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Table 3 Overall comparison of multiple regression (REG), backpropagation neural network (BPNN), generalized regression neural network (GRNN) and support vector machine (SVM) based prediction accuracy of rice blast severity measured as average correlation coefficient (r), coefficient of determination (r2) and percent mean absolute error (%MAE) of observed value for 'cross-location' and 'cross-year' models.

From: Machine learning techniques in disease forecasting: a case study on rice blast prediction

Model(s) Multiple Regression (REG) Artificial Neural Network (ANN) Support Vector Machine (SVM)
     BPNN GRNN    
  r r 2 %MAE r r 2 %MAE r r 2 %MAE r r 2 %MAE
Cross-location models             
2000 0.57 0.33 67.01 0.61 0.39 51.68 0.67 0.47 40.20 0.73 0.55 33.74
2001 0.44 0.23 77.95 0.50 0.29 66.42 0.62 0.45 64.51 0.70 0.54 48.93
2002 0.50 0.29 97.48 0.64 0.45 94.04 0.66 0.49 83.87 0.69 0.58 57.09
2003 0.48 0.26 66.76 0.58 0.34 58.03 0.68 0.48 53.28 0.82 0.67 41.37
2004 0.43 0.22 78.51 0.47 0.28 60.38 0.65 0.44 49.43 0.78 0.62 39.44
Average 0.48 0.27 77.54 0.56 0.35 66.11 0.66 0.47 58.26 0.74 0.59 44.12
Cross-year models             
Location-I 0.42 0.21 65.96 0.51 0.29 61.12 0.60 0.37 55.93 0.69 0.48 47.97
Location-II 0.40 0.20 73.29 0.41 0.23 59.66 0.59 0.40 54.21 0.70 0.51 40.98
Location-III 0.42 0.22 56.11 0.62 0.39 38.41 0.76 0.59 33.10 0.78 0.62 25.85
Location-IV 0.68 0.49 68.29 0.73 0.55 50.85 0.78 0.63 41.44 0.85 0.73 34.90
Location-V 0.59 0.37 63.46 0.73 0.54 51.15 0.76 0.58 46.79 0.84 0.72 33.62
Average 0.50 0.30 65.42 0.60 0.40 52.24 0.70 0.51 46.30 0.77 0.61 36.66
  1. where,
  2. L – I = Location-I viz. Palampur (1st date of transplanting; 15 days prior to normal transplanting)
  3. L – II = Location-II viz. Palampur (2nd date of transplanting; normal time of transplanting)
  4. L – III = Location-III viz. Palampur (3rd date of transplanting; 15 days after the normal transplanting)
  5. L – IV = Location-IV viz. Rice Research Station, Malan (CSK HPAU)
  6. L – V = Location-V viz. Farmers' fields, Pharer.