This article introduces a novel Fuzzy Regression Hybrid Algorithm, combining fuzzy logic and regression techniques to enhance predictive modeling. The algorithm adeptly handles uncertainty and non-linearity, offering a robust solution for complex data relationships. Through empirical analysis, the algorithm's effectiveness is demonstrated across various domains, showcasing its potential for accurate predictions and informed decision-making. The Fuzzy Regression Hybrid Algorithm emerges as a valuable tool for tackling real-world challenges and advancing the field of data-driven modeling.
%0 Journal Article
%1 noauthororeditor
%A ogli | Toshtemirov Zafarjon Nematullo ogli, Egamberdiev Nodir Abdunazarovich | Berdiev Maruf Ramshiddin
%D 2023
%J CENTRAL ASIAN JOURNAL OF MATHEMATICAL THEORY AND COMPUTER SCIENCES
%K Fuzzy Hybrid Logic, Model Regression,
%N 8
%P 63-69
%T DEVELOPMENT OF FUZZY REGRESSION HYBRID ALGORITHM
%U https://cajmtcs.centralasianstudies.org/index.php/CAJMTCS/article/view/499/555
%V 4
%X This article introduces a novel Fuzzy Regression Hybrid Algorithm, combining fuzzy logic and regression techniques to enhance predictive modeling. The algorithm adeptly handles uncertainty and non-linearity, offering a robust solution for complex data relationships. Through empirical analysis, the algorithm's effectiveness is demonstrated across various domains, showcasing its potential for accurate predictions and informed decision-making. The Fuzzy Regression Hybrid Algorithm emerges as a valuable tool for tackling real-world challenges and advancing the field of data-driven modeling.
@article{noauthororeditor,
abstract = {This article introduces a novel Fuzzy Regression Hybrid Algorithm, combining fuzzy logic and regression techniques to enhance predictive modeling. The algorithm adeptly handles uncertainty and non-linearity, offering a robust solution for complex data relationships. Through empirical analysis, the algorithm's effectiveness is demonstrated across various domains, showcasing its potential for accurate predictions and informed decision-making. The Fuzzy Regression Hybrid Algorithm emerges as a valuable tool for tackling real-world challenges and advancing the field of data-driven modeling.},
added-at = {2024-02-26T11:16:12.000+0100},
author = {ogli | Toshtemirov Zafarjon Nematullo ogli, Egamberdiev Nodir Abdunazarovich | Berdiev Maruf Ramshiddin},
biburl = {https://www.bibsonomy.org/bibtex/251635cc2cab6bd4b4369487801046183/centralasian_20},
interhash = {20497d2ec7bb86a8a93cf728adafae7e},
intrahash = {51635cc2cab6bd4b4369487801046183},
issn = {2660-5309},
journal = {CENTRAL ASIAN JOURNAL OF MATHEMATICAL THEORY AND COMPUTER SCIENCES},
keywords = {Fuzzy Hybrid Logic, Model Regression,},
language = {english},
month = aug,
number = 8,
pages = {63-69},
timestamp = {2024-02-26T11:16:12.000+0100},
title = {DEVELOPMENT OF FUZZY REGRESSION HYBRID ALGORITHM},
url = {https://cajmtcs.centralasianstudies.org/index.php/CAJMTCS/article/view/499/555},
volume = 4,
year = 2023
}