The authors use neural networks to examine the power of Treasury term spreads and other macro-financial variables forecast US recessions compare them with probit regression. They propose a novel three-step econometric method for cross-validating conducting statistical inference on machine learning classifiers explaining forecasts. find that regression does not underperform network classifier in...

The purpose of this paper is to explore the dynamics of neural networks in forecasting crop (wheat) yield using remote sensing and other data. We use the Adaptive Neuro-Fuzzy Inference System (ANFIS). The input to ANFIS are several parameters derived from the crop growth simulation model (CGMS) including soil moisture content, above ground biomass, and storage organs biomass. In addition we use...

Information on the outlook of yield and production of crops over large regions is essential for government services dealing with import and export of food crops, for agencies playing a role in food relief, for international organisations with a mandate in monitoring the world food production and trade, as well as for commodity traders. In Europe, such information is provided by the MARS (Monito...