Angesh Anupam

Cardiff Metropolitan University, Computer Science, Faculty Member

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Dr Angesh Anupam is a data scientist based in Cardiff, United Kingdom. He is employed at Cardiff Metropolitan University, as the Programme Director in Data Science (PG). Along with administration, he is actively involved in lecturing and research in data science. Dr Anupam's area of interests include nonlinear dynamical systems modelling using machine learning techniques, machine learning applications in business analytics, design of decision support systems, sustainable food production, and environmental sustainability.
Address: Llandaff Campus, Western Ave, Cardiff CF5 2YB, United Kingdom

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Kevin Mcilhany

US Naval Academy

Khashayar Ghorbani

joshua gabriel

Journal of Materials Informatics

Theodoros Karakasidis

UNIVERSITY OF THESSALY, GREECE

Arnaud Demortière

Centre National de la Recherche Scientifique / French National Centre for Scientific Research

David Farache

Tapaswani Pradhan

Rakesh K . Barik

Indian Institute of Technology Kharagpur

Laurent Proville

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Papers by Angesh Anupam

Exploiting Machine Learning in Multiscale Modelling of Materials

Journal of the institution of engineers (India) series D, Nov 28, 2022

of machine learning of equivariant properties, machine learning-aided statistical mechanics, the ... more of machine learning of equivariant properties, machine learning-aided statistical mechanics, the incorporation of ab initio approaches in multiscale models of materials processing and application of machine learning in uncertainty quantification. In addition to the above, the applicability of Bayesian approach for multiscale modelling will be discussed. Critical issues related to the multiscale materials modelling are also discussed. This manuscript has been authored in part by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The publisher acknowledges the US government license to provide public access under the DOE Public Access Plan (http://energy.gov/downloads/doe-publicaccess-plan).

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Review of security issues in Internet of Things and artificial intelligence‐driven solutions

SECURITY AND PRIVACY

Data driven modelling and simulation of wetland dynamics

International Journal of Modelling and Simulation, 2021

A Data-Driven Framework for Identifying Tropical Wetland Model

2018 UKACC 12th International Conference on Control (CONTROL), 2018

A wetland is a land area that is saturated with water. Most of the wetlands exhibit seasonal vari... more A wetland is a land area that is saturated with water. Most of the wetlands exhibit seasonal variations because of soil characteristics, climate variables and orography of a site. This study applies the orthogonal least square (OLS) algorithm under the system identification methodology for the identification of a nonlinear dynamic model structure of the tropical wetlands, using a remotely sensed dataset. Despite the availability of data from the multiple tropical sites, a single dynamic-model structure is able to explain the underlying processes, governing the wetland extents of the tropics. The model is validated against a fresh data set, derived using the similar remote sensing technique. Overall, this study is a novel application of the systems identification for obtaining a single model structure of a category of wetlands, enabling some understanding about their dynamics. The model can also be employed for the assessment of future wetlands in the advent of climate change.

Nonlinear Dynamical Systems Modelling for Environmental Sustainability

Increasing global human population coupled with the climate change pose serious threats on the ba... more Increasing global human population coupled with the climate change pose serious threats on the basic needs of society. The coming decades will witness the challenges associated with the food security, land availability, clean water availability, and energy security. These issues directly or indirectly affect the various components of the Earth’s Critical Zone (ECZ). Our natural resources are finite and hence a policy framework is urgently required to deal with the growing demand in food, clean energy, and water in sustainable ways. This work characterises some key components of the ECZ such as wetlands, through modelling and computational simulation approaches. A data-driven methodology known as the system identification is used to devise a nonlinear dynamic model of the tropical wetlands. The dataset used in the study corresponds to a Global Inundation Extent from Multi-Satellites. The model gives some useful insights about the dynamics of tropical wetlands and the possible effects...

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NARX model identification for analysing Amazon vegetation under climate change

The Amazon rainforest is a critical landscape and harbours a wide range of biodiversity. This is ... more The Amazon rainforest is a critical landscape and harbours a wide range of biodiversity. This is considered to be one of the largest sink for anthropogenic carbon sequestration on the Earth. Undoubtably, any substantial variation in the vegetation of this basin have tremendous impact upon the carbon absorption. Nonetheless, the impact of changing climate on the Amazon rainforest further complicates the matter. This study, for the first time, utilises the system identification method, under a wider realm of machine learning, for modelling the nonlinear dynamical relationship among the Leaf Area Index (LAI) and surface temperature for an Amazon rainforest site. The chosen model structure is Nonlinear Autoregressive with Exogenous Inputs (NARX). The training and testing datasets involved in this study correspond to the NASA Earth Observations. On contrary to the existing modelling methods performed for the Amazon, this data driven method results into a parsimonious model structure cons...

Exploiting Machine Learning in Multiscale Modelling of Materials

Journal of the institution of engineers (India) series D, Nov 28, 2022

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Review of security issues in Internet of Things and artificial intelligence‐driven solutions

SECURITY AND PRIVACY

Data driven modelling and simulation of wetland dynamics

International Journal of Modelling and Simulation, 2021

A Data-Driven Framework for Identifying Tropical Wetland Model

2018 UKACC 12th International Conference on Control (CONTROL), 2018

Nonlinear Dynamical Systems Modelling for Environmental Sustainability

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NARX model identification for analysing Amazon vegetation under climate change

Angesh Anupam

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