Results 81 to 90 of about 62,652 (233)

Video‐based diagnostics supported by artificial intelligence as an opportunity to address the epilepsy diagnostic gap: A narrative review

Epilepsia, EarlyView.
Abstract Despite advancements in epilepsy care, a substantial diagnostic gap persists, particularly in resource‐limited settings. This narrative review explores the potential of video‐based diagnostics augmented by artificial intelligence (AI) to address this gap by enabling earlier and more accessible seizure detection and classification.
Gadi Miron, Robert Terziev, Maximilian Schöls, John McLaren, Tobias Loddenkemper, Jörg Wellmer, Sigrid Mues, Christian Meisel   +7 more
wiley   +1 more source

Adaptive neuro-fuzzy model with fuzzy clustering for nonlinear prediction and control [PDF]

, 2014
Nonlinear systems have more complex manner and profoundness than linear systems.Thus, their analyses are much more difficult.This paper presents the use of neuro-fuzzy networks as means of implementing algorithms suitable for nonlinear black-box ...
Al-Himyari, Bayadir Abbas, Gitano, Horizon, Yasin, Azman   +2 more
core  

Comparative performance of intelligent algorithms for system identification and control [PDF]

, 2008
This paper presents an investigation into the comparative performance of intelligent system identification and control algorithms within the framework of an active vibration control (AVC) system.
Dahal, Keshav, Hossain, Alamgir, Madkour, Ammr, Yu, Hongniang   +3 more
core   +2 more sources

Artificial intelligence in preclinical epilepsy research: Current state, potential, and challenges

Epilepsia Open, EarlyView.
Abstract Preclinical translational epilepsy research uses animal models to better understand the mechanisms underlying epilepsy and its comorbidities, as well as to analyze and develop potential treatments that may mitigate this neurological disorder and its associated conditions. Artificial intelligence (AI) has emerged as a transformative tool across
Jesús Servando Medel‐Matus, Cesar Santana‐Gomez, Ruby G. Escalante, Dominique Duncan, Pedro F. Viana, Giulia Sofia Cereda, Naoto Kuroda, Aristea S. Galanopoulou   +7 more
wiley   +1 more source

A Data-Driven Approach of Takagi-Sugeno Fuzzy Control of Unknown Nonlinear Systems

Applied Sciences, 2020
A novel approach to build a Takagi-Sugeno (T-S) fuzzy model of an unknown nonlinear system from experimental data is presented in the paper. The neuro-fuzzy models or, more specifically, fuzzy basis function networks (FBFNs) are trained from input–output
Bin Zhang, Yung C. Shin
doaj   +1 more source

"Can the neuro fuzzy model predict stock indexes better than its rivals?" [PDF]

This paper develops a model of a trading system by using neuro fuzzy framework in order to better predict the stock index. Thirty well-known stock indexes are analyzed with the help of the model developed here.
Chi-Chung Huang, Chin-Shien Lin, Haider Ali Khan   +2 more
core  

Machine Learning and Artificial Intelligence Techniques for Intelligent Control and Forecasting in Energy Storage‐Based Power Systems

Energy Science &Engineering, EarlyView.
A new energy paradigm assisted by AI. ABSTRACT The tremendous penetration of renewable energy sources and the integration of power electronics components increase the complexity of the operation and power system control. The advancements in Artificial Intelligence and machine learning have demonstrated proficiency in processing tasks requiring ...
Balasundaram Bharaneedharan, Suresh Panchanathan, Chan Choon Kit, Elumalai Perumal Venkatesan, Nasim Hasan   +4 more
wiley   +1 more source

Optimization of Energy Efficiency in Photovoltaic Water Pumping Systems Using Neural Networks

Energy Science &Engineering, EarlyView.
This study investigates an optimal control strategy for a photovoltaic (PV) water pumping system aimed at improving efficiency and autonomy in off‐grid applications. The system uses an induction motor with direct torque control and compares three maximum power point tracking (MPPT) techniques: neural network–based MPPT, Incremental Conductance (IC ...
Sihem Ghoudelbourk, Habib Benbouhenni, Z. M. S. Elbarbary, Mohamed Benidir   +3 more
wiley   +1 more source

Smart Solar Power Site Selection Through a Hybrid Computational Framework of Neuro‐Fuzzy With Genetic Algorithm Optimization

Energy Science &Engineering, EarlyView.
Solar Power plants at various locations a: Pavagada SPP, Karnataka b: Bhadla SPP, Rajasthan c: West Bengal Solar Park ABSTRACT This paper presents a new neuro‐fuzzy multi‐criteria decision‐making (MCDM) framework designed to optimize the selection of solar power plant (SPP) sites across India.
Rajkumari Malemnganbi Devi, Benjamin A. Shimray, Ingudam Chitrasen Meitei, Khelchandra Thongam, Shuma Adhikari, Anuradha Laishram, Subir Datta, Ahmed Al Mansur, Taha Selim Ustun   +8 more
wiley   +1 more source

Robust Control Using a Matrix Converter to Enhance Wind Turbine Systems

Energy Science &Engineering, EarlyView.
This study uses a more efficient and effective solution to improve the operational performance of a wind turbine‐based power system. This system uses a doubly fed induction generator and relies on a matrix converter and fractional‐order proportional–integral controller.
Sihem Ghoudelbourk, Habib Benbouhenni, Adil Yahdou, Zakaria Mohamed Salem Elbarary, Nicu Bizon   +4 more
wiley   +1 more source