Thesis/Capstone
Publication Date
Authored by
Topic(s) Covered:
  • Case Study
  • Forecasting
  • Product Development
  • Simulation
Abstract

This project explores whether the readily available data in agriculture, published by various sources such as USDA, universities and weather stations, can be used in conjunction with the manufacturer’s private data to better forecast the demand of agricultural products (chemicals). We analyzed certain variables such as corn price, acres harvested etc., using three regression models to quantify their significance in predicting demand over various time and geographical horizons. We found out that corn price and fertilizer price are significant in predicting annual demand.

Authors: Derik Smith and Satya Dhavala
Advisor: Dr. Bruce Arntzen