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CBRi2: Imputation of solar radiation time series with case based reasoning

This paper proposes a new technique for the short-gaps imputation of not available (NA) values in solar radiation time series. The proposal technique is an update of CBRi hence its name CBRi2. The fundamental changes with respect to CBRi, consist of the definition of a threshold for the recovery of success cases and the insertion of a factor that approximates the results obtained by Case Base Reasoning (CBR) to the closest neighbors of a NA value, that is to its prior and next values. The results achieved show that for the same solar radiation time series CBRi2 exceeds CBRi, Local Average of Nearest Neighbors (LANN) and Autoregressive Integrated Moving Average (ARIMA).