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All Journal International Journal of Reconfigurable and Embedded Systems (IJRES) Indonesian Journal of Electrical Engineering and Computer Science
Muniappan Ramaraj
Rathinam College of Arts and Science
Economics, Econometrics & Finance

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Sophisticated CPBIS methods applied for FBISODATA clustering algorithm using with real time image database Muniappan Ramaraj; Dhandapani Sabareeswaran; V. Vijayalaksmi; Chembath Jothish; N. Thangarasu; Govindaraj Manivasagam
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 1: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i1.pp614-624

Abstract

Data mining is a process of mining hidden information to the previously unknown data and theoretically useful unknown information from a large amount of genuine data to be stored in a database. Image mining is a part of data mining with used as a predictive measure to identify with the age of the tiger. This research work is mainly focused on, to identify with the age of the Tiger using data mining techniques. This research work incorporates with which those domains of image processing and data mining to predict the age of the tiger using different kinds of color images are used. The fuzzy iterative self-organizing data analysis (FISODATA) clustering method requires more predefined parameters tofind the maximum number of iterations, the minimum number of points in the cluster, and smallest amount of distance with the centers of the clusters. The key undertaking of the studies of diverse colors mechanism is to decide the age of the tiger; the usage of shade action pixel primarily based on image segmentation; the usage of facts that are used in the mining techniques. However, the more matrix components to be measuring the processing time, retrieval time, accuracy, and blunders fee with the aid of using producing better performance.
A new fuzzy rule-based optimization approach for predicting the user behaviour classification in M-commerce Muniappan Ramaraj; Jothish Chembath; Balluru Thammaiahshetty Adishankar Nithya; Gnanakumar Ganesan; Balakrishnan Uma Shankari; Nagarajan Karthikeyan
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 12, No 3: November 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v12.i3.pp320-328

Abstract

A novel approach for classification of user behaviour prediction using proposed embracing the optimized fuzzy techniques to predicting the user data in M-commerce. Using this technique, network users can be monitored and their behavior categorized according to their activity. Unauthorized use of the website, network security breach attempts, firewalls, unauthorized access to the service and frequency of attempts. The proposed method has been adapted with the user classification to predict the predefine segregation of information to extract from user logs. Pattern recognition is a method for information discovery that results in current information patterns. Continuing items are a required task in various knowledge mining operations in pursuit of fascinating types from the data banks, including association rules, connections, sequences, episodes, classifications, bunches and much more. The functionality findings achieved in relation to precision and recall show that our technique can contribute to predicting more accurately than the different approaches. This paper focuses on to enhance the far better forecast for the mobile phone users through locating more reliable frequent patterns coming from the consumer deal data bank through looking at the body weight value of each thing collection and also examining the consumer activities on all time intervals.
Co-Authors Balakrishnan Uma Shankari Balluru Thammaiahshetty Adishankar Nithya Chembath Jothish Dhandapani Sabareeswaran Gnanakumar Ganesan Govindaraj Manivasagam Jothish Chembath N. Thangarasu Nagarajan Karthikeyan V. Vijayalaksmi