Applied Soft Computing 

TL;DR: A review on deep learning methods for semantic segmentation applied to various application areas and points out a set of promising future works to help researchers decide which are the ones that best suit their needs and goals.

TL;DR: The comparative analysis has shown that the Fuzzy TOPSIS method is better suited to the problem of supplier selection in regard to changes of alternatives and criteria, agility and number of criteria and alternative suppliers.

TL;DR: A new wrapper feature selection approach is proposed based on Whale Optimization Algorithm based on the influence of using the Tournament and Roulette Wheel selection mechanisms instead of using a random operator in the searching process to search the optimal feature subsets for classification purposes.

TL;DR: This paper reviews the state-of-the-art and focuses over a wide range of applications of SVMs in the field of hydrology, providing a brief synopsis of the techniques of SVM and other emerging ones (hybrid models), which have proven useful in the analysis of the various hydrological parameters.

TL;DR: A comprehensive literature review on DL studies for financial time series forecasting implementations and grouped them based on their DL model choices, such as Convolutional Neural Networks (CNNs), Deep Belief Networks (DBNs), Long-Short Term Memory (LSTM).