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Explainable AI: novel approaches and applications in engineering Very powerful approaches have been developed in the context of artificial intelligence and big data analytics during the last years. Such approaches deal with large datasets, considering all samples and measurements, as well as including many additional features. However, most of them are presented as blackboxes which prevent experts from understanding the relations found, or simply, to properly interpret them. Guest editors: Dr. Francisco Martínez-Álvarez Data Science and Big Data Lab, Pablo de Olavide University, Seville, Spain fmaralv@upo.es Dr. Mohannad-Zeyad Naser College of Engineering, Computing and Applied Sciences, Clemson University, Clemson, USA mznaser@clemson.edu Special issue information: Topics of primary interest include, but are not limited to: Novel XAI models for spatial and temporal data. Novel XAI models for real-time processing. Novel XAI models for visualization. Rule-based approaches for XAI
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