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P. Verma et al.
Fig. 3 Rainfall of thirty-nine years (1980–2018) of two hill stations (Majitar and Ghum)
rainfall as indicated in Table 2 shows nearly an expected estimation. For scale-free
measures of fit, MAE is calculated. First a couple of “best possible” models are
selected, and after that best n estimated models based on the lowest RMSE or MAE
has been selected for the prediction.
This table shows that the various parameters after prediction of rainfall give the
better result with scatter index which is minimum in Majitar, and mean absolute
error (MAE) is also minimum in Majitar because of its higher altitude. So, we fix
the model na and nc value which is 6 and 4 for Ghum, but for Majitar it is 6 and 8
for the betterment of result, and na and nc are polynomial order and delays of the
model, respectively.
5 Summary and Conclusion
Rainfall has got a direct impact on agriculture, and on the other hand, it is also the
major cause of the natural disasters like landslide. So, in order to arrange for any
mitigation of the above said issues, we need to predict the event at an early stage
of it happening. The regression model tuned for this work shows acceptable error
P. Verma et al.
Fig. 3 Rainfall of thirty-nine years (1980–2018) of two hill stations (Majitar and Ghum)
rainfall as indicated in Table 2 shows nearly an expected estimation. For scale-free
measures of fit, MAE is calculated. First a couple of “best possible” models are
selected, and after that best n estimated models based on the lowest RMSE or MAE
has been selected for the prediction.
This table shows that the various parameters after prediction of rainfall give the
better result with scatter index which is minimum in Majitar, and mean absolute
error (MAE) is also minimum in Majitar because of its higher altitude. So, we fix
the model na and nc value which is 6 and 4 for Ghum, but for Majitar it is 6 and 8
for the betterment of result, and na and nc are polynomial order and delays of the
model, respectively.
5 Summary and Conclusion
Rainfall has got a direct impact on agriculture, and on the other hand, it is also the
major cause of the natural disasters like landslide. So, in order to arrange for any
mitigation of the above said issues, we need to predict the event at an early stage
of it happening. The regression model tuned for this work shows acceptable error