Prediction of environmental indicators in land leveling using artificial intelligence techniques

Chemical and Biological Technologies in Agriculture

Table 4 Calculated statistical criteria for prediction of total machinery cost/energy using different combination of optimization methods and FIS types

Optimization method	Fis type	MSE			R ²
Optimization method	Fis type	Min.	Ave.	Max.	Min.	Ave.	Max.
Cost
Hybrid	Mamdani	0.00122	0.00188	0.00387	0.9837	0.9921	0.9949
Hybrid	Sugeno	0.00119	0.00185	0.00394	0.9834	0.9922	0.9950
Back propagation	Mamdani	0.00140	0.00251	0.00465	0.9805	0.9894	0.9941
Back propagation	Sugeno	0.00141	0.00250	0.00465	0.9805	0.9895	0.9940
Energy
Hybrid	Mamdani	0.00059	0.00121	0.00353	0.9856	0.9950	0.9975
Hybrid	Sugeno	0.00058	0.00120	0.00356	0.9855	0.9952	0.9976
Back propagation	Mamdani	0.00077	0.00183	0.00395	0.9839	0.9925	0.9968
Back propagation	Sugeno	0.00080	0.00182	0.00395	0.9839	0.9926	0.9967