Outputs (17)

Sensitizing Scenarios: Sensitizing Designer Teams to Theory (2020)
Presentation / Conference Contribution
Waern, A., Rajkowska, P., Johansson, K. B., Back, J., Spence, J., & Løvlie, A. S. (2020, April). Sensitizing Scenarios: Sensitizing Designer Teams to Theory. Presented at CHI '20: CHI Conference on Human Factors in Computing Systems, Honolulu HI USA

Concepts and theories that emerge within the social sciences tend to be nuanced, dealing with complex social phenomena. While their relevance to design could be high, it is difficult to make sense of them in design projects, especially when participa... Read More about Sensitizing Scenarios: Sensitizing Designer Teams to Theory.

Parameterised Resource-Bounded ATL (2020)
Presentation / Conference Contribution
Alechina, N., Demri, S., & Logan, B. (2020, February). Parameterised Resource-Bounded ATL. Presented at Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), New York, NY, USA

It is often advantageous to be able to extract resource requirements in resource logics of strategic ability, rather than to verify whether a fixed resource requirement is sufficient for achieving a goal. We study Parameterised Resource-Bounded Alter... Read More about Parameterised Resource-Bounded ATL.

Ensemble Deep Learning for Multilabel Binary Classification of User-Generated Content (2020)
Journal Article
Haralabopoulos, G., Anagnostopoulos, I., & McAuley, D. (2020). Ensemble Deep Learning for Multilabel Binary Classification of User-Generated Content. Algorithms, 13(4), Article 83. https://doi.org/10.3390/a13040083

Uncertainty-Aware Forecasting of Renewable Energy Sources (2020)
Presentation / Conference Contribution
Pekaslan, D., Wagner, C., Garibaldi, J. M., Marín, L. G., & Sáez, D. (2020, February). Uncertainty-Aware Forecasting of Renewable Energy Sources. Presented at 2020 IEEE International Conference on Big Data and Smart Computing (BigComp), Busan, Korea (South)

Smart grid systems are designed to enable the efficient capture and intelligent distribution of electricity across a distributed set of utilities. They are an essential component of increasingly important renewable energy sources, where it is vital t... Read More about Uncertainty-Aware Forecasting of Renewable Energy Sources.

Multigranulation Super-Trust Model for Attribute Reduction (2020)
Journal Article
Ding, W., Pedrycz, W., Triguero, I., Cao, Z., & Lin, C.-T. (2020). Multigranulation Super-Trust Model for Attribute Reduction. IEEE Transactions on Fuzzy Systems, 29(6), 1395-1408. https://doi.org/10.1109/tfuzz.2020.2975152

As big data often contains a significant amount of uncertain, unstructured, and imprecise data that are structurally complex and incomplete, traditional attribute reduction methods are less effective when applied to large-scale incomplete information... Read More about Multigranulation Super-Trust Model for Attribute Reduction.

Intersection SPaT Estimation by means of Single-Source Connected Vehicle Data (2020)
Presentation / Conference Contribution
Rostami-Shahrbabaki, M., Bogenberger, K., Safavi, A. A., & Moemeni, A. (2020, January). Intersection SPaT Estimation by means of Single-Source Connected Vehicle Data. Presented at Transportation Research Board (TRB) Annual Meeting 2020, Washington DC, USA

Current traffic management systems in urban networks require real-time estimation of the traffic states.With the development of in-vehicle and communication technologies, connected vehicle data has emerged as a new data source for traffic measurement... Read More about Intersection SPaT Estimation by means of Single-Source Connected Vehicle Data.

A Bibliometric Overview of the Field of Type-2 Fuzzy Sets and Systems [Discussion Forum] (2020)
Journal Article
Shukla, A. K., Kumar Bansal, S., Seth, T., Basu, A., John, R., & Muhuri, P. K. (2020). A Bibliometric Overview of the Field of Type-2 Fuzzy Sets and Systems [Discussion Forum]. IEEE Computational Intelligence Magazine, 15(1), 89-98. https://doi.org/10.1109/MCI.2019.2954669

© 2005-2012 IEEE. Fuzzy Sets and Systems is an area of computational intelligence, pioneered by Lotfi Zadeh over 50 years ago in a seminal paper in Information and Control. Fuzzy Sets (FSs) deal with uncertainty in our knowledge of a particular situa... Read More about A Bibliometric Overview of the Field of Type-2 Fuzzy Sets and Systems [Discussion Forum].