مدلسازی رابطه دبی_اشل در رودخانه با استفاده از روش شبکههای عصبی مصنوعی(ANN) و روش کنترل گروهی دادهها(GMDH)(مطالعه موردی: رودخانه اسکویلکیل) [PDF]
پژوهشهای حفاظت آب و خاک, 2016 پیشبینی جریان در رودخانهها، یکی از مهمترین مولفههای فرآیندهای هیدرولیکی و هیدرولوژیکی در مدیریت منابع آب میباشد. به منظور کاربردهای هیدرولوژیکی گوناگون نظیر تجزیه وتحلیل بیلان آب و رسوب و همچنین پروژههای کنترل و بهرهبرداری از مخازن، وجود اطلاعات
مریم حسین زاده +2 more
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Predicting Stream Nitrogen Concentration From Watershed Features Using Neural Networks [PDF]
, 1999 The present work describes the development and validation of an artificial neural network (ANN) for the purpose of estimating inorganic and total nitrogen concentrations. The ANN approach has been developed and tested using 927 nonpoint source watersheds
Giraudel, J.-L. +2 more
core +2 more sources
Robust estimation based nonlinear higher order sliding mode control strategies for PMSG-WECS [PDF]
Bulletin of the Polish Academy of Sciences: Technical Sciences, 2023 The wind energy conversion systems (WECS) suffer from an intermittent nature of source (wind) and the resulting disparity between power generation and electricity demand. Thus, WECS are required to be operated at maximum power point (MPP).
Awais Nazir +7 more
doaj +1 more source
POWER RIPPLE REDUCTION OF DPC DFIG DRIVE USING ANN CONTROLLER [PDF]
Acta Electrotechnica et Informatica, 2020 Over the past years, many kinds of control strategies is proposed for doubly fed induction generators drives. Among them, direct power control (DPC) has gained more importance due to simple control structures and fast dynamic response. However, it has a
Habib BENBOUHENNI +2 more
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An enhanced artificial neural network with a shuffled complex evolutionary global optimization with principal component analysis [PDF]
, 2017 The classical Back-Propagation (BP) scheme with gradient-based optimization in training Artificial Neural Networks (ANNs) suffers from many drawbacks, such as the premature convergence, and the tendency of being trapped in local optimums.
Asanjan, AA +5 more
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Neural Network based Direct Torque Controller of SRM for EV Application [PDF]
E3S Web of Conferencesthe control aspects of the elecytric vehicle are presented in this paper. The electric car which is driven by a 6/4 Switched Reluctance Motor (SRM) powered by four battery banks is presented in this paper.
D Ganesh +3 more
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An ANN Model for Predicting the Compressive Strength of Concrete
Applied Sciences, 2021 An artificial neural network (ANN) model for predicting the compressive strength of concrete is established in this study. The Back Propagation (BP) network with one hidden layer is chosen as the structure of the ANN.
Chia-ju Lin, Nan-Jing Wu
semanticscholar +1 more source
Chemosensors, 2020 The drift of metal oxide semiconductor (MOX) chemical sensors is one of the most important topics in this field. The work aims to test the performance of MOX gas sensors over the aging process.
Marco Abbatangelo +4 more
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, 2011 Objective This study was conducted with sera from patients with rheumatoid arthritis (RA), systemic lupus erythematosus (SLE) and arthritis and lupus-like disease animal models to identify innate immune system-dependent and -independent ...
Burmester, G. +5 more
core +2 more sources
Heart disease prediction using machine learning algorithms [PDF]
MATEC Web of ConferencesHeart disease is among the conditions that people suffer from most frequently. Millions of people worldwide pass away each year as a result of it, making it one of the main causes of mortality.
Logabiraman Govardhan +4 more
doaj +1 more source