Dr GRAZZIELA FIGUEREDO's Outputs (7)

Using agent-based modelling for investigating modal shift: The case of university travel (2019)
Journal Article
Olusola, F. T., Siebers, P.-O., Faboya, O., Ryan, B., & Figueredo, G. P. (2020). Using agent-based modelling for investigating modal shift: The case of university travel. Computers and Industrial Engineering, 139, Article 106077. https://doi.org/10.1016/j.cie.2019.106077

© 2019 Travel mode choices are a result of several factors and how they affect individual travellers. This paper examines those factors influencing travellers’ mode choices commuting to and from a university. Furthermore, we investigate how a shift t... Read More about Using agent-based modelling for investigating modal shift: The case of university travel.

A Hybrid Evolutionary Strategy to Optimise Early-Stage Cancer Screening (2019)
Presentation / Conference Contribution
Figueredo, G. P., Shi, P., Parkes, A. J., Evans, K., Garibaldi, J. M., Negm, O., Tighe, P. J., Sewell, H. F., & Robertson, J. (2019, June). A Hybrid Evolutionary Strategy to Optimise Early-Stage Cancer Screening. Presented at 2019 IEEE Congress on Evolutionary Computation (CEC), Wellington, New Zealand

Current methods to identify cutoff values for tumour-associated molecules (antigens) discrimination are based on statistics and brute force. These methods applied to cancer screening problems are very inefficient, especially with large data sets with... Read More about A Hybrid Evolutionary Strategy to Optimise Early-Stage Cancer Screening.

Microarray Feature Selection and Dynamic Selection of Classifiers for Early Detection of Insect Bite Hypersensitivity in Horses (2019)
Presentation / Conference Contribution
Maciel Guerra, A., Figueredo, G. P., Von Zuben, F., Marti, E., Twycross, J., & Alcocer, M. J. (2019, June). Microarray Feature Selection and Dynamic Selection of Classifiers for Early Detection of Insect Bite Hypersensitivity in Horses. Presented at 2019 IEEE Congress on Evolutionary Computation (CEC), Wellington, New Zealand

Microarrays can be employed to better characterise allergies, as interactions between antibodies and allergens in mammals can be monitored. Once the joint dynamics of these elements in both healthy and diseased animals are understood, a model to pred... Read More about Microarray Feature Selection and Dynamic Selection of Classifiers for Early Detection of Insect Bite Hypersensitivity in Horses.

Evolving Deep CNN-LSTMs for Inventory Time Series Prediction (2019)
Presentation / Conference Contribution
Xue, N., Triguero, I., Figueredo, G. P., & Landa-Silva, D. (2019, June). Evolving Deep CNN-LSTMs for Inventory Time Series Prediction. Presented at 2019 IEEE Congress on Evolutionary Computation (CEC), Wellington, New Zealand

Inventory forecasting is a key component of effective inventory management. In this work, we utilise hybrid deep learning models for inventory forecasting. According to the highly nonlinear and non-stationary characteristics of inventory data, the mo... Read More about Evolving Deep CNN-LSTMs for Inventory Time Series Prediction.

Fuzzy Hot Spot Identification for Big Data: An Initial Approach (2019)
Presentation / Conference Contribution
Triguero, I., Tickle, R., Figueredo, G. P., Mesgarpour, M., Ozcan, E., & John, R. I. (2019, June). Fuzzy Hot Spot Identification for Big Data: An Initial Approach. Presented at 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), New Orleans, LA, USA

Hot spot identification problems are present across a wide range of areas, such as transportation, health care and energy. Hot spots are locations where a certain type of event occurs with high frequency. A recent big data approach is capable of iden... Read More about Fuzzy Hot Spot Identification for Big Data: An Initial Approach.

PAS3-HSID: a Dynamic Bio-Inspired Approach for Real-Time Hot Spot Identification in Data Streams (2019)
Journal Article
Tickle, R., Triguero, I., Figueredo, G. P., Mesgarpour, M., & John, R. I. (2019). PAS3-HSID: a Dynamic Bio-Inspired Approach for Real-Time Hot Spot Identification in Data Streams. Cognitive Computation, 11(3), 434–458. https://doi.org/10.1007/s12559-019-09638-y

© 2019, Springer Science+Business Media, LLC, part of Springer Nature. Hot spot identification is a very relevant problem in a wide variety of areas such as health care, energy or transportation. A hot spot is defined as a region of high likelihood o... Read More about PAS3-HSID: a Dynamic Bio-Inspired Approach for Real-Time Hot Spot Identification in Data Streams.

A Simulation-based Optimisation Approach for Inventory Management of Highly Perishable Food (2019)
Presentation / Conference Contribution
Xue, N., Landa-Silva, D., Figueredo, G. P., & Triguero, I. (2019, February). A Simulation-based Optimisation Approach for Inventory Management of Highly Perishable Food. Presented at 8th International Conference on Operations Research and Enterprise Systems, Prague, Czech Republic

The taste and freshness of perishable foods decrease dramatically with time. Effective inventory management requires understanding of market demand as well as balancing customers needs and references with products’ shelf life. The objective is to av... Read More about A Simulation-based Optimisation Approach for Inventory Management of Highly Perishable Food.