All Outputs (12)

A Hybrid Evolutionary Strategy to Optimise Early-Stage Cancer Screening (2019)
Conference Proceeding

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)
Conference Proceeding

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)
Conference Proceeding

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)
Conference Proceeding

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.

A Simulation-based Optimisation Approach for Inventory Management of Highly Perishable Food (2019)
Conference Proceeding

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.

Position Paper: The Usefulness of Data-driven, Intelligent Agent-Based Modelling for Transport Infrastructure Management (2018)
Conference Proceeding

The uneven utilisation of modes of transport has a big impact on traffic in transport pathway infrastrutures. For motor vehicles for instance, this situation explains rapid road deterioration and the large amounts of money invested in maintenance and... Read More about Position Paper: The Usefulness of Data-driven, Intelligent Agent-Based Modelling for Transport Infrastructure Management.

A genetic algorithm with composite chromosome for shift assignment of part-time employees (2018)
Conference Proceeding

Personnel scheduling problems involve multiple tasks, including assigning shifts to workers. The purpose is usually to satisfy objectives and constraints arising from management, labour unions and employee preferences. The shift assignment problem is... Read More about A genetic algorithm with composite chromosome for shift assignment of part-time employees.

Vehicle incident hot spots identification: An approach for big data (2017)
Conference Proceeding

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.

Adaptive Data Communication Interface: A User-Centric Visual Data Interpretation Framework (2015)
Conference Proceeding

In this position paper, we present ideas about creating a next generation framework towards an adaptive interface for data communication and visualisation systems. Our objective is to develop a system that accepts large data sets as inputs and provid... Read More about Adaptive Data Communication Interface: A User-Centric Visual Data Interpretation Framework.

A data analysis framework to rank HGV drivers (2015)
Conference Proceeding

We report on the details of the methodology applied to support shortlisting the nominees for the Microlise Driver of the Year awards. The aim was to recognise the United Kingdom’s most talented heavy goods vehicle (HGV) drivers, with the list of top... Read More about A data analysis framework to rank HGV drivers.

Comparing System Dynamics and Agent-Based Simulation for tumour growth and its interactions with effector cells (2011)
Conference Proceeding

There is little research concerning comparisons and combination of System Dynamics Simulation (SDS) and Agent Based Simulation (ABS). ABS is a paradigm used in many levels of abstraction, including those levels covered by SDS. We believe that the est... Read More about Comparing System Dynamics and Agent-Based Simulation for tumour growth and its interactions with effector cells.

The use of agent-based simulation to discover extreme cases in immune-interactions with early-stage cancer scenarios
Conference Proceeding