Likewise, each retail dealer is interested in acquiring vehicles from the manufacturer which can be quickly sold to customers.
解答例
Generally, manufacturers and their retail dealers spend considerable resources trying to forecast what types of vehicles and how many of each type of vehicle will be purchased by their customers.
Forecasting vehicle sales for a retail dealer is often a manually intensive and time consuming process.
In those instances where an automated dealer inventory management system has been implemented, the forecasting process for an individual dealer typically only focuses on that dealer's own vehicle sales.
As a result, the vehicle sales information may not be representative of the dealer's local market.
In a metropolitan area, an individual dealer's sales may not reflect all of the vehicle sales made in that dealer's local market.
In the case of a low volume dealer located in a rural area, the specific dealer's sales can be so small that the vehicle sales information gives an unreliable guide to that dealer's market.
If the dealer is given access to vehicle sales information based upon vehicle sales made throughout an entire zone, that too can be misleading because the zone usually encompasses a large geographic area and thus the vehicle sales made throughout the zone may also not represent the types of vehicles sold in that dealer's local market.
Therefore, it would be desirable to provide a computer-implemented dealer inventory management system that would recommend to each dealer how they should order their retail vehicles.
The recommendation should be formulated by analyzing a dealers availability and developing specific orders that drive availability towards that dealer's ideal sales mix.
The ideal sales mix for a dealer is based on a sampling of vehicle sales made in the dealer's local market during a predefined sales period.
Since the sampling method focuses only on fast-selling vehicles, including those made by other dealers in the same local market, the resultant ideal sales mix includes the best ordering practices of adjacent dealers as well as eliminates the poor practices of the ordering dealer.
Lastly, the dealer inventory management system should account for material constraints when formulating order recommendations.
In accordance with the teachings of the present invention, a dealer inventory management system is provided for recommending which types of vehicles a dealer should order from the automotive manufacturer.
The computer-implemented system includes a vehicle sales data structure for storing vehicle sales information, a dealer data structure for storing dealer information, and a vehicle availability data structure for storing which vehicles are available to each dealer.
A market determination module accesses the vehicle sales and dealer data structures to determine an ideal sales mix of vehicles for each dealer based upon a sampling of vehicle sales made in the dealer's local market.
A dealer assessment module then accesses the vehicle availability data structure to formulate a recommended order for each dealer by comparing the dealer's ideal sales mix to the mix of vehicles available to that dealer.
Additional benefits and advantages of the present invention will become apparent to those skilled in the art to which this invention relates from a reading of the subsequent description of the preferred embodiment and the appended claims, taken in conjunction with the accompanying drawings.
A superensemble is developed using a plurality of forecasts from a variety of weather and climate models.
Along with observed analysis fields, these forecasts are used to derive statistics on the past behavior of the models.
These statistics, combined with future forecasts of the models, enables the construction of a superensemble forecast.
More specifically, given a set of past model forecasts, the present invention uses a multiple regression technique to regress the model forecasts against observed fields.
Least-squares minimization of the difference between the model and the analysis field is used to determine the weights of each model component at any geographic location and vertical level.
Therefore, the superensemble generates a model that combines the historical performance of forecasting data from multiple models at a large number of geographic areas or regions.
Furthermore, the superensemble model can combine the historical performance of multiple models in forecasting one weather condition at any geographic location.
The present invention relates generally to weather forecasts, and more specifically, to weather and seasonal forecasts generated from an assembly of forecast models.
Because of the importance of the weather, forecasts are readily available via a wide variety of media, including the Internet, television, radio and print media.
Images of the weather generated by satellite photographs and radar networks are familiar to almost everyone.
Nevertheless, despite a long history of the study of the atmosphere and its phenomena, and enormous technological and scientific advances, local, regional and seasonal forecasts often are inaccurate.
Meteorology as an exact science is a relatively recent science.
