Prof. JONATHAN GARIBALDI's Outputs (8)

A fast community detection method in bipartite networks by distance dynamics (2017)
Journal Article
Sun, H.-L., Ch'ng, E., Yong, X., Garibaldi, J. M., See, S., & Chen, D.-B. (2018). A fast community detection method in bipartite networks by distance dynamics. Physica A: Statistical Mechanics and its Applications, 496, https://doi.org/10.1016/j.physa.2017.12.099

Many real bipartite networks are found to be divided into two-mode communities. In this paper, we formulate a new two-mode community detection algorithm BiAttractor. It is based on distance dynamics model Attractor proposed by Shao et al. with extens... Read More about A fast community detection method in bipartite networks by distance dynamics.

Determining firing strengths through a novel similarity measure to enhance uncertainty handling in non-singleton fuzzy logic systems (2017)
Presentation / Conference Contribution
Pekaslan, D., Kabir, S., Wagner, C., & Garibaldi, J. M. (2017). Determining firing strengths through a novel similarity measure to enhance uncertainty handling in non-singleton fuzzy logic systems. In Proceedings of the 9th International Joint Conference on Computational Intelligence - Volume 0IJCCI (83-90). https://doi.org/10.5220/0006502000830090

Non-singleton Fuzzy Logic Systems have the potential to tackle uncertainty within the design of fuzzy systems. The inference process has a major role in determining results, being partly based on the interaction of input and antecedent fuzzy sets (in... Read More about Determining firing strengths through a novel similarity measure to enhance uncertainty handling in non-singleton fuzzy logic systems.

Vehicle incident hot spots identification: An approach for big data (2017)
Presentation / Conference Contribution
Triguero, I., Figueredo, G. P., Mesgarpour, M., Garibaldi, J. M., & John, R. (2017). Vehicle incident hot spots identification: An approach for big data. In Proceedings - 16th IEEE International Conference on Trust, Security and Privacy in Computing and Communications; 11th IEEE International Conference on Big Data Science and Engineering (IEEE BigDataSE); and 14th IEEE International Conference on Embedded Software and Systems, (901-908). https://doi.org/10.1109/Trustcom/BigDataSE/ICESS.2017.329

In this work we introduce a fast big data approach for road incident hot spot identification using Apache Spark. We implement an existing immuno-inspired mechanism, namely SeleSup, as a series of MapReduce-like operations. SeleSup is composed of a nu... Read More about Vehicle incident hot spots identification: An approach for big data.

An improved game-theoretic approach to uncover overlapping communities (2017)
Journal Article
Sun, H.-L., Ch'ng, E., Yong, X., Garibaldi, J. M., See, S., & Chen, D.-B. (2017). An improved game-theoretic approach to uncover overlapping communities. International Journal of Modern Physics C, 28(8), Article 1750112. https://doi.org/10.1142/S0129183117501121

How can we uncover overlapping communities from complex networks to understand the inherent structures and functions? Chen et al. firstly proposed a community game (Game) to study this problem, and the overlapping communities have been discovered whe... Read More about An improved game-theoretic approach to uncover overlapping communities.

An Immune-Inspired Technique to Identify Heavy Goods Vehicles Incident Hot Spots (2017)
Journal Article
Figueredo, G. P., Triguero, I., Mesgarpour, M., Maciel Guerra, A., Garibaldi, J. M., & John, R. (2017). An Immune-Inspired Technique to Identify Heavy Goods Vehicles Incident Hot Spots. IEEE Transactions on Emerging Topics in Computational Intelligence, 1(4), 248-258. https://doi.org/10.1109/TETCI.2017.2721960

We report on the adaptation of an immune-inspired instance selection technique to solve a real-world big data problem of determining vehicle incident hot spots. The technique, which is inspired by the Immune System self-regulation mechanism, was orig... Read More about An Immune-Inspired Technique to Identify Heavy Goods Vehicles Incident Hot Spots.

Exploring the use of type-2 fuzzy sets in multi-criteria decision making based on TOPSIS (2017)
Presentation / Conference Contribution
Madi, E., Garibaldi, J. M., & Wagner, C. (2017). Exploring the use of type-2 fuzzy sets in multi-criteria decision making based on TOPSIS. In 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (1-6). https://doi.org/10.1109/FUZZ-IEEE.2017.8015664

Multi-criteria decision making (MCDM) problems are a well known category of decision making problem that has received much attention in the literature, with a key approach being the Technique for Order Preference by Similarity to Ideal Solution (TOPS... Read More about Exploring the use of type-2 fuzzy sets in multi-criteria decision making based on TOPSIS.

A new accuracy measure based on bounded relative error for time series forecasting (2017)
Journal Article
Chen, C., Twycross, J., & Garibaldi, J. M. (2017). A new accuracy measure based on bounded relative error for time series forecasting. PLoS ONE, 12(3), Article e0174202. https://doi.org/10.1371/journal.pone.0174202

Many accuracy measures have been proposed in the past for time series forecasting comparisons. However, many of these measures suffer from one or more issues such as poor resistance to outliers and scale dependence. In this paper, while summarising c... Read More about A new accuracy measure based on bounded relative error for time series forecasting.

Modeling and control of operator functional state in a unified framework of fuzzy inference petri nets (2017)
Journal Article
Zhang, J.-H., Xia, J.-J., Garibaldi, J. M., Groumpos, P. P., & Wang, R.-B. (2017). Modeling and control of operator functional state in a unified framework of fuzzy inference petri nets. Computer Methods and Programs in Biomedicine, 144, https://doi.org/10.1016/j.cmpb.2017.03.016

Background and objective: In human-machine (HM) hybrid control systems, human operator and machine cooperate to achieve the control objectives. To enhance the overall HM system performance, the discrete manual control task-load by the operator must b... Read More about Modeling and control of operator functional state in a unified framework of fuzzy inference petri nets.