REPEATABILITY INDEX TO ENHANCE SEASONAL PRODUCT FORECASTING
    1.
    发明申请
    REPEATABILITY INDEX TO ENHANCE SEASONAL PRODUCT FORECASTING 审中-公开
    可再生能源指标,以加强季节性产品预测

    公开(公告)号:US20100138273A1

    公开(公告)日:2010-06-03

    申请号:US12325414

    申请日:2008-12-01

    IPC分类号: G06Q10/00

    CPC分类号: G06Q30/02 G06Q30/0202

    摘要: A repeatability score is described for determining the quality and reliability of product sales data for generating seasonal demand forecasts. The repeatability scores are calculated from seasonal sales data stored in a data warehouse. Products are sorted based on their reliability scores such that those products that are highly seasonal and have a reliable year-to-year demand pattern are used to form initial or unique demand models. Products that are determined to be less reliable based on their repeatability score are added to the unique demand models through an iterative matching process or left out of the unique demand models.

    摘要翻译: 描述了重复性评分,用于确定用于产生季节性需求预测的产品销售数据的质量和可靠性。 重复性得分是从存储在数据仓库中的季节性销售数据计算的。 产品根据其可靠性分数进行排序,使得那些高度季节性且具有可靠的年度需求模式的产品被用于形成初始或独特的需求模型。 基于其可重复性评分被确定为不太可靠的产品通过迭代匹配过程被添加到独特需求模型中,或者不包括在独特需求模型中。

    METHODS AND SYSTEMS FOR RANDOMIZING STARTING RETAIL STORE INVENTORY WHEN DETERMINING DISTRIBUTION CENTER AND WAREHOUSE DEMAND FORECASTS
    2.
    发明申请
    METHODS AND SYSTEMS FOR RANDOMIZING STARTING RETAIL STORE INVENTORY WHEN DETERMINING DISTRIBUTION CENTER AND WAREHOUSE DEMAND FORECASTS 审中-公开
    在确定分销中心和仓库需求预测时,随机开始零售店库存的方法和系统

    公开(公告)号:US20110054982A1

    公开(公告)日:2011-03-03

    申请号:US12644063

    申请日:2009-12-22

    IPC分类号: G06Q10/00

    摘要: A method and system for determining distribution center or warehouse product order quantities of a slow selling product. The method includes the step of determining for each one of a plurality of stores supplied by the distribution center, a store order forecast for the slow selling product. The method generates a random beginning on-hand inventory value for stores with inventories below a minimum inventory threshold value. Store order forecasts are thereafter determined by subtracting the random beginning on-hand inventory value from store sales forecasts when the beginning on-hand inventory value is less than the minimum inventory threshold value, and subtracting the actual beginning on-hand inventory value from the store sales forecasts when the beginning on-hand inventory value is not less than the minimum inventory threshold value. The individual store order forecasts are accumulated to generate a distribution center demand forecast; which is compared with current and projected inventory levels for the product at the distribution center to determine distribution center order quantities necessary for maintaining a product inventory level sufficient to meet the distribution center demand forecast for the product.

    摘要翻译: 一种用于确定慢销产品的配送中心或仓库产品订单数量的方法和系统。 该方法包括确定由分配中心提供的多个商店中的每一个的步骤,用于慢销产品的商店订单预测。 该方法为存货低于最低库存阈值的商店生成随机库存现货库存值。 商店订单预测此后通过从开始现有库存值小于最小库存门槛值减去商店销售预测中的随机开始现有库存值,并从商店中减去实际库存现有价值 销售预测当开始现有库存值不低于最小库存阈值时。 累积个别店铺订单预测以产生配送中心需求预测; 将其与配送中心的产品的当前和预计库存水平进行比较,以确定维持产品库存水平足以满足产品配送中心需求预测所需的配送中心订单数量。

    METHODS AND SYSTEMS FOR FORECASTING PRODUCT DEMAND DURING PROMOTIONAL EVENTS USING A CAUSAL METHODOLOGY
    4.
    发明申请
    METHODS AND SYSTEMS FOR FORECASTING PRODUCT DEMAND DURING PROMOTIONAL EVENTS USING A CAUSAL METHODOLOGY 有权
    使用原理方法在促销活动中预测产品需求的方法和系统

    公开(公告)号:US20090125375A1

    公开(公告)日:2009-05-14

    申请号:US11938812

    申请日:2007-11-13

    IPC分类号: G06Q10/00 G06F17/11

    摘要: An improved method for forecasting and modeling product demand for a product during promotional periods. The forecasting methodology employs a multivariable regression model to model the causal relationship between product demand and the attributes of past promotional activities. The model is utilized to calculate the promotional uplift from the coefficients of the regression equation. The methodology utilizes a mathematical formulation that transforms regression coefficients, a combination of additive and multiplicative coefficients, into a single promotional uplift coefficient that can be used directly in promotional demand forecasting calculations.

