Innovative Soft-Computing Solutions for Industrial and Environmental Problems.

The satisfactory results validate the proposed application of classifiers on the dataset improved by data-balancing techniques. Several experiments on a benchmark dataset of household electric energy demand show that the proposed method explains the prediction appropriately with the most influential input attributes in the long-term and short-term dependencies. Novel solutions, based on soft-computing techniques, are proposed in the present issue. [Extracted from the article]