@article{(Open Science Index):https://publications.waset.org/pdf/14600,
	  title     = { Using Data Mining Techniques for Estimating Minimum, Maximum and Average Daily Temperature Values},
	  author    = {S. Kotsiantis and  A. Kostoulas and  S. Lykoudis and  A. Argiriou and  K. Menagias},
	  country	= {},
	  institution	= {},
	  abstract     = {Estimates of temperature values at a specific time of day, from daytime and daily profiles, are needed for a number of environmental, ecological, agricultural and technical applications, ranging from natural hazards assessments, crop growth forecasting to design of solar energy systems. The scope of this research is to investigate the efficiency of data mining techniques in estimating minimum, maximum and mean temperature values. For this reason, a number of experiments have been conducted with well-known regression algorithms using temperature data from the city of Patras in Greece. The performance of these algorithms has been evaluated using standard statistical indicators, such as Correlation Coefficient, Root Mean Squared Error, etc.
},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {1},
	  number    = {2},
	  year      = {2007},
	  pages     = {401 - 405},
	  ee        = {https://publications.waset.org/pdf/14600},
	  url   	= {https://publications.waset.org/vol/2},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 2, 2007},
	}