Results 71 to 80 of about 52,378 (250)
, 2010 Predictive modeling is the process of identifying a model of an unknown or complex process from numerical data. Due to the inherent complexity of many real processes, conventional modeling techniques have proved to be too restrictive. Recently, the hybrid approach to predictive modeling has become a popular research focus.
Azar, , Taher, Ahmad
openaire +3 more sources
EcoEnergy, EarlyView.As maritime transport electrifies, bidirectional charging (V2G) offers a dual‐purpose solution for energy resilience and economic viability. This work identifies key technological advancements and lifecycle challenges utilizing practical case studies to demonstrate how V2G systems can drive decarbonization and grid stability in the marine sector ...
Jonathan Bloor +3 more
wiley +1 more source
Modeling of biotechnological objects [PDF]
BIO Web of ConferencesThe article discusses the system of modeling biotechnological objects and biogas production in the process of fermentation of various agricultural wastes.
Kalandarov P.I. +4 more
doaj +1 more source
Design of an Adaptive Neurofuzzy Inference Control System for the Unified Power-Flow Controller [PDF]
, 2011 This paper presents a new approach to control the operation of the unified power-flow controller (UPFC) based on the adaptive neurofuzzy inference controller (ANFIC) concept.
Farrag, Mohamed, Putrus, Ghanim
core +1 more source
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 +7 more
wiley +1 more source
Using of artificial intelligence for improving of lautering process productivity (part 2).
Kvasný průmysl, 2001 For control of lautering process firm Kiemann and Technical University Heilbronn have developed and control system Neuro-Fuzzy-Controller, that enables to obtain very good results even under using raw stuffs of different qualities.
F. MIROLL +4 more
doaj +1 more source
Approximation properties of the neuro-fuzzy minimum function [PDF]
, 1999 The integration of fuzzy logic systems and neural networks in data driven nonlinear modeling applications has generally been limited to functions based upon the multiplicative fuzzy implication rule for theoretical and computational reasons.
Gottschling, Andreas, Kreuter, Christof
core
Clinical use and radiological yield of magnetic resonance fingerprinting in epilepsy
Epilepsia, EarlyView.Abstract Objective Magnetic resonance fingerprinting (MRF) is a novel paradigm for magnetic resonance imaging (MRI) that efficiently generates multiparametric quantitative tissue property maps with a single acquisition. Its quantitative nature offers many advantages over conventional MRI.
Maksim Parfyonov +11 more
wiley +1 more source
Fruit production forecasting by neuro-fuzzy techniques [PDF]
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, George S. +1 more
core +1 more source
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 +7 more
wiley +1 more source