MaREI Symposium 2024: AI ML techniques are pivotal in climate change risk assessment, predicting meteorological events, water quality (WQ) assessment and characterizing hazard sources. Variations in hydro-climatic variables are recognized for influencing water availability and quality across various regions. Sophisticated statistical methods offer precise quantification of connections between hydro-climatic factors and WQ parameters, complementing ML AI models. Aim: To analyse the inter-relationship between  hydro-climatic variables and WQ by obtaining insights into trend changes over the years.

MD GALAL UDDIN

MaREI Symposium 2024: AI ML techniques are pivotal in climate change risk assessment, predicting meteorological events, water quality (WQ) assessment and characterizing hazard sources. Variations in hydro-climatic variables are recognized for influencing water availability and quality across various regions. Sophisticated statistical methods offer precise quantification of connections between hydro-climatic factors and WQ parameters, complementing ML AI models. Aim: To analyse the inter-relationship between hydro-climatic variables and WQ by obtaining insights into trend changes over the years.

MD GALAL UDDIN

Civil Engineering

Research output: Contribution to conference (Published) › Poster

Original language	English (Ireland)
Publication status	Published - 1 Jan 2024
Event	MaREI Symposium 2024 at University College Cork, Ireland. 2024 - Duration: 20 Jun 2024 → …

Conference

Conference	MaREI Symposium 2024 at University College Cork, Ireland. 2024
Period	20/06/24 → …

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 13 Climate Action

Authors (Note for portal: view the doc link for the full list of authors)

Authors
Apoorva Bamal, Uddin. Md Galal, Olbert Indiana

Cite this

UDDIN, MD. GALAL. (2024). MaREI Symposium 2024: AI ML techniques are pivotal in climate change risk assessment, predicting meteorological events, water quality (WQ) assessment and characterizing hazard sources. Variations in hydro-climatic variables are recognized for influencing water availability and quality across various regions. Sophisticated statistical methods offer precise quantification of connections between hydro-climatic factors and WQ parameters, complementing ML AI models. Aim: To analyse the inter-relationship between hydro-climatic variables and WQ by obtaining insights into trend changes over the years. . Poster session presented at MaREI Symposium 2024 at University College Cork, Ireland. 2024.

UDDIN, MD GALAL. / MaREI Symposium 2024 : AI ML techniques are pivotal in climate change risk assessment, predicting meteorological events, water quality (WQ) assessment and characterizing hazard sources. Variations in hydro-climatic variables are recognized for influencing water availability and quality across various regions. Sophisticated statistical methods offer precise quantification of connections between hydro-climatic factors and WQ parameters, complementing ML AI models. Aim: To analyse the inter-relationship between hydro-climatic variables and WQ by obtaining insights into trend changes over the years. . Poster session presented at MaREI Symposium 2024 at University College Cork, Ireland. 2024.

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title = "MaREI Symposium 2024: AI ML techniques are pivotal in climate change risk assessment, predicting meteorological events, water quality (WQ) assessment and characterizing hazard sources. Variations in hydro-climatic variables are recognized for influencing water availability and quality across various regions. Sophisticated statistical methods offer precise quantification of connections between hydro-climatic factors and WQ parameters, complementing ML AI models. Aim: To analyse the inter-relationship between hydro-climatic variables and WQ by obtaining insights into trend changes over the years. ",

author = "UDDIN, \{MD GALAL\}",

year = "2024",

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language = "English (Ireland)",

note = "MaREI Symposium 2024 at University College Cork, Ireland. 2024 ; Conference date: 20-06-2024",

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UDDIN, MDGALAL 2024, 'MaREI Symposium 2024: AI ML techniques are pivotal in climate change risk assessment, predicting meteorological events, water quality (WQ) assessment and characterizing hazard sources. Variations in hydro-climatic variables are recognized for influencing water availability and quality across various regions. Sophisticated statistical methods offer precise quantification of connections between hydro-climatic factors and WQ parameters, complementing ML AI models. Aim: To analyse the inter-relationship between hydro-climatic variables and WQ by obtaining insights into trend changes over the years. ', MaREI Symposium 2024 at University College Cork, Ireland. 2024, 20/06/24.

MaREI Symposium 2024: AI ML techniques are pivotal in climate change risk assessment, predicting meteorological events, water quality (WQ) assessment and characterizing hazard sources. Variations in hydro-climatic variables are recognized for influencing water availability and quality across various regions. Sophisticated statistical methods offer precise quantification of connections between hydro-climatic factors and WQ parameters, complementing ML AI models. Aim: To analyse the inter-relationship between hydro-climatic variables and WQ by obtaining insights into trend changes over the years. . / UDDIN, MD GALAL.
2024. Poster session presented at MaREI Symposium 2024 at University College Cork, Ireland. 2024.

Research output: Contribution to conference (Published) › Poster

UDDIN MDGALAL. MaREI Symposium 2024: AI ML techniques are pivotal in climate change risk assessment, predicting meteorological events, water quality (WQ) assessment and characterizing hazard sources. Variations in hydro-climatic variables are recognized for influencing water availability and quality across various regions. Sophisticated statistical methods offer precise quantification of connections between hydro-climatic factors and WQ parameters, complementing ML AI models. Aim: To analyse the inter-relationship between hydro-climatic variables and WQ by obtaining insights into trend changes over the years. . 2024. Poster session presented at MaREI Symposium 2024 at University College Cork, Ireland. 2024.