Search

Your search keyword '"Subbalakshmi, Chatti"' showing total 19 results
Start Over Author "Subbalakshmi, Chatti"
19 results on '"Subbalakshmi, Chatti"'

2. Energy and Buffer Size-Based Routing Protocol for Internet of Things

Author

Ahanger, Tariq Ahamed, Subbalakshmi, Chatti, Narayana, M. V., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Saini, H. S., editor, Sayal, Rishi, editor, Govardhan, A., editor, and Buyya, Rajkumar, editor

Published
2023
Full Text
View/download PDF

3. A Gravitational Search Algorithm Study on Text Summarization Using NLP

Author

Subbalakshmi, Chatti, Pareek, Piyush Kumar, Narayana, M. V., Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Kumar, Ashwani, editor, Fister Jr., Iztok, editor, Gupta, P. K., editor, Debayle, Johan, editor, Zhang, Zuopeng Justin, editor, and Usman, Mohammed, editor

Published
2022
Full Text
View/download PDF

4. A Study on Social Engineering Attacks in Cybersecurity

Author

Subbalakshmi, Chatti, Pareek, Piyush Kumar, Sayal, Rishi, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Saini, H. S., editor, Sayal, Rishi, editor, Govardhan, A., editor, and Buyya, Rajkumar, editor

Published
2022
Full Text
View/download PDF

5. Improvement of Precision in Agriculture Using IoT-Based Machine Learning Techniques

Author

Narayana, M. V., Rajeshwar, J., Subbalakshmi, Chatti, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Saini, H. S., editor, Sayal, Rishi, editor, Govardhan, A., editor, and Buyya, Rajkumar, editor

Published
2022
Full Text
View/download PDF

9. Cluster Validity Using Modified Fuzzy Silhouette Index on Large Dynamic Data Set

Author

Subbalakshmi, Chatti, Sayal, Rishi, Saini, H. S., Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Behera, Himansu Sekhar, editor, Nayak, Janmenjoy, editor, Naik, Bighnaraj, editor, and Pelusi, Danilo, editor

Published
2020
Full Text
View/download PDF

19. Performance Issues on K-Mean Partitioning Clustering Algorithm

Author

subbalakshmi, chatti, Rao, P. Venkateswara, Rao, S Krishna Mohan, subbalakshmi, chatti, Rao, P. Venkateswara, and Rao, S Krishna Mohan

Abstract

In data mining, cluster analysis is one of challenging field of research. Cluster analysis is called data segmentation. Clustering is process of grouping the data objects such that all objects in same group are similar and object of other group are dissimilar. In literature, many categories of cluster analysis algorithms present. Partitioning methods are one of efficient clustering methods, where data base is partition into groups in iterative relocation procedure. K-means is widely used partition method. In this paper, we presented the k-means algorithm and its mathematical calculations for each step in detailed by taking simple data sets. This will be useful for understanding performance of algorithm. We also executed k-means algorithm with same data set using data mining tool Weka Explorer. The tool displays the final cluster points, but won’t give internal steps. In our paper, we present each step calculations and results. This paper helpful to user, who wants know step by step process. We also discuss performance issues of k-means algorithm for further extension.

Published
2014

Catalog

Books, media, physical & digital resources
See catalog results