This question aims to explore, from the part of expert colleagues, some methods that can be used to adjust the negative inflows calculated for the dams.
Dear Pr. Houichi,
As you know I'm not specialist in dams, but I asked the same question about negative value in forecasting or prediction of GHG time series using SVM.
I find a very interesting paper (Improved Hybrid Model Based on Support Vector Regression Machine for Monthly Precipitation Forecasting) "Chen and Zhu, Journal of Computer, vol. 8, n 1, junuary 2013".
The authors said "Because the monthly precipitation is nonnegative real value data, the fitting and forecasting data is negative are assigned to zeros".
Hope that idea can help.
But if the negative value are calculated with specific software for dams, please don't consider this answer.
Best regards
Dear all
To a scientific point of view , a negative value can not be replaced by zero.
The response of the black box models using a training algorithm is mainly related to the set of parameters (weights and biases for ANN), which mainly become positive or negative values.
the negative values should be checked one by one and the model need to be retrained several time , and if the values become always negative regardless the values of the parameters , in this case, the model is unable to predict these values for several raisons, and in this case the quality of data is doubtful .
Also in some case it is very important to use a varities of the input and output standarization and normalization.
Best regards
Dear all,
Thanks for the attention..the answers are worthy of contemplation.
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