Special Issue in Entropy in Soft Computing and Machine Learning Algorithms
Journal of Entropy (ISSN 1099-4300). 2019 Impact Factor: 2.494 (Journal Citation Reports)
DEADLINE 30 NOVEMBER 2021.
Soft computing and machine learning algorithms are used in different fields of science and technology. They are important tools designed to solve complex real-life problems under uncertainty.
Entropy is a powerful tool that has changed the analysis of information. The use of entropy has been extended in soft computing and machine learning methodologies, from measuring uncertainty to exploring and exploiting search spaces in optimization. Different kinds of entropy are used depending on what is required. Moreover, it is necessary to use soft computing and machine learning methods to provide accurate solutions to complex problems in the information era. Hybrid algorithms are also important; they merge skills from different approaches and make decisions based on different rules to accurately explore the possible solutions.
Since the fields of soft computing and machine algorithms are constantly growing, following all the different branches in which entropy is used is complicated. Considering the above, this Special Issue aims to present the latest advances in soft computing and machine learning algorithms that employ or solve problems where entropy is included. It also seeks to include literature reviews and surveys on related topics.
Dr. Diego Oliva
Dr. Salvador Miguel Hinojosa Cervantes
More information: https://www.mdpi.com/journal/entropy/special_issues/soft_comput_alg