Groundwater sources are crucial for human activities and general sustainable improvement, particularly in urban areas. However, the growing populace and urbanization pose significant challenges to controlling and planning for these resources. This is where technical predictive analytics, ML, and DL approaches can play an essential role in smart metropolis-making plans. ML algorithms can examine ancient and real-time information to create models that could, as they should, include modifications in groundwater levels. This will help town planners make informed decisions on the green use of groundwater sources for diverse functions, including consuming water supply, irrigation, and business tactics. DL strategies can further decorate the accuracy of those predictions by incorporating non-linear relationships and excessive-dimensional facts. ML and DL models can also identify capability risks and vulnerabilities associated with groundwater assets, including contamination and depletion, and provide early caution structures for mitigating those issues. This can aid in the sustainable management of groundwater resources and prevent capability failures.
L. Godlin Atlas, K.V. Shiny
Bharath Institute of Higher Education and Research, India
Groundwater, Dimensional, Accuracy, Relationships, Structures
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| Published By :
ICTACT
Published In :
ICTACT Journal on Data Science and Machine Learning
( Volume: 5 , Issue: 1 , Pages: 555 - 559 )
Date of Publication :
December 2023
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