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Inspecting Distortion in the Power Amplifiers with the aid of Neural Networks
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Inspecting Distortion in the Power Amplifiers with the aid of Neural Networks
2020 22nd International Conference on Advanced Communication Technology (ICACT), Vol. 2020, 16 Şubat 2020, s. 448, ISSN: 17389445
AYGÜN SERCAN,KOUHALVANDİ LİDA,GÜNEŞ ECE OLCAY,ÖZOĞUZ İSMAİL SERDAR
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Dynamic security enhancement of power systems via population based optimization methods integrated with artificial neural networks
Fen Bilimleri Enstitüsü, İstanbul Teknik Üniversitesi, 2015
CAVİT FATİH KÜÇÜKTEZCAN
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A probabilistic dynamic security assessment of large power systems using artificial neural networks
Fen Bilimleri Enstitüsü, İstanbul Teknik Üniversitesi, 2017
SEVDA JAFARZADEH
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Aplications of neural networks to nuclear power systems
Fen Bilimleri Enstitüsü, Hacettepe Üniversitesi, 1993
MEHMET CEYHAN
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Power optimization, network coding and decision fusion in multi-access relay networks
Mühendislik ve Fen Bilimleri Enstitüsü, Sabancı Üniversitesi, 2014
KAYHAN ERİTMEN
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MODELING OF RF POWER AMPLIFIERS USING MEMRISTOR BASED ARTIFICIAL NEURAL NETWORKS
Fen Bilimleri Enstitüsü, İstanbul Teknik Üniversitesi, 2022
MUSTAFA CİHAD TORUN
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Forecasting of renewable power generation in European markets via long short-term memory neural networks
Lisansüstü Eğitim Enstitüsü, Bahçeşehir Üniversitesi, 2022
ALPER ÜNAL
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Short-mid-term solar power prediction by using artificial neural networks
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Machine Learning-Based Error Correction Codes and Communication Protocols for Power Line Communication: An Overview
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A power based integrated protection scheme for active distribution networks against asymmetrical faults
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A decentralized emergency control scheme for power System transient stability enhancement based on model predictive control
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Component wide and plant wide monitoring by neural networks for Borssele nuclear power plant
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Dynamic security assessment of a power system based on Probabilistic Neural Networks
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An Online Dynamic Security Assessment in Power Systems Using RBF-R Neural Networks
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A novel integrated framework for real-time prediction of transient instabilities in power systems with their severity levels using deep learning
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