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Special Sessions

Special sessions are very small and specialized events to be held during the conference as a set of oral and poster presentations that are highly specialized in some particular theme or consisting of the works of some particular international project. The goal of special sessions (minimum 4 papers; maximum 9) is to provide a focused discussion on innovative topics. All accepted papers will be published in a special section of the conference proceedings book, under an ISBN reference, and on digital support. All papers presented at the conference venue will be available at the SCITEPRESS Digital Library. SCITEPRESS is a member of CrossRef and every paper is given a DOI (Digital Object Identifier). The proceedings are submitted for indexation by SCOPUS, Google Scholar, DBLP, Semantic Scholar, Microsoft Academic, EI and Web of Science / Conference Proceedings Citation Index.


CI4EMS 2020Special Session on Computational Intelligence for Energy Management and Storage
Chair(s): Alessio Martino and Fabio Massimo Frattale Mascioli

Special Session on Computational Intelligence for Energy Management and Storage - CI4EMS 2020

Paper Submission: September 21, 2020 (expired)
Authors Notification: September 28, 2020 (expired)
Camera Ready and Registration: October 6, 2020 (expired)


Alessio Martino
Institute of Cognitive Sciences and Technologies, Department of Information Engineering, Electronics and Telecommunications, University of Rome “La Sapienza”, via Eudossiana 18, 00184 Rome
Fabio Massimo Frattale Mascioli
University of Rome “La Sapienza”

The increasing amount of fuel consumption and CO2 pollutions pushed both academia and industrial partners towards the development and implementation of sustainable and advanced energy management strategies. In most cases, the (possibly joint) reduction of costs and emissions leads to the definition of hard optimization problems, possibly mixed-integers and non-convex, which can be solved more effectively (albeit approximately) using computational intelligence techniques.

With this special session, we aim at collecting research and application papers describing current approaches on data-driven modelling for intelligent energy management and storage. This special session aims at being cross-disciplinary: prospective papers may regard neural, fuzzy and evolutionary approaches, or their hybridisation. Surveys and positions papers are also welcome.