Journals Proceedings

International Journal of Artificial Intelligence and Neural Networks

A New Time Series Based Fuzzy Logic Approach for Prediction of Atmospheric Temperature



Temperature prediction could be a temporal and statistic based mostly method. Weather prediction has drawn heap of analysis interest in recent years. The prediction of temperature has essential applications in numerous fields like climate watching, weather prediction, agriculture, energy, aviation, communication, pollution spread etc. The fuzzy aggregation has powerful logic expression ability and is in a position to precise inaccurate and unsure in sequence. during this paper, a Fuzzy data – Rule base technique is employed to predict the close part temperature for Indian coastal cities. The current study utilizes historical temperature likewise as info of varied meteorologic parameters to develop a prediction method in fuzzy rule domain to estimate temperature. Daily observations of Mean water level Pressure, ratio and Temperature for all three seasons area unit analyzed to predict the Temperature for a given values of Mean water level Pressure and ratio. Symbolic logic has principally been utilized in totally different quite field either in taking call, or system and statement. Symbolic logic is one that may represent a knotty scenario into a straightforward kind in an exceedingly language that's simply caught by humans. Similarly, to represent the character of weather simply understood by normal individuals, this is often the results of foretelling supported meteorological information. We tend to propose a Testing the strength of Exponential Regression Model for prediction of atmosphere temperature. The planned methodology gets higher average statement accuracy rate than a number of the prevailing strategies on temperature prediction

No fo Author(s) : 4
Page(s) : 24 - 28
Electronic ISSN : 2250-3749
Volume 6 : Issue 2
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