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Parameters identification of photovoltaic models using hybrid adaptive Nelder-Mead simplex algorithm based on eagle strategy
Fast accurate and reliable identification of photovoltaic (PV) model parameters based on measured current-voltage (IV) characteristic curves is significant for the analysis, evaluation and diagnosisExpand
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Intelligent fault diagnosis of photovoltaic arrays based on optimized kernel extreme learning machine and I-V characteristics
Fault diagnosis of photovoltaic (PV) arrays is important for improving the reliability, efficiency and safety of PV power stations, because the PV arrays usually operate in harsh outdoor environmentExpand
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An Intelligent Fault Diagnosis Approach for PV Array Based on SA-RBF Kernel Extreme Learning Machine
Abstract In this paper, based on an improved radial basis function (RBF) kernel extreme learning machine (ELM) optimized by simulated annealing algorithm, a novel intelligent fault diagnosis approachExpand
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Object tracking in the presence of shaking motions
TLDR
In this paper, we present a novel tracker framework for tracking shaking targets in the presence of shaking motion. Expand
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Parameters extraction of solar cell models using a modified simplified swarm optimization algorithm
TLDR
A modified simplified swarm optimization (MSSO) algorithm is presented for the single diode and double diode models by minimizing the least square error between the calculated and experimental data. Expand
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Random forest based intelligent fault diagnosis for PV arrays using array voltage and string currents
TLDR
In this paper, the random forest ensemble learning algorithm is explored for the detection and diagnosis of PV arrays early faults (including line-line faults, degradation, open circuit, and partial shading), which combines multiple learning algorithms to achieve a superior diagnostic performance. Expand
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Fault diagnosis for photovoltaic array based on convolutional neural network and electrical time series graph
TLDR
We propose a Convolutional Neural Network based photovoltaic array fault diagnosis method that automatically extracts suitable features representation from raw electrical time series graph, which eliminates the need of using artificially established features of data and then employs for photovaultaic fault diagnosis. Expand
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Accurate modeling of photovoltaic modules using a 1-D deep residual network based on I-V characteristics
TLDR
In this study, motivated by the high performance of fast developing deep learning techniques, we propose a novel black-box modeling method for the PV modules using a modified one-dimensional deep residual network (1-D ResNet) and measured I-V characteristic curves, which can predict a wholeI-V curve at a time for arbitrary operating conditions. Expand
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Implementation of 2D-DCT Based on FPGA with Verilog HDL
TLDR
This paper describes the FPGA implementation of a two dimensional Discrete Cosine Transform (8×8 point 2D-DCT) processor with Verilog HDL for application of image processing. Expand
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Temperature dependence of photogalvanic effect in GaAs/AlGaAs two-dimensional electron gas at interband and intersubband excitation
The linear (LPGE) and circular photogalvanic effects (CPGE), induced by interband (532 nm) and intersubband (1064 nm) excitation, have been investigated in a temperature range from 77 to 300 K inExpand
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