Modelling carbon emission intensity: Application of artificial neural network
AO Acheampong, EB Boateng - Journal of Cleaner Production, 2019 - Elsevier
This study applies an artificial neural network (ANN) to develop models for forecasting
carbon emission intensity for Australia, Brazil, China, India, and USA. Nine parameters that …
carbon emission intensity for Australia, Brazil, China, India, and USA. Nine parameters that …
Beyond 2020: Modelling obesity and diabetes prevalence
AG Ampofo, EB Boateng - Diabetes research and clinical practice, 2020 - Elsevier
Aims To examine and forecast the patterns of diabetes prevalence in synergy with obesity.
Methods Prophet models were employed to forecast the prevalence of diabetes and obesity …
Methods Prophet models were employed to forecast the prevalence of diabetes and obesity …
A Bibliometrics-Based systematic review of safety risk assessment for IBS hoisting construction
Construction faces many safety accidents with urbanization, particularly in hoisting.
However, there is a lack of systematic review studies in this area. This paper explored the …
However, there is a lack of systematic review studies in this area. This paper explored the …
A glimpse into the future: modelling global prevalence of hypertension
EB Boateng, AG Ampofo - BMC Public Health, 2023 - Springer
Background Hypertension is a major risk factor for cardiovascular diseases. Insights and
foresights on trends of hypertension prevalence are crucial to informing health policymaking …
foresights on trends of hypertension prevalence are crucial to informing health policymaking …
Development of model predictive control system using an artificial neural network: A case study with a distillation column
Y Shin, R Smith, S Hwang - Journal of Cleaner Production, 2020 - Elsevier
Abstracts Over the past few decades, advanced process control (APC) such as model
predictive control (MPC) has been introduced to process industry to enhance its operational …
predictive control (MPC) has been introduced to process industry to enhance its operational …
[HTML][HTML] Analysing near-miss incidents in construction: a systematic literature review
The construction sector is notorious for its high rate of fatalities globally. Previous research
has established that near-miss incidents act as precursors to accidents. This study aims to …
has established that near-miss incidents act as precursors to accidents. This study aims to …
[PDF][PDF] The role of energy consumption and economic growth on carbon emission-application of artificial neural network
This paper examines the influence of gross domestic product (GDP) and energy
consumption (renewable energy and non-renewable energy) on carbon emissions in …
consumption (renewable energy and non-renewable energy) on carbon emissions in …
Validating and forecasting carbon emissions in the framework of the environmental Kuznets curve: the case of Vietnam
This paper examines the environmental Kuznets curve (EKC) in Vietnam between 1977 and
2019. Using the autoregressive distributed lag (ARDL) approach, we find an inverted N …
2019. Using the autoregressive distributed lag (ARDL) approach, we find an inverted N …
Development of novel hybrid machine learning models for monthly thunderstorm frequency prediction over Bangladesh
Thunderstorm frequency (TSF) prediction with higher accuracy is of great significance under
climate extremes for reducing potential damages. However, TSF prediction has received …
climate extremes for reducing potential damages. However, TSF prediction has received …
Deploying artificial neural networks for modeling energy demand: international evidence
E Bannor B, AO Acheampong - International Journal of Energy Sector …, 2020 - emerald.com
Purpose This paper aims to use artificial neural networks to develop models for forecasting
energy demand for Australia, China, France, India and the USA. Design/methodology …
energy demand for Australia, China, France, India and the USA. Design/methodology …