Analyzing the Impact of Climate Change With Major Emphasis on Pollution: A Comparative Study of ML and Statistical Models in Time Series Data
This addresses the challenge of predicting and mitigating climate change impacts from pollution for environmental monitoring, but it appears incremental as it compares existing methods without introducing new ones.
The study tackled the problem of forecasting diverse environmental impacts of industrial activities across regions using time series data, comparing machine learning and statistical models, but no concrete results or numbers were reported.
Industrial operations have grown exponentially over the last century, driving advancements in energy utilization through vehicles and machinery.This growth has significant environmental implications, necessitating the use of sophisticated technology to monitor and analyze climate data.The surge in industrial activities presents a complex challenge in forecasting its diverse environmental impacts, which vary greatly across different regions.Aim to understand these dynamics more deeply to predict and mitigate the environmental impacts of industrial activities.