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SPECIAL ISSUE FOR INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS

Applications of Computational Intelligence basedSystems for Societal Enhancement

Fabio Caraffini, Francisco Chiclana, Raymond Moodley, Mario GongoraInstitute of Artificial Intelligence

De Montfort UniversityLeicester, UK

Computational Intelligence (CI), originally represented by the three subjects of Evolutionary Computation (EC), Fuzzy Logic (FL) and Neural Networks (NNs), has significantly evolved to date and is ever more embedded in both software and hardware structures to obtain intelligent systems capable of self-adaptation, decision-making and problem-solving. These highly interconnected and high-level systems are becoming ubiquitous as their applicability has widened and grown to traverse many disciplines and application domains such as e.g. finance, medicine, precision agriculture,sustainability, aviation, as well as in numerous information systems.

To gather the state-of-the art, this special issue calls for recent new advances on intelligent systems and their applications to tackle high impact real-world scenarios for enhancing our society.

I. RELEVANCE OF THE THEME OF THE SPECIAL ISSUE AND NEED IN THE PRESENT CONTEXT

The vertiginous technological growth in the last decades has produced several novel technologies but also a similar amount of novel challenges. We now have instant internet-based services and moving towards smart cities, on the other side we do also have a higher exposure on cyber attacks, privacy issues, etc. Similar considerations can be made in other heterogeneous sectors including information systems, socials, education, the healthcare system, crime prevention, intelligent transportation, finance, precision agriculture, etc., which strongly impact on our society. while computational intelligence techniques have been successfully employed to tackle technical applications in engineering, system control, telecommunication, etc., less has been done to address different application domains having a more direct societal impact. In this light, the proposed special session is timely and encourages the generation and introduction of intelligent systems in such fields of application.

II. AIM AND SCOPE

This special issue aims to attract recent novel advances on applied research for societal improvement through technology and technology-driven generation of knowledge. Despite having a wide scope, a strong emphasis is given to those systems, both hardware and software, displaying an intelligent behaviour thanks to the use of CI, decision making and data mining techniques to address high-impact (e.g. humanitarian, environmental or economical) real-world scenarios for enhancing our society.

We encourage submissions falling in (but not limited to) the following application domains:

• FinTech, Management & Business• Ambient Intelligence• Consensus Modelling in Social Networks• Smart Cities, Smart Environments & Optimal use of

lands• Precision Agriculture & Remote Sensing• Sustainability in Rural Communities

• Intelligent and Safe Transportation• Internet of things & Internet of Beings• Computational Biology, Healthcare & Medicine• Intelligent Wearable Systems• Services Optimisation & Scheduling applications• AI and Robotics in Healthcare• Applied Sentimental Analysis

• Neural Networks & Neural Systems; Fuzzy Logic & FuzzySystems

• Genetic Fuzzy Systems; Fuzzy Neural Systems• Stochastic & Metaheuristic Optimisation• Machine Learning; Reinforcement Learning

In particular when addressed via data mining and computational intelligence methods such as:

• Decision Making• Neuroevolution; Deep Learning• Association Rules & Data Mining• Hybridisation of CI techniques

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III. TIMETABLE FOR THIS SPECIAL ISSUE

Important dates:

• Submission Opens: 1th September 2020• Submission Closes: 31st January 2021• Final Acceptance Notifications: 31st July

2021

IV. GUEST EDITORS

Fabio Caraffini is a senior lecturer in Computer Science and Mathematics at De Montfort University ( Leicetser, UK) and an active resercehr within its Institute of Artificial I ntelligence. H e r eceived t he B Sc i n “ Electronics Engineering” and the MSc in “Telecommunications Engineering” degrees from the University of Perugia (Italy) in 2008 and 2011 respectively and holds a PhD in Computer Science (De Montfort University, UK, 2014) and a PhD in Computing and Mathematical Sciences (University of Jyvaskyla, Finland, 2016). Dr Caraffini sits in the programme committee of established conferences and is engaged within the research community in Evolutionary Computation. His research interests include theoretical and applied computational intelligence with a strong emphasis on heuristics for optimisation.

E: fabio.caraffini@dmu.ac.ukW: http://tinyurl.com/FabioCaraffini

Francisco Chiclana is a professor at the School of Computer Sciences and Informatics at De Montfort University (UK). He received his BSc and PhD in Mathematics from the University of Granada (Spain) in June 1989 and March 2000 re-spectively. Prof. Chiclana is a Visiting Scholar at Dept. of Computer Science and AI (Univ. of Granada, Spain) and was Honorary Professor in the Department of Mathematics at the University of Leicester (UK) in the period 2015-2018. He is an expert in Computational Intelligence and Decision Making, a Highly Cited Researcher (2018, 2019) in Computer Sci-ence, and 24 of his papers are classed as highly cited in WoS (November 2019). Prof. Chiclana is Associate Editor of 10 journals indexed in WoS and one of the Specialty Chief Editor of the Fuzzy Systems section of Frontiers in Artificial Intelligence.

E: chiclana@dmu.ac.ukW: http://tinyurl.com/fchiclana

Raymond Moodley is a Visiting Researcher at the Institute of Artificial Intelligence at DMU. He received his PhD in AI from DMU and holds a MSc in Strategic Management (University of Derby) and a MSc in Chemical Engineering (University of KwaZulu Natal, South Africa). His research interests include the application of AI to enhance society and has developed AI models for education, crime prevention, and medicine.

E: raymond.moodley@dmu.ac.ukW: https://figshare.com/authors/Raymond Moodley/8996357

Mario Gongora is Associate Professor in the School of Computer Science and Informatics at De Montfort University (DMU). He is the Faculty Enterprise Lead and a member of the Institute of Artificial Intelligence at the Faculty of Computing, Engineering and Media. He has a degree in Electronic Engineering and got his MSc and PhD from the University of Warwick (UK). His research started in the field of robotics and machine learning and is currently focusing in the application of Artificial Intelligence techniques for modelling natural phenomena, identification, s imulation a nd optimisation.

E: mgongora@dmu.ac.ukW: Aww.cse.dmu.ac.uk/∼mgongora/