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All Outputs (33)

Robotics in construction: A critical review of the reinforcement learning and imitation learning paradigms (2022)
Journal Article

The reinforcement and imitation learning paradigms have the potential to revolutionise robotics. Many successful developments have been reported in literature; however, these approaches have not been explored widely in robotics for construction. The... Read More about Robotics in construction: A critical review of the reinforcement learning and imitation learning paradigms.

Rainfall Prediction: A Comparative Analysis of Modern Machine Learning Algorithms for Time-Series Forecasting (2021)
Journal Article

Rainfall forecasting has gained utmost research relevance in recent times due to its complexities and persistent applications such as flood forecasting and monitoring of pollutant concentration levels, among others. Existing models use complex statis... Read More about Rainfall Prediction: A Comparative Analysis of Modern Machine Learning Algorithms for Time-Series Forecasting.

Deep learning with small datasets: Using autoencoders to address limited datasets in construction management (2021)
Journal Article

Large datasets are necessary for deep learning as the performance of the algorithms used increases as the size of the dataset increases. Poor data management practices and the low level of digitisation of the construction industry represent a big hur... Read More about Deep learning with small datasets: Using autoencoders to address limited datasets in construction management.

IoT for predictive assets monitoring and maintenance: An implementation strategy for the UK rail industry (2020)
Journal Article

With about 100% increase in rail service usage over the last 20 years, it is pertinent that rail infrastructure continues to function at an optimal level to avoid service disruptions, cancellations or delays due to unforeseen asset breakdown. In an e... Read More about IoT for predictive assets monitoring and maintenance: An implementation strategy for the UK rail industry.

Estimating occupancy levels in enclosed spaces using environmental variables: A fitness gym and living room as evaluation scenarios (2020)
Journal Article

The understanding of occupancy patterns has been identified as a key contributor to achieve improvements in energy efficiency in buildings since occupancy information can benefit different systems, such as HVAC (Heating, Ventilation, and Air Conditio... Read More about Estimating occupancy levels in enclosed spaces using environmental variables: A fitness gym and living room as evaluation scenarios.

Genetic algorithm-determined deep feedforward neural network architecture for predicting electricity consumption in real buildings (2020)
Journal Article

A genetic algorithm-determined deep feedforward neural network architecture (GA-DFNN) is proposed for both day-ahead hourly and week-ahead daily electricity consumption of a real-world campus building in the United Kingdom. Due to the comprehensive r... Read More about Genetic algorithm-determined deep feedforward neural network architecture for predicting electricity consumption in real buildings.

Optimised Big Data analytics for health and safety hazards prediction in power infrastructure operations (2020)
Journal Article

© 2020 Elsevier Ltd Forecasting imminent accidents in power infrastructure projects require a robust and accurate prediction model to trigger a proactive strategy for risk mitigation. Unfortunately, getting ready-made machine learning algorithms to e... Read More about Optimised Big Data analytics for health and safety hazards prediction in power infrastructure operations.