Search Results - (( developing function using algorithm ) OR ( learning application solar algorithm ))
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Artificial intelligent integrated into sun-tracking system to enhance the accuracy, reliability and long-term performance in solar energy harnessing
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Final Year Project / Dissertation / Thesis -
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Micro-Crack Detection Of Solar Cells Featuring Adaptive Anisotropic Diffusion Filter And Semi-Supervised Support Vector Learning
Published 2014“…In this thesis, a machine vision-based application for detecting micro-crack in an electro luminescence (el) image of solar cell is presented. …”
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Investigating photovoltaic solar power output forecasting using machine learning algorithms
Published 2023“…It is concluded that ANN is the most reliable and applicable algorithm for PV solar power output forecasting. � 2022 The Author(s). …”
Article -
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Analysis of photovoltaic panels performance and power output forecasting based on optimized deep learning technique / Muhammad Naveed Akhter
Published 2021“…Moreover, Salp Swarm Algorithm (SSA) is used to tune the hyperparameters of the developed deep learning method on an annual basis over four years to enhance its forecasting accuracy and is compared with RNN-LSTM, GA-RNN-LSTM, and PSO-RNN-LSTM. …”
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Thesis -
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Fuzzy based BSA optimization for maximum power point tracking controller performance evaluation
Published 2023Conference Paper -
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Intelligent irrigation system energized by solar photovoltaic power
Published 2023text::Final Year Project -
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A comparative analysis of LSTM, SVM, and GSTANN models for enhancing solar power prediction
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Proceeding Paper -
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Recent advances and future challenges of solar power generation forecasting
Published 2024“…A significant obstacle lies in the deficiency of real-world application for large-scale specifically for solar power generation forecasting. …”
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Article -
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A block cipher based on genetic algorithm
Published 2016“…In many algorithms which are based on the genetic algorithm approach, diffusion properties using crossover and mutation function are being generated to produce a secure data transmission. …”
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Thesis -
12
Computing the autopilot control algorithm using predictive functional control for unstable model
Published 2009“…This paper discusses the computing development of a control algorithm using Predictive Functional Control (PFC) for model-based that having one or more unstable poles. …”
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Conference or Workshop Item -
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An improved teaching-learning-based optimization for extreme learning machine in floating photovoltaic power forecasting
Published 2025“…This study presents an improved teaching-learning-based optimization algorithm with extreme learning machine for floating photovoltaic power forecasting. …”
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Short-Term forecasting of floating photovoltaic power generation using machine learning models
Published 2024“…This study investigates the application of machine learning models for predicting FPV power generation using data from the Universiti Malaysia Pahang Al-Sultan Abdullah (UMPSA) solar installation, which has a capacity of 157.20 kWp. …”
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Logic Programming In Radial Basis Function Neural Networks
Published 2013“…I used different types of optimization algorithms to improve the performance of the neural networks. …”
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Thesis -
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Development and applications of metaheuristic algorithms in engineering design and structural optimization / Ali Sadollah
Published 2013“…Metaheuristic algorithms have been extensively used in numerous domains especially in engineering. …”
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Thesis -
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Chebyshev approximation of discrete polynomials and splines
Published 2004“…These algorithms use either cubic splines or Lagrange polynomials to construct the approximation function. …”
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Thesis -
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Chebyshev approximation of discrete polynomials and splines
Published 2004“…These algorithms use either cubic splines or Lagrange polynomials to construct the approximation function. …”
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Shunt active power filter using hybrid fuzzy-proportional and crisp-integral control algorithms for total harmonic distortion improvement
Published 2016“…Additionally, the proposed HFP+CI voltage control algorithm has resulted fastest response time; it is 94% faster than using the Fuzzy-PI voltage control algorithm and 6% faster than using the Crisp-PI voltage control algorithm.Hence, it can be concluded that the proposed algorithms have successfully performed their functions by effectively enhancing the operation of the SAPF.…”
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