Abstract

A tariff is a list of costs incurred during the movement of commodities across different distances. Seasonal and non-seasonal variables also affect tariffs. The goal of this study is to use multiple linear regression, a machine learning method, to estimate truck load tariff rates. We will attempt to forecast the truck tariff rates by using a few variables and the machine learning regression procedure previously discussed. By doing this, we can assist the industries in estimating the tariff rates so they can take the appropriate steps and manage and control the cost of transportation to run their businesses profitably

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