Fuzzy Logic Model for Predicting the Heat Index

10/28/2022
by   Nnamdi Uzoukwu, et al.
0

A fuzzy inference system was developed for predicting the heat index from temperature and relative humidity data. The effectiveness of fuzzy logic in using imprecise mapping of input to output to encode interconnectedness of system variables was exploited to uncover a linguistic model of how the temperature and humidity conditions impact the heat index in a growth room. The developed model achieved an R2 of 0.974 and a RMSE of 0.084 when evaluated on a test set, and the results were statistically significant (F1,5915 = 222900.858, p < 0.001). By providing the advantage of linguistic summarization of data trends as well as high prediction accuracy, the fuzzy logic model proved to be an effective machine learning method for heat control problems.

READ FULL TEXT
research
12/11/2012

A Study on Fuzzy Systems

We use princiles of fuzzy logic to develop a general model representing ...
research
04/22/2021

Finding Fuzziness in Neural Network Models of Language Processing

Humans often communicate by using imprecise language, suggesting that fu...
research
02/10/2019

Software Development Effort Estimation Using Regression Fuzzy Models

Software effort estimation plays a critical role in project management. ...
research
01/10/2017

IoFClime: The fuzzy logic and the Internet of Things to control indoor temperature regarding the outdoor ambient conditions

The Internet of Things is arriving to our homes or cities through fields...
research
03/01/2011

Fuzzy Approach to Critical Bus Ranking under Normal and Line Outage Contingencies

Identification of critical or weak buses for a given operating condition...
research
11/30/2016

Comparison of the COG Defuzzification Technique and Its Variations to the GPA Index

The Center of Gravity (COG) method is one of the most popular defuzzific...

Please sign up or login with your details

Forgot password? Click here to reset