Rain Fall Prediction using Ada Boost Machine Learning Ensemble Algorithm

Every government takes initiative for the well-being of their citizens in terms of environment and climate in which they live. Global warming is one of the reason for climate change. With the help of machine learning algorithms in the flash light of Artificial Intelligence and Data Mining techniques, weather predictions not only rainfall, lightings, thunder outbreaks, etc. can be predicted. Management of water reservoirs, flooding, traffic - control in smart cities, sewer system functioning and agricultural production are the hydro-meteorological factors that affect human life very drastically. Due to dynamic nature of atmosphere, existing Statistical techniques (Support Vector Machine (SVM), Decision Tree (DT) and logistic regression (LR)) fail to provide good accuracy for rainfall forecasting. Different weather features (Temperature, Relative Humidity, Dew Point, Solar Radiation and Precipitable Water Vapour) are extracted for rainfall prediction. In this research work, data analysis using machine learning ensemble algorithm like Adaptive Boosting (Ada Boost) is proposed. Dataset used for this classification application is taken from hydrological department, India from 1901-2015. Overall, proposed algorithm is feasible to be used in order to qualitatively predict rainfall with the help of R tool and Ada Boost algorithm. Accuracy rate and error false rates are compared with the existing Support Vector Machine (SVM) algorithm and the proposed one gives the better result

New algorithm for solving mixed intuitionistic fuzzy assignment problem

In conventional assignment problem, cost is always certain. In this paper, Assignment problem with crisp, fuzzy and intuitionistic fuzzy numbers as cost coefficients is investigated. There is no systematic approach for finding an optimal solution for mixed intuitionistic fuzzy assignment problem. This paper develops an approach to solve a mixed intuitionistic fuzzy assignment problem where cost is not in deterministic numbers but imprecise ones. The solution procedure of mixed intuitionistic fuzzy assignment problem is proposed to find the optimal assignment and also obtain an optimal value in terms of triangular intuitionistic fuzzy numbers. Numerical examples show that an intuitionistic fuzzy ranking method offers an effective tool for handling an intuitionistic fuzzy assignment problem

Transportation problem with the aid of triangular intuitionistic fuzzy numbers

In this paper, we investigate transportation problem in which supplies and demands are intuitionistic fuzzy numbers. Intuitionistic fuzzy Vogel's Approximation method is proposed to find an initial basic feasible solution in terms of triangular intuitionistic fuzzy numbers. The solution procedure is illustrated with suitable numerical example