Artificial intelligence in preclinical epilepsy research: Current state, potential, and challenges
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 +7 more
wiley +1 more source
Um modelo de rede neuro-fuzzy baseada em funções de base radial capaz de inferir regras do tipo Mamdani [PDF]
Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Ciência da Computação, Florianópolis, 2015.Este trabalho tem como objetivo apresentar um novo sistema de inferência neuro-fuzzy, chamado ...
Rodrigues, Diego Garcia
core
Reactive Power Control of Thyristor Controlled Reactor using Neuro - Fuzzy Controller
In this study, the reactive power of thyristor controlled reactor (TCR) that is fundamental element of flexible ac transmission system devices is controlled using neuro-fuzzy controller.
Ö. Fatih KEÇECİOĞLU, Erdal KILIÇ
doaj +1 more source
Energy Consumption and CO2 Emissions Forecasting of Transport Sector Using Machine Learning
The transport sector accounts for approximately one‐quarter of Iran's final energy consumption. The energy demand in this sector has the least variation, with petroleum products accounting for more than 85% of the demand. Furthermore, the accelerated growth of energy consumption and the sector's reliance on fossil fuels, which are the main cause of ...
Amir Hossein Akbari +2 more
wiley +1 more source
A comparison of fuzzy approaches to e-commerce review rating prediction
This paper presents a comparative analysis of the performance of fuzzy approaches on the task of predicting customer review ratings using a computational intelligence framework based on a genetic algorithm for data dimensionality reduction.
Cosma, G, Acampora, G
core +1 more source
Aim. This paper presents the minimization of reactive and active power ripples of doubly fed induction generators using super twisting algorithms and pulse width modulation based on neuro-fuzzy algorithms. Method. The main role of the indirect active and
H. Benbouhenni, A. Driss, S. Lemdani
doaj +1 more source
PMU‐Based Wide Area Monitoring With Machine Learning to Prevent Blackouts in Bangladesh Power System
A Unified Real‐time Dynamic State Measurements (URTDSM) system with PMU and Phasor Data Concentrator (PDC) deployment plan has been proposed to avoid blackout in the Bangladeshi power system. Machine learning has been used to process data from PMU to identify abnormal events. ABSTRACT The electrical power system must be trustworthy and secure enough to
Imi Bintey Fariha Rahman +5 more
wiley +1 more source
Research progress on the depth of anesthesia monitoring based on the electroencephalogram
Electroencephalogram (EEG) can noninvasive, continuous, and real‐time monitor the state of brain electrical activity, and the monitoring of EEG can reflect changes in the depth of anesthesia (DOA). The development of artificial intelligence can enable anesthesiologists to extract, analyze, and quantify DOA from complex EEG data.
Xiaolan He, Tingting Li, Xiao Wang
wiley +1 more source
An adaptive neuro‐fuzzy inference system is presented which is optimized by a genetic algorithm to classify normal and abnormal brain tumours. The classifier is fast and simple, named genetic algorithm‐adaptive neuro‐fuzzy inference system, and the ...
Marzieh Ghahramani, Nabiollah Shiri
doaj +1 more source
Novel Intelligence ANFIS Technique for Two-Area Hybrid Power System’s Load Frequency Regulation [PDF]
The main objective of Load Frequency Control (LFC) is to effectively manage the power output of an electric generator at a designated site, in order to maintain system frequency and tie-line loading within desired limits, in reaction to fluctuations. The
Nireekshana Namburi +2 more
doaj +1 more source

