Application of Machine Learning (ML) and Computational Modelling (CM) in Energy Transition Journey to Achieve Net Zero 2050
Climate change has significantly impacted the livelihood of mankind. Extreme weather, rising of sea levels and increasing temperature are among the results of climate change. Globally and nationally significant measures have been addressed to mitigate the impact of climate change not limited to policies and developed strategies. Malaysia pledged to achieve the Net Zero target by 2050. To progress towards this target, the Carbon Development Strategy for Malaysia has been established to progress towards achieving the Net Zero target. Industry sectors are paving to reduce carbon emissions through improved energy efficiencies, integration of renewables in the energy mix and applying fuel switching among the initiatives. The talk highlights low-carbon development initiatives from lab to industrial case studies that apply ML and Computational Modelling. ML and deep learning play significant roles in today’s computational era to enable predictions/forecast specific outcomes with a higher degree of accuracy and finding patterns and relationships in data for various aims. It enables prediction and forecasted scenarios ranging across many disciplines and chemical engineering.
