GDL

Atmospheric Condition based Clustering using ART Neural

ISSN 2223-4985
Journal from gdlhub / 2017-08-14 11:52:31
Oleh : Bhupesh Gour , Asif Ullah Khan, International Journal of Information and Communication Technology Research
Dibuat : 2012-06-23, dengan 1 file

Keyword : Atmospheric Conditions, ART, Clusters, Temperature, Pressure, Humidity
Subjek : Atmospheric Condition based Clustering using ART Neural
Url : http://esjournals.org/journaloftechnology/archive/vol2no2/vol2no2_13.pdf
Sumber pengambilan dokumen : Internet

Ambient air temperatures prediction is of a concern in environment, industry and agriculture. The increase of average temperature


results in global warming. The aim of this research is to develop artificial neural network based clustering method for ambient


atmospheric condition prediction in Indian city. In this paper, we presented a clustering method that classifies cities based on


atmospheric conditions like Temperature, Pressure and Humidity. Data representing Month-wise atmospheric conditions are


presented to ART Neural Network to form clusters which represents association in between two or more cities. Such associations


predict atmospheric conditions of one city on the bases of another. ART based clustering method shows that the months of two cities


which fall in the same cluster, represent similar atmospheric conditions in them.

Deskripsi Alternatif :

Ambient air temperatures prediction is of a concern in environment, industry and agriculture. The increase of average temperature


results in global warming. The aim of this research is to develop artificial neural network based clustering method for ambient


atmospheric condition prediction in Indian city. In this paper, we presented a clustering method that classifies cities based on


atmospheric conditions like Temperature, Pressure and Humidity. Data representing Month-wise atmospheric conditions are


presented to ART Neural Network to form clusters which represents association in between two or more cities. Such associations


predict atmospheric conditions of one city on the bases of another. ART based clustering method shows that the months of two cities


which fall in the same cluster, represent similar atmospheric conditions in them.

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