Skip to main content

Research Repository

Advanced Search

Fuzzy Hot Spot Identification for Big Data: An Initial Approach

Triguero, Isaac; Tickle, Rebecca; Figueredo, Grazziela P.; Mesgarpour, Mohammad; Ozcan, Ender; John, Robert I.

Fuzzy Hot Spot Identification for Big Data: An Initial Approach Thumbnail


Authors

Rebecca Tickle

Mohammad Mesgarpour

Profile Image

ENDER OZCAN ender.ozcan@nottingham.ac.uk
Professor of Computer Science and Operational Research

Robert I. John



Abstract

Hot spot identification problems are present across a wide range of areas, such as transportation, health care and energy. Hot spots are locations where a certain type of event occurs with high frequency. A recent big data approach is capable of identifying hot spots in a dynamic manner, through the processing of large volumes of sensor data arriving as a stream. However, the method may produce imprecise results due to its crisp interpretation of hot spot locations and reliance on a fixed hot spot radius value. This paper presents an initial approach to addressing this shortcoming through incorporating the concept of fuzzy hot spots into the process. Experimental results on large real-world transportation datasets demonstrate the improved way in which this approach handles uncertainty in the definition of hot spots, and highlight promising future research areas for further application of fuzzy systems to the hot spot identification problem.

Citation

Triguero, I., Tickle, R., Figueredo, G. P., Mesgarpour, M., Ozcan, E., & John, R. I. (2019). Fuzzy Hot Spot Identification for Big Data: An Initial Approach. In 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). https://doi.org/10.1109/FUZZ-IEEE.2019.8858979

Conference Name 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
Conference Location New Orleans, LA, USA
Start Date Jun 23, 2019
End Date Jun 26, 2019
Acceptance Date Mar 7, 2019
Online Publication Date Oct 11, 2019
Publication Date 2019-06
Deposit Date Nov 5, 2019
Publicly Available Date Nov 5, 2019
Publisher Institute of Electrical and Electronics Engineers
Series ISSN 1558-4739
Book Title 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
ISBN 978-1-5386-1729-8
DOI https://doi.org/10.1109/FUZZ-IEEE.2019.8858979
Public URL https://nottingham-repository.worktribe.com/output/3059289
Publisher URL https://ieeexplore.ieee.org/document/8858979
Additional Information © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Files




You might also like



Downloadable Citations