Results 101 to 110 of about 12,863 (232)

ANFIS Controller for Non-holonomic Robots

Majlesi Journal of Electrical Engineering
In this paper, a control strategy for a non-holonomic robot based on an Adaptive Neural Fuzzy Inference System is proposed. The neuro-controller makes it possible for the robot to track a given reference trajectory.
Ting Wang, Christophe Sabourin, Kourosh Madani   +2 more
doaj   +1 more source

Fruit production forecasting by neuro-fuzzy techniques

Neuro-fuzzy techniques are finding a practical application in many fields such as in model identification and forecasting of linear and non-linear systems.
Atsalakis, Ioanna G., Atsalakis, George S.   +1 more
core  

A comparative analysis of soft computing techniques used to estimate missing precipitation records

, 2012
Estimation of missing precipitation records is one of the most important tasks in hydrological and environmental study. The efficiency of hydrological and environmental models is subject to the completeness of precipitation data. This study compared some
Wong, K.W., Fung, Chun Che, Fung, C.C., Wong, Kok Wai, Kajornrit, Jesada, Kajornrit, J.   +5 more
core  

A Predictive Controler for Object Tracking of a Mobile Robot [PDF]

, 2008
In this paper a predictive controller for real-time target tracking in mobile robotics is proposed based on adaptive/evolving Takagi-Sugeno fuzzy systems, eTS.
Angelov, Plamen, Wang, Chu, Zhou, Xiao
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A Portrayal of Sliding Mode Control Through Adaptive Neuro Fuzzy Inference System With Optimization Perspective

IEEE Access
Sliding mode control is a promising approach for designing controllers for systems with empirical characteristics. This is a favored nonlinear control strategy that effectively addresses the uncertainties present in derived mathematical models.
Jim George, Geetha Mani
doaj   +1 more source

Evolving Intelligent Systems, eIS [PDF]

, 2006
The basic concept, formulation, background, and a panoramic view over the recent research results and open problems in the newly emerging area of research that is on the crossroads of computational intelligence and cybernetics is compressed in this short
Angelov, Plamen, Kasabov, Nik
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Laparoscopy Pneumoperitoneum Fuzzy Modeling

, 2011
: Gas volume to intra-peritoneal pressure fuzzy modeling for evaluating pneumoperitoneum in videolaparoscopic surgery is proposed in this paper. The proposed approach innovates in using fuzzy logic and fuzzy set theory for evaluating the accuracy of the ...
Jose E. Araujo Jr., Otavio M. Becker Jr., Joao L. M. C. Azevedo   +2 more
core   +1 more source

Retracted: Taxonomy of Adaptive Neuro-Fuzzy Inference System in Modern Engineering Sciences. [PDF]

Comput Intell Neurosci, 2023
Intelligence And Neuroscience C.
europepmc   +1 more source

PERAMALAN TEMPERATUR UDARA MENGGUNAKAN ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM (ANFIS) [PDF]

, 2009
ABSTRAKSI: Adaptive Neuro Fuzzy Inference System (ANFIS) merupakan kombinasi dari Sistem Inferensi Fuzzy dengan Jaringan Syaraf Tiruan dimana nilai keanggotaan dari Sistem Inferensi Fuzzy akan diperbaiki melalui pembelajaran dengan Jaringan Syaraf Tiruan
DHARUMAS PINURBO
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Prediction of littoral drift with Adaptive Neuro-Fuzzy Inference System

, 2010
Prediction of littoral drift with Adaptive Neuro-Fuzzy Inference System The amount of sand moving parallel to a coastline forms a prerequisite for many harbor design projects.
Hosein Sabet, Mehdi Naseri, Masumeh Sabet   +2 more
core   +1 more source