交替效应，并且前一周用于考虑季节效应。 该方法自动计算从最近几周和前一周计算的每日重量的重要度量度。 在最近几周和前一天每日体重值的混合期间，每周的意义被用作加权因子。

    Programmable ticketing system
    27.
    发明授权
    Programmable ticketing system 有权
    可编程票务系统

    公开(公告)号：US08346618B2

    公开(公告)日：2013-01-01

    申请号：US12825183

    申请日：2010-06-28

    申请人： Tyler Brooks ,  Kevin McLaughlin ,  Helga Cecilia Dahl ,  Edward Kim

    发明人： Tyler Brooks ,  Kevin McLaughlin ,  Helga Cecilia Dahl ,  Edward Kim

    IPC分类号： G06Q30/00 ,  G06F17/30

    CPC分类号： G06Q30/00 ,  G06Q30/0601 ,  G07C9/00007 ,  G07C11/00 ,  G07C2011/02 ,  G07C2011/04

    摘要： A smart-card based system and methods to control access to a plurality of attractions within a geographical area. The system may include one or more reward terminals that are located at attractions and are configured to read smart cards presented to them and, assuming the card is valid for that location, allow the card holder to access the attraction. Each smart card may be programmed with a product code that defines the attractions at which the card may be used. Product codes may be stored in a central database along with a list of the attractions associated with the each product code. The list of attractions may be updated as desired, thereby updating and changing the attractions at which any given card may be used.

    摘要翻译： 一种基于智能卡的系统和方法来控制对地理区域内的多个景点的访问。 该系统可以包括位于景点的一个或多个奖励终端，并被配置为读取呈现给他们的智能卡，并且假定该卡对于该位置有效，允许该卡座访问该吸引力。 每个智能卡可以用定义可以使用卡的吸引力的产品代码进行编程。 产品代码可以与每个产品代码相关联的景点列表一起存储在中央数据库中。 可以根据需要更新景点列表，从而更新和改变可以使用任何给定的卡的景点。

    Techniques for multi-variable analysis at an aggregate level
    28.
    发明授权
    Techniques for multi-variable analysis at an aggregate level 有权
    综合水平多变量分析技术

    公开(公告)号：US08290913B2

    公开(公告)日：2012-10-16

    申请号：US11967673

    申请日：2007-12-31

    申请人： Arash Bateni ,  Edward Kim

    发明人： Arash Bateni ,  Edward Kim

    IPC分类号： G06F7/00

    CPC分类号： G06F17/30412

    摘要： Techniques for multi-variable analysis at an aggregate level are provided. Two or more datasets having different statistical data distributions and which are not capable of being aggregated are acquired. The values for variables in the two or more datasets are normalized to produce a single integrated dataset of normalized values. The normalized values are then used to produce a demand model that represents and integrates multiple disparate products or services from the two or more datasets into a single demand model.

    摘要翻译： 提供了一个综合水平的多变量分析技术。 获取具有不同统计数据分布且不能聚合的两个或多个数据集。 两个或更多数据集中变量的值被归一化以产生一个归一化值的集成数据集。 归一化值然后用于产生一个需求模型，它将来自两个或多个数据集的多个不同的产品或服务整合到一个需求模型中。

    DETERMINATION OF DEMAND UPLIFT VALUES FOR CAUSAL FACTORS WITH SEASONAL PATTERNS IN A CAUSAL PRODUCT DEMAND FORECASTING SYSTEM
    29.
    发明申请
    DETERMINATION OF DEMAND UPLIFT VALUES FOR CAUSAL FACTORS WITH SEASONAL PATTERNS IN A CAUSAL PRODUCT DEMAND FORECASTING SYSTEM 审中-公开
    确定原产地需求预测系统中季节性因素的原因因素的需求上限值

    公开(公告)号：US20110153385A1

    公开(公告)日：2011-06-23

    申请号：US12643079

    申请日：2009-12-21

    申请人： Arash Bateni ,  Edward Kim

    发明人： Arash Bateni ,  Edward Kim

    IPC分类号： G06Q10/00

    CPC分类号： G06Q10/04 ,  G06Q30/0202

    摘要： An improved method and system for forecasting product demand using a causal methodology, based on multiple regression techniques. The causal method uses both historical and future values of causal factors for causal forecasting. Historical values are used to build a causal model, i.e., to determine the influence of the causal factors upon the demand for a product, and future values are used to generate demand uplifts which applied to an initial demand forecast based upon historical product demand. The improved causal method provides different processes for the calculation of demand uplifts associated with seasonal variables, such as temperature, than typical, non-seasonal causal variables, such as product price. Demand uplifts for seasonal variables are determined from the difference between a forecast value for the seasonal variable and an average of corresponding historical, prior-year, values of the seasonal variable, and demand uplifts for non-seasonal variables are determined from the difference between a forecast value for the non-seasonal variable and an average of recent values of the non-seasonal variable.

    摘要翻译： 基于多元回归技术，使用因果方法预测产品需求的改进方法和系统。 因果方法使用因果预测的因果因素的历史和未来价值。 历史价值被用于构建因果模型，即确定因果因素对产品需求的影响，未来价值被用于产生应用于基于历史产品需求的初始需求预测的需求提升。 改进的因果方法提供了与诸如产品价格的典型非季节性因素变量等季节变量（如温度）相关的需求升幅的计算的不同过程。 季节变量的需求升幅是根据季节变量的预测值与季节变量的相应历史和上一年值的平均值之间的差异确定的，非季节变量的需求上升是根据 非季节变量的预测值和非季节变量的近期值的平均值。