User profiles for Oluseun Omotola Aremu
 | Oluseun AremuUniversity of Queensland Verified email at uq.edu.au Cited by 274 |
A machine learning approach to circumventing the curse of dimensionality in discontinuous time series machine data
The growing interest in artificial intelligence has led to current data-driven predictive
maintenance (PdM) relying on machine learning (ML) algorithms. Although ML algorithms are …
maintenance (PdM) relying on machine learning (ML) algorithms. Although ML algorithms are …
A relative entropy based feature selection framework for asset data in predictive maintenance
Predictive maintenance (PdM) is applied to monitor a system’s life cycle to provide current
diagnostics, prognostics and provide information capable of guiding maintenance related …
diagnostics, prognostics and provide information capable of guiding maintenance related …
Exploring the relationship between data science and circular economy: an enhanced CRISP-DM process model
To date, data science and analytics have received much attention from organizations seeking
to explore how to use their massive volumes of data to create value and accelerate the …
to explore how to use their massive volumes of data to create value and accelerate the …
A Relative Entropy Weibull-SAX framework for health indices construction and health stage division in degradation modeling of multivariate time series asset data
Predictive maintenance is the monitoring of an asset’s condition over its life cycle to provide
a prognosis for when maintenance is required. Prior to prognosis, an asset’s life cycle is …
a prognosis for when maintenance is required. Prior to prognosis, an asset’s life cycle is …
Structuring data for intelligent predictive maintenance in asset management
Predictive maintenance (PdM) within asset management improves savings in operational
cost, productivity, and safety management capabilities. While PdM can be administered using …
cost, productivity, and safety management capabilities. While PdM can be administered using …
Kullback-leibler divergence constructed health indicator for data-driven predictive maintenance of multi-sensor systems
OO Aremu, DO O'Reilly… - 2019 IEEE 17th …, 2019 - ieeexplore.ieee.org
The unexpected failure of modern industrial systems is often managed using data-driven
predictive maintenance (PdM) tools that continuously monitor a system's health condition (HC) …
predictive maintenance (PdM) tools that continuously monitor a system's health condition (HC) …
Machine learning-based embedding for discontinuous time series machine data
OO Aremu, D Hyland-Wood… - 2019 IEEE 17th …, 2019 - ieeexplore.ieee.org
This paper presents a machine learning-based dimension reduction framework (ML-framework).
The ML-framework is designed to circumvent the challenges of high-dimensional …
The ML-framework is designed to circumvent the challenges of high-dimensional …
[PDF][PDF] Faculty of Arts
BI Studies - The University of Melbourne, 2020 - lasu.edu.ng
… BUSARI OLUWASEUN AYISAT 3. OLOLAPUPO MUSTAPHA ADEWALE 4. TIAMIYU
ABDUL-LATEEF … AREMU KUNLE OJO 15. ATEY RITA 16. AYENI OLUWATOMISIN BUKOLA 17. …
ABDUL-LATEEF … AREMU KUNLE OJO 15. ATEY RITA 16. AYENI OLUWATOMISIN BUKOLA 17. …
[CITATION][C] Achieving a representation of asset data conducive to machine learning driven predictive maintenance
O Aremu - 2020 - espace.library.uq.edu.au
The success of an operation in industries such as mining, aviation, and industrial manufacturing
is heavily dependent on the continuous functioning of complex systems. These complex …
is heavily dependent on the continuous functioning of complex systems. These complex …
[CITATION][C] Restrained Manifold Learning: Circumventing the Curse of Dimensionality when Preparing Discontinuous Data for Data-Driven Predictive Maintenance
OO Aremu, D Hyland-Wood, PR McAree - algorithms