Route selection is essential in everyday life. We have several algorithms for detecting efficient route on Large Road Networks. This paper introduces the hierarchical community, is presented. It splits large road networks into hierarchical structure. It introduces a multi parameter route selection system which employs Fuzzy Logic (FL) and ant’s behavior in nature is applied to the dynamic routing. The important rates of parameters such as path length and traffic are adjustable by the user. The purposes of the new hierarchical routing algorithm significantly reduce the search space. We develop a community-based hierarchical graph model that supports Dynamic, efficient route computation on large road networks.
The agricultural stock depends upon several factors like biological, seasonal, and economic determinants. The growers sustain a vital loss if they are not capable of predicting the variations in these circumstances. The uncertainty on crop yield can be predicted in a logical and mathematical way. The forecast is made based on the previous archives of yield data secured from that area. Data mining is one such procedure practised to predict the crop yield. The systems examine the data, and on mining, several patterns based on numerous parameters predict the return. This article directs on crop yield forecast in Trichy district by adopting data mining techniques for rule formation on classifying the training data and implementing prediction for test data. The suggested method employs fuzzy C means algorithm for clustering and multilayer perceptron design for prediction. The results of accuracy and execution time of the proposed system correlated with the regression algorithm of prediction.
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