Urban Air Quality using K-Means Clustering
Tanvir Mukherjee
Corresponding
Nanyang Technological University
Abstract
As solar photovoltaic plants continues to expand, ensuring the reliability of urban air quality grows steadily more important. The methodology coupled k-means clustering with statistical analysis to quantify the associated uncertainty. The optimised configuration outperformed the conventional design by roughly 42% in the experiments. Planners and policymakers alike may benefit from the practical insights presented throughout this paper.
Keywords:
urban air qualityk-means clusteringmicrostrip antennamimothin filmresponse surface methodology
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