Predicting average regional yield and production of wheat in the Argentine Pampas by an artificial neural network approach

By R. Alvarez. 2009

166 citations recorded by the source corpus.

Subfields: Ecology, Environmental Engineering, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/f77da01cffce47ad8c82eefc47cc1c57de7e2651

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

1. Majeed Safa
2. M. Nejat
3. Sandhya Samarasinghe

In Environmental Engineering

1. Majeed Safa
2. M. Nejat
3. Sandhya Samarasinghe

In Global and Planetary Change

1. Majeed Safa
2. M. Nejat
3. Sandhya Samarasinghe

Citations in the corpus

• Prediction of Wheat Production Using Artificial Neural Networks and Investigating Indirect Factors Affecting It: Case Study in Canterbury Province, New Zealand (2015, methodology): “i i z t N MSE − = ∑ (1) Where, ti and zi”