    摘要翻译: 一种在促销期间预测和建模产品需求的改进方法。 预测方法采用多变量回归模型来模拟产品需求与过去促销活动的属性之间的因果关系。 该模型用于从回归方程的系数计算促销隆起。 该方法利用将回归系数(加法和乘法系数的组合)转换成可以在促销需求预测计算中直接使用的单个促销隆起系数的数学公式。

    METHODS AND SYSTEMS FOR PARTITIONING OF DATASETS FOR RETAIL SALES AND DEMAND CHAIN MANAGEMENT ANALYSIS
    5.
    发明申请
    METHODS AND SYSTEMS FOR PARTITIONING OF DATASETS FOR RETAIL SALES AND DEMAND CHAIN MANAGEMENT ANALYSIS 有权
    用于零售销售和需求链管理分析的数据分类方法与系统

    公开(公告)号:US20090012979A1

    公开(公告)日:2009-01-08

    申请号:US11772343

    申请日:2007-07-02

    IPC分类号: G06F19/00

    CPC分类号: G06Q30/02 Y10S707/972

    摘要: A partitioning system that provides a fast, simple and flexible method for partitioning a dataset. The process, executed within a computer system, retrieves product and sales data from a data store. Data items are selected and sorted by a data attribute of interest to a user and a distribution curve is determined for the selected data and data attribute. The total length of the distribution curve is calculated, and then the curve is divided into k equal pieces, where k is the number of the partitions. The selected data is thereafter partitioned into k groups corresponding to the curve divisions.

    摘要翻译: 分区系统,提供快速,简单和灵活的分割数据集的方法。 在计算机系统内执行的过程从数据存储中检索产品和销售数据。 通过用户感兴趣的数据属性选择和排序数据项,并为所选择的数据和数据属性确定分布曲线。 计算分布曲线的总长度,然后将曲线划分为k个相等的部分,其中k是分区的数量。 然后将所选择的数据划分成与曲线分割对应的k个组。

    IMPROVED METHODS AND SYSTEMS FOR FORECASTING PRODUCT DEMAND USING PRICE ELASTICITY
    6.
    发明申请
    IMPROVED METHODS AND SYSTEMS FOR FORECASTING PRODUCT DEMAND USING PRICE ELASTICITY 审中-公开
    改进使用价格弹性预测产品需求的方法和系统

    公开(公告)号:US20080133313A1

    公开(公告)日:2008-06-05

    申请号:US11566357

    申请日:2006-12-04

    IPC分类号: G06Q10/00

    摘要: An improved method for forecasting and modeling product demand for a product. The forecasting methodology blends information about the future price of a product with historical sales data to better forecast the future product demand. This forecasting methodoloy takes into account three main parameters that may affect the future demand for a product: seasonality (using seasonal factors), recent sales trends (through average rate of sale analysis) and the product price (by estimating the price driven demand).

    摘要翻译: 一种改进的产品需求预测和建模方法。 预测方法将有关产品未来价格的信息与历史销售数据相结合,以更好地预测未来的产品需求。 这种预测方法考虑了可能影响产品未来需求的三个主要参数:季节性(使用季节性因素),最近的销售趋势(通过平均销售率分析)和产品价格(通过估算价格驱动的需求)。

    Methods and systems for forecasting product demand during promotional events using statistical confidence filters
    7.
    发明授权
    Methods and systems for forecasting product demand during promotional events using statistical confidence filters 有权
    使用统计置信滤波器在促销活动期间预测产品需求的方法和系统

    公开(公告)号:US08359229B2

    公开(公告)日:2013-01-22

    申请号:US11863958

    申请日:2007-09-28

    IPC分类号: G06Q40/00

    摘要: An improved method for forecasting and modeling product demand for a product during promotional periods. The forecasting methodology employs information about prior promotional demand forecasts, prior product sales, and the data dispersion and the number of data samples in a product class hierarchy to dynamically determine the optimal level at which to compute promotional uplift coefficients. The methodology calculates confidence values for promotional uplift coefficients for products at each level in a merchandise product hierarchy, and uses the confidence values as a filter to determine the optimal level for promotional uplift aggregation.

