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Climate Prediction

CP-KNN: Seasonal to Inter – annual Climate Prediction using Data Mining KNN technique.
The impact of seasonal to inter – annual climate prediction on the society, business, agriculture and almost all aspect of human life enforce the scientist to give proper attention to the matter. The last few years show tremendous achievements in this field. All systems, techniques developed so far, use the Sea Surface Temperature (SST) as a main factor among other seasonal climatic attributes. The statistical and mathematical models are then used for further climate predictions. In this paper we are going to develop a system that uses the historical weather data (Rain, Wind speed, Dew point, temperature etc) of a region and applies data mining algorithm “k–nearest neighbor (KNN)” for classification of these historical data into specific time span, the k nearest time spans (K nearest Neighbors) are then taken to predict the weather a month in advance. The experiments show that the system generates accurate result within reasonable time for a month in advance.
Objectives
The motivation behind the research is to extend the application of Data Mining to the field of meteorology, oceanography and climatology. This will open a new era in the field of Data Mining and climate prediction. The main Objectives are
• Utilization of historical data
• Data Cleansing to convert the data in uniform format
• Concrete Model for Climate Prediction using Data Mining
• Prediction using Numerical Data
• Improvements in performance and accuracy of Climate Prediction
Hypothesis (Problem Solution)
The huge amount of climatic data is available for years. The data should be brought into a uniform format. If the data is noisy it can be cleanse using any of data mining technique. The textual information that is of categorical nature can be converted to numerical form e.g. the attribute having yes/no option will be converted to 1/0. Once the data is converted to numerical format, then the data...