Results 81 to 90 of about 4,688 (196)
Strong Convergence of Neuro-Fuzzy Learning With Adaptive Momentum for Complex System
This paper studies a split-complex-valued neuro-fuzzy algorithm for fuzzy inference system, which realizes a frequently used zero-order Takagi-Sugeno-Kang system. Here, adaptive momentum is utilized to speed up the learning convergence.
Yan Liu, Fang Liu, Long Li
doaj +1 more source
ABSTRACT Combining different theoretical frameworks can lead to new insights into the role of material things in shaping human experience in the Paleolithic period. This paper first presents a historical review of three theoretical approaches in archaeology, anthropology, and the philosophy of mind: Material culture and materiality studies, the ...
Bar Efrati
wiley +1 more source
Background and Objective: One of the important environmental problems is the mass production of urban waste, which has increased per capita household waste production with the ever-increasing population growth; Therefore, nowadays, the use of ...
Samira Bagheri +3 more
doaj
ABSTRACT Flood loss mapping is one of the essential prerequisites for urban flood assessment studies to identify areas vulnerable to floods and to make cities safe and resilient. This study develops a neuro‐fuzzy loss model to generate flood loss maps, classifying loss levels into several categories ranging from no loss to severe loss.
Mahdi Sedighkia +2 more
wiley +1 more source
ANFIS Controller for Non-holonomic Robots
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 +2 more
doaj +1 more source
Modeling of Activated Sludge Process Using Sequential Adaptive Neuro-fuzzy Inference System [PDF]
In this study, an adaptive neuro-fuzzy inference system (ANFIS) has been applied to model activated sludge wastewater treatment process of Mobin petrochemical company.
Mahsa Vajedi, Shahrokh Shahhosseini
doaj
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
Retracted: Taxonomy of Adaptive Neuro-Fuzzy Inference System in Modern Engineering Sciences. [PDF]
Intelligence And Neuroscience C.
europepmc +1 more source
Classification of COVID-19 Individuals Using Adaptive Neuro-Fuzzy Inference System. [PDF]
Dehghandar M, Rezvani S.
europepmc +2 more sources
Enhancing Intrusion Detection Systems with Adaptive Neuro-Fuzzy Inference Systems
Network security has become increasingly critical in recent years. Among the various aspects of network security and considering several approaches to network security, intrusion detection systems (IDSs) have gained considerable attention. The prominence of this factor, among other factors of network security, is due to its ability to address the ...
Jitender Sharma +5 more
openaire +1 more source

