Estimating the availability of Sunshine Using Data Mining Techniques

机译：使用数据挖掘技术估算阳光的可用性

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The daily temperature values of a city or place acts as data for prediction of rainfall, energy calculation etc. There are weather stations available which records the weather of almost all the region in the earth. The weather data acquired in these stations are raw data and found in abundance. The data mining techniques can be applied to these raw data to acquire meaningful patterns out of it, which can be used to predict rainfall, solar energy availability etc. This paper deals with estimating the temperature values of four cities in Tamil Nadu, South India namely Chennai, Coimbatore, Madurai and Kanyakumari. The paper also illustrates the use of data mining technique- Clustering algorithms Simple k-Means and Expectation Maximization algorithm to compare the availability of sun shine in the above mentioned cities, this facilitates for estimation of solar energy to be acquired in these cities.

机译：城市或地方的日常温度值充当降雨，能量计算等的预测数据。有可用的气象站，它记录了地球上几乎所有地区的天气。在这些站中获取的天气数据是原始数据，在丰富的情况下发现。数据挖掘技术可以应用于这些原始数据以获取其中的有意义的模式，可以用于预测降雨，太阳能可用性等。本文涉及估算泰米尔纳德邦，南印度南印度的四个城市的温度值 Chennai，Coimbatore，Madurai和Kanyakumari。本文还说明了使用数据挖掘技术集群聚类算法简单的K-means和期望最大化算法，可以比较上述城市中的太阳照耀的可用性，这有助于估计在这些城市中的太阳能。

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《ICCCI 2013;International Conference on Computer Communication and Informatics》|2013年||共4页
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作者
M.Mayilvahanan; M.Sabitha;
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中图分类 TN919-532;
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Weather Data; Data Mining; Clustering; Simple K-Means; Expectation Maximization; Solar energy.;

机译：天气数据;数据挖掘;聚类;简单的K均值;期望最大化;太阳能。;

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Estimating the availability of Sunshine Using Data Mining Techniques

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