Outputs (87)

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].

A hybrid approach for stain normalisation in digital histopathological images (2019)
Journal Article
Bukenya, F. (2020). A hybrid approach for stain normalisation in digital histopathological images. Multimedia Tools and Applications, 79(3-4), 2339-2362. https://doi.org/10.1007/s11042-019-08262-0

Stain in-homogeneity adversely affects segmentation and quantifi-cation of tissues in histology images. Stain normalisation techniques have been used to standardise the appearance of images. However, most the available stain normalisation techniques... Read More about A hybrid approach for stain normalisation in digital histopathological images.

An Intelligent Toolkit for Benchmarking Data-Driven Aerospace Prognostics (2019)
Presentation / Conference Contribution
Rengasamy, D., Mase, J. M., Rothwell, B., & Figueredo, G. P. (2019, October). An Intelligent Toolkit for Benchmarking Data-Driven Aerospace Prognostics. Presented at 2019 IEEE Intelligent Transportation Systems Conference - ITSC, Auckland, New Zealand

© 2019 IEEE. Machine Learning (ML) has been largely employed to sensor data for predicting the Remaining Useful Life (RUL) of aircraft components with promising results. A review of the literature, however, has revealed a lack of consensus regarding... Read More about An Intelligent Toolkit for Benchmarking Data-Driven Aerospace Prognostics.

Clinical Scene Segmentation with Tiny Datasets (2019)
Presentation / Conference Contribution
Smith, T. J., Sharkey, D., Crowe, J., & Valstar, M. (2019, October). Clinical Scene Segmentation with Tiny Datasets. Presented at 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW), Seoul, Korea (South)

Many clinical procedures could benefit from automatic scene segmentation and subsequent action recognition. Using Convolutional Neural Networks to semantically segment meaningful parts of an image or video is still an unsolved problem. This becomes e... Read More about Clinical Scene Segmentation with Tiny Datasets.

Optimal Power Flow Based Architecture Design for Electrical Power System in More-Electric Aircraft (2019)
Presentation / Conference Contribution
Wang, X., Atkin, J., Bozhko, S., & Hill, C. I. (2019, October). Optimal Power Flow Based Architecture Design for Electrical Power System in More-Electric Aircraft. Presented at IEEE 45th Annual Conference of the Industrial Electronics Society (IECON'2019), Lisbon, Portugal

When designing an electric power system (EPS) architecture for a more electric aircraft (MEA), the total weight of the system is treated as one of the most important criteria. For the weight saving purpose, this paper proposes an optimal power flow (... Read More about Optimal Power Flow Based Architecture Design for Electrical Power System in More-Electric Aircraft.

A novel framework for evaluating the impact of individual decision-making on public health outcomes and its potential application to study antiviral treatment collection during an influenza pandemic (2019)
Journal Article
Venkatesan, S., Nguyen-Van-Tam, J., & Siebers, P.-O. (2019). A novel framework for evaluating the impact of individual decision-making on public health outcomes and its potential application to study antiviral treatment collection during an influenza pandemic. PLoS ONE, 14(10), Article e0223946. https://doi.org/10.1371/journal.pone.0223946

© 2019 Venkatesan et al. The importance of accounting for social and behavioural processes when studying public health emergencies has been well-recognised. For infectious disease outbreaks in particular, several methods of incorporating individual b... Read More about A novel framework for evaluating the impact of individual decision-making on public health outcomes and its potential application to study antiviral treatment collection during an influenza pandemic.

A Measure of Structural Complexity of Hierarchical Fuzzy Systems Adapted from Software Engineering (2019)
Presentation / Conference Contribution
Razak, T. R., Garibaldi, J. M., & Wagner, C. (2019, June). A Measure of Structural Complexity of Hierarchical Fuzzy Systems Adapted from Software Engineering. Presented at International Conference on Fuzzy Systems (FUZZ-IEEE 2019), New Orleans, USA

Hierarchical fuzzy systems (HFSs) have been seen as an effective approach to reduce the complexity of fuzzy logic systems (FLSs), largely as a result of reducing the number of rules. However, it is not clear completely how complexity of HFSs can be m... Read More about A Measure of Structural Complexity of Hierarchical Fuzzy Systems Adapted from Software Engineering.