    摘要翻译: 一种在促销期间预测和建模产品需求的改进方法。 预测方法采用关于先前的促销需求预测,先前的产品销售以及产品类层次结构中的数据分散和数据样本的数量的信息来动态地确定计算促销隆起系数的最佳级别。 该方法计算商品产品层级中每个级别的产品的促销提升系数的置信度值,并使用置信度值作为过滤器来确定促销隆起聚合的最佳级别。

    Methods and systems for forecasting product demand during promotional events using a causal methodology
    8.
    发明授权
    Methods and systems for forecasting product demand during promotional events using a causal methodology 有权
    使用因果方法在促销活动期间预测产品需求的方法和系统

    公开(公告)号:US07996254B2

    公开(公告)日:2011-08-09

    申请号:US11938812

    申请日:2007-11-13

    IPC分类号: G06Q99/00

    摘要: An improved method for forecasting and modeling product demand for a product during promotional periods. The forecasting methodology employs a multivariable regression model to model the causal relationship between product demand and the attributes of past promotional activities. The model is utilized to calculate the promotional uplift from the coefficients of the regression equation. The methodology utilizes a mathematical formulation that transforms regression coefficients, a combination of additive and multiplicative coefficients, into a single promotional uplift coefficient that can be used directly in promotional demand forecasting calculations.

    摘要翻译: 一种在促销期间预测和建模产品需求的改进方法。 预测方法采用多变量回归模型来模拟产品需求与过去促销活动的属性之间的因果关系。 该模型用于从回归方程的系数计算促销隆起。 该方法利用将回归系数(加法和乘法系数的组合)转换成可以在促销需求预测计算中直接使用的单个促销隆起系数的数学公式。

    SYSTEM AND METHOD FOR DE-SEASONALIZING PRODUCT DEMAND BASED ON MULTIPLE REGRESSION TECHNIQUES
    9.
    发明申请
    SYSTEM AND METHOD FOR DE-SEASONALIZING PRODUCT DEMAND BASED ON MULTIPLE REGRESSION TECHNIQUES 审中-公开
    基于多重回归技术去产品需求的系统和方法

    公开(公告)号:US20110153386A1

    公开(公告)日:2011-06-23

    申请号:US12644053

    申请日:2009-12-22

    IPC分类号: G06Q10/00 G06F17/30

    摘要: An improved method and system for forecasting product demand using a causal methodology, based on multiple regression techniques. The improved causal method revises product group seasonal factors used by conventional forecasting applications to best fit the sales pattern of an individual product in the product group through the calculation of an exponential coefficient which measures the deviation of the historical sales pattern of an individual product from the product group seasonal factors. The value of exponential coefficient is calculated using a causal framework through multivariable regression analysis.

    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。 改进的因果方法通过计算指标系数​​来衡量常规预测应用中使用的产品组季节性因素,以最佳地适应产品组中单个产品的销售模式,该指数系数衡量单个产品的历史销售模式与 产品组季节性因素。 指数系数的值通过多变量回归分析的因果框架计算。

    DATA QUALITY TESTS FOR USE IN A CAUSAL PRODUCT DEMAND FORECASTING SYSTEM
    10.
    发明申请
    DATA QUALITY TESTS FOR USE IN A CAUSAL PRODUCT DEMAND FORECASTING SYSTEM 审中-公开
    数据质量测试用于产品需求预测系统

    公开(公告)号:US20100169166A1

    公开(公告)日:2010-07-01

    申请号:US12649005

    申请日:2009-12-29

    IPC分类号: G06Q10/00 G06F17/30

    CPC分类号: G06Q30/02 G06Q30/0202

    摘要: An improved method for forecasting and modeling product demand for a product. The forecasting methodology employs a causal methodology, based on multiple regression techniques, to model the effects of various factors on product demand, and hence better forecast future patterns and trends, improving the efficiency and reliability of the inventory management systems. The improved method identifies linear dependent causal factors and removes redundant causal factors from the regression analysis. A product demand forecast is generated by blending forecast or expected values of the non-redundant causal factors together with corresponding regression coefficients determined through the analysis of historical product demand and factor information.

    摘要翻译: 一种改进的产品需求预测和建模方法。 预测方法采用基于多元回归技术的因果方法来模拟各种因素对产品需求的影响,从而更好地预测未来模式和趋势,提高库存管理系统的效率和可靠性。 改进的方法识别线性相关因素,并从回归分析中消除重要的因果因素。 产品需求预测是通过将非冗余因果因子的预测值或预期值与通过分析历史产品需求和因子信息确定的相应回归系数相结合而产生的。