Optimizing alpha–beta filter for enhanced predictions accuracy in industrial applications using Mamdani fuzzy inference system
This work presents a novel approach for dynamically optimizing the alpha–beta filter parameters through the Mamdani fuzzy inference system (MFIS) for industrial applications to estimate the state of dynamic systems based on sensor measurements. Our proposed method has two important components: the p...
Saved in:
Main Authors: | Junaid Khan, Muhammad Fayaz, Umar Zaman, Eunkyu Lee, Awatef Salim Balobaid, Muhammad Bilal, Kyungsup Kim |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2025-04-01
|
Series: | Alexandria Engineering Journal |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S1110016825001437 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Adaptive Neuro-Fuzzy Inference System guided objective function parameter optimization for inverse treatment planning
by: Eduardo Cisternas Jiménez, et al.
Published: (2025-02-01) -
Fuzzy Inference-Based Adaptive Sonar Control for Collision Avoidance in Autonomous Underwater Vehicles
by: Kot Rafał
Published: (2024-12-01) -
ANFIS-optimized control for resilient and efficient supply chain performance in smart manufacturing
by: Mona A. AbouElaz, et al.
Published: (2025-03-01) -
Implementasi Algoritma Fuzzi Mamdani pada Sistem Pakar Menggunakan Software Aplikasi Matlab R2007B, Studi Kasus: Tanaman Hidroponik Selada Air
by: Okta Purnawirawan, et al.
Published: (2024-10-01) -
Steering conservation biocontrol at the frontlines: A fuzzy logic approach unleashing potentials of climate-smart intercropping as a component within the integrated management of fall armyworm in Africa
by: Komi Mensah Agboka, et al.
Published: (2025-02-01)