An improved weighted density clustering based ensemble model for air quality index prediction
Keywords:
Air quality analysis, multi-level clustering, heterogeneous data samples.Abstract
Air quality analysis plays a vital role in the multi-region based severity detection.Since, most of the conventional density based clustering approaches use static homogeneoustype of air quality data for severity prediction. However, most of the conventional models arenot applicable to dynamic sub-region based cluster analysis for severity prediction. In thiswork,a novel weighted density inter and intra cluster based ensemble learning approach isdeveloped for air quality prediction process. Experimental results show that the proposedmulti-level weighted density based clustering approach has better efficiency for sub-clustering and severity detection process than the conventional approaches.
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Published
2023-03-27
How to Cite
Krishna Chaitanya Atmakuri, Dr. K V Prasad. (2023). An improved weighted density clustering based ensemble model for air quality index prediction. SJIS-P, 35(1), 566–575. Retrieved from http://sjis.scandinavian-iris.org/index.php/sjis/article/view/351
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