Rainfall Prediction in Hilly Region Using Hybrid Ant Bee Algorithm Incorporated Fuzzy Expert System

Abstract

The weather on a mountainside varies based on the altitude (height). There could be a warm environment in the foothills (down at the bottom), whereas the peaks (the tops of hills) could well be blanketed with ice.It must be said that the region receives the most south west monsoon rainfall of about 35% in September, whereas August receives just 29%. The south west monsoon rains fall 18% and 20% in June and July, accordingly..Agriculture and related industries agro - climatic area management is primarily energy organization. In fact, the regional approach to climate modification is a desire to identify local risk, premised on which effective solution measures can be developed for sustaining natural equilibrium and environmental sustainability, especially in sub tropics under monsoon variation. However, the majority of research much further has been determined by the perceived variations in weather patterns global factors. As a result, we must migrate from broad generalities to local details in order to construct a credible impact estimate on a local scale.The two major goals of a fuzzy inference system driven microarray data categorization are efficiency improvement and complex reduction. To determine the fuzzy segmentation involved in gene predicting the value and generate a simplified rule - based system, ant colony optimization (ACO) with global and regional signal modifications is used. This work uses the artificial bee colony (ABC) algorithm to generate the elements of membership function in order to handle the mutare and uninterrupted expression patterns of a gene. In order to identify useful genes, mutual data is employed. Numbers of genomic data sets are used to assess the efficiency of the suggested hybrid Ant Bee Algorithm