Chapter 14: Fuzzy-machine learning models for the prediction of fire outbreaks: A comparative analysis
Uduak A. Umoha; Imo J. Eyoha; Vadivel S. Murugesanb; Emmanuel E. Nyohoa a Department of Computer Science, University of Uyo, Uyo, Akwa Ibom, Nigeriab Department of Industrial Production Engineering, National Institute of Engineering, Mysore, India
Abstract
This chapter compares fuzzy-machine learning algorithms for predicting fire outbreaks using temperature, smoke, and flame datasets. The datasets are preprocessed using interval type-2 fuzzy logic (IT2FL). Min-max normalization and principal component analysis (PCA) are used to predict, normalize, and select relevant feature labels in the dataset. The preprocessed datasets are used ...
Get Artificial Intelligence and Machine Learning for EDGE Computing now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
