Comprehensive, Precise and real time data regarding the position and characteristics of animals is necessary for safeguarding visitors inside a wildlife sanctuary. Investigations are made on the capability for automated, unambiguous and economical collection of data that are useful to perform rescue operations within the sanctuary because of the absence of other communicational sources. Web camera enables collection of photos relating to wildlife economically, conservatively as well as regularly. Extraction of information from such photos is costly, slow and requires human intervention. The proposed system demonstrates the automatic extraction of such data using Convolutional Neural Network (CNN). Deep CNN is trained for a set of images available in a wildlife dataset.
Fuzzy logic and Data mining is used to find out some association rules. It is very difficult to find out some association rules of fuzzy values of any membership function because fuzzy values are distinct, so it is very difficult to find the minimum frequency value of any data item sets. It also increases the operational time of item sets. So my research paper is to overcome these problems in very efficient manner. I proposes algorithm to overcome from the above mentioned problem. The size of data items is very large, so it is difficult to reduce its operational time. This research paper tries to eliminate those item sets which are not important for finding any association rule. We also try to eliminate more than 60% of item sets which is not important by using fuzzy classification technique. we able to reduce operational data. This proposed algorithm is more suitable when we apply mining association rule from very large data sets.
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