MKFF: mid-point K-means based clustering in wireless sensor network for forest fire prediction
Authors:
- 23 January 2024
- journal article
- research article
- Published by Springer Nature in Microsystem Technologies
- Vol. 30 (4) , 469-480
Abstract
No abstract availableKeywords
This publication has 31 references indexed in Scilit:
- Detection of forest fires using machine learning technique: A perspective2015
- C5. 0 Algorithm to Improved Decision Tree with Feature Selection and Reduced Error PruningInternational Journal of Computer Applications, 2015
- An energy efficient framework for detection and monitoring of forest fire using mobile agent in wireless sensor networks2014
- Visualisation of efficiency coverage and energy consumption of sensors in wireless sensor networks using heat mapIET Communications, 2011
- Fire detection based on hidden Markov modelsInternational Journal of Control, Automation, and Systems, 2010
- OMNeT++2010
- An initialization method for the -Means algorithm using neighborhood modelComputers & Mathematics with Applications, 2009
- An efficient k′-means clustering algorithmPattern Recognition Letters, 2008
- Cluster center initialization algorithm for K-means clusteringPattern Recognition Letters, 2004
- An Exploratory Technique for Investigating Large Quantities of Categorical DataJournal of the Royal Statistical Society Series C: Applied Statistics, 1980