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Dr Kate Han's Outputs (8)

Automating Business Process to Enhance Organisational Efficiency and Productivity: Using Academic Intervention at Salford Business School as a Case Study (2025)
Presentation / Conference Contribution

Organisations, particularly large ones with multiple stakeholders involved in their business processes, frequently face challenges related to process efficiency and productivity, leading to wasted resources, time, and effort, ultimately reducing over... Read More about Automating Business Process to Enhance Organisational Efficiency and Productivity: Using Academic Intervention at Salford Business School as a Case Study.

A Novel Surrogate Model for Variable-Length Encoding and its Application in Optimising Deep Learning Architecture (2024)
Presentation / Conference Contribution

Deep neural networks (DNN) has achieved great successes across multiple domains. In recent years, a number of approaches have emerged on automatically finding the optimal DNN configurations. A technique among these approaches which show great promise... Read More about A Novel Surrogate Model for Variable-Length Encoding and its Application in Optimising Deep Learning Architecture.

VISTA: A Variable Length Genetic Algorithm and LSTM-Based Surrogate Assisted Ensemble Selection algorithm in Multiple Layers Ensemble System (2024)
Presentation / Conference Contribution

We proposed a novel ensemble selection method called VISTA for multiple layers ensemble systems (MLES). Our ensemble model consists of multiple layers of ensemble of classifiers (EoC) in which the EoC in each layer is trained on the data generated by... Read More about VISTA: A Variable Length Genetic Algorithm and LSTM-Based Surrogate Assisted Ensemble Selection algorithm in Multiple Layers Ensemble System.

On Discovering Optimal Trade-Offs When Introducing New Routes in Existing Multi-modal Public Transport Systems (2023)
Presentation / Conference Contribution

While self-driving technology is still being perfected, public transport authorities are increasingly interested in the ability to model and optimise the benefits of adding connected and autonomous vehicles (CAVs) to existing multi-modal transport sy... Read More about On Discovering Optimal Trade-Offs When Introducing New Routes in Existing Multi-modal Public Transport Systems.

Optimising the introduction of connected and autonomous vehicles in a public transport system using macro-level mobility simulations and evolutionary algorithms (2021)
Presentation / Conference Contribution

The past five years have seen a rapid development of plans and test pilots aimed at introducing connected and autonomous vehicles (CAVs) in public transport systems around the world. Using a real-world scenario from the Leeds Metropolitan Area as a c... Read More about Optimising the introduction of connected and autonomous vehicles in a public transport system using macro-level mobility simulations and evolutionary algorithms.

VEGAS: A Variable Length-Based Genetic Algorithm for Ensemble Selection in Deep Ensemble Learning (2021)
Presentation / Conference Contribution

In this study, we introduce an ensemble selection method for deep ensemble systems called VEGAS. The deep ensemble models include multiple layers of the ensemble of classifiers (EoC). At each layer, we train the EoC and generates training data for th... Read More about VEGAS: A Variable Length-Based Genetic Algorithm for Ensemble Selection in Deep Ensemble Learning.