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Predicting Wheat Production in Pakistan by using an Artificial Neural Network Approach

Predicting Wheat Production in Pakistan by using an Artificial Neural Network Approach

Faheem Aslam1*, Aneel Salman1 and Inayatullah Jan2

1Department of Management Sciences, Comsats University, Park Road, Islamabad, Pakistan; 2Institute of Development Studies (IDS), The University of Agriculture, Peshawar, Khyber Pakhtunkhwa, Pakistan.


*Correspondence | Faheem Aslam, Department of Management Sciences, Comsats University, Park Road, Islamabad, Pakistan; Email: faheem.aslam@comsats.edu.pk 

Figure 1:

Annual wheat production growth rate in Pakistan from 1948 to 2018.

Figure 2:

Annual wheat production growth rate in Pakistan from 1948 to 2018.

Figure 3:

Neural network architecture.

Figure 4:

Neural network architecture (full model).

Figure 5:

Hyper parameter optimization for neuron selection (full model).

Figure 6:

Relative Importance Plot for Feature Selection.

Figure 7:

Neural network architecture (selected features).

Figure 8:

Hyper parameter optimization for neuron selection (selected features).

Figure 9:

Actual vs predicted wheat production from 2005 to 2018.

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Sarhad Journal of Agriculture

March

Sarhad Journal of Agriculture, Vol.40, Iss. 1, Pages 01-262

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