Search Results - (( panel optimization based algorithm ) OR ( parameter estimation learning algorithm ))

Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Nor Farizan, Zakaria, Mohd Mawardi, Saari

“…This paper presents the application of a recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) for optimizing the Deep Learning (DL) parameters to estimate the state of charge (SOC) of a battery for an electric vehicle in the real environment. …”
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Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohamad Fadhil, Abas, Bayuaji, Luhur

“…Therefore, it is crucial to assess the parameter of chaotic systems. To solve the issue of parameter estimation for a chaotic system, deep learning is utilized. …”
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Evaluation of genetic algorithm based solar tracking system for photovoltaic panels by Mashohor, Syamsiah, Samsudin, Khairulmizam, M. Noor, Amirullah, A. Rahman, Adi Razlan

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An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems by Muhammad Akmal, Remli, Mohd Saberi, Mohamad, Safaai, Deris, Sinnott, Richard O., Suhaimi, Napis

“…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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An improved scatter search algorithm for parameter estimation in large-scale kinetic models of biochemical systems by Remli, Muhammad Akmal, Mohamad, Mohd Saberi, Deris, Safaai, Sinnott, Richard, Napis, Suhaimi

“…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram by Faris Francis Singaram, Fareena

“…The parameters involved to estimate the mangrove age are differences feature selection and different supervised machine learning algorithm. …”
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Optimisation of tilt angles for fixed PV Panel via computational algorithm by Tang, Hong Wei

“…Additionally, the comparisons among three cases have been performed, which are Case 1: optimum annual energy generation based on optimal tilt angles, Case 2: optimum annual energy generation based on optimal tilt angle and azimuth angle faces South, and Case 3: optimum annual energy generation based on tilt angle according to location’s latitude coordinate and azimuth angle faces South. …”
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A Bayesian parameter learning procedure for nonlinear dynamical systems via the ensemble Kalman filter by Ur Rehman, M.J., Dass, S.C., Asirvadam, V.S.

“…Within the parameter learning steps, the MCMC algorithm requires to perform state estimation for which the target distribution is constructed by using the Ensemble Kalman filter (EnKF). …”
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A HYBRID COMPROMISE PROGRAMMING BASED GENETIC ALGORITHM FOR MULTI-OBJECTIVE OPTIMIZATION by Son, Ngo Tung

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Performance analyses of various photovoltaic power plant based on local spectral irradiances in Malaysia using genetic algorithm by Lim, Song Wei

“…The solar sites will be evaluated based on their annual average solar irradiation and the optimal tilt angle and orientation angle for solar panel at the solar sites can be estimated using the computational model. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…Then, the developed algorithm is implemented to estimate the parameters of the Lorenz system. …”
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Hybrid MPPT algorithm for mismatch photovoltaic panel application / Muhammad Iqbal Mohd Zakki by Mohd Zakki, Muhammad Iqbal

“…Closed-loop PID control system is implemented to optimize the control speed, and accuracy of the MPPT system, along with PSO-based auto-tuning algorithm dedicated for the PID controller to provide adaptability with diverse hardware setup. …”
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Optimization variation for multiple heuristic approaches in solar tracking by Fam D.F., Koh S.P., Tiong S.K., Chong K.H.

“…In this research, genetic algorithm is one of the optimization techniques used to maximize the performance of solar tracking system. …”

Parameter estimation in computational systems biology models: a comparative study of initialization methods in global optimization by Muhammad Akmal, Remli, Nor Syahidatul Nadiah, Ismail, Noor Azida, Sahabudin, Nor Bakiah, Abd Warif

“…Estimating parameters values is difficult and time-consuming process due to their highly nonlinear and huge number of kinetic parameters involved. …”
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RECURSIVE LEARNING ALGORITHMS ON RBF NETWORKS FOR NONLINEAR SYSTEM IDENTIFICATION by CATUR ANDRYANI, NUR AFNY

“…The thesis also try to investigate the influence of initialization of RBF weights parameters on the overall learning performance using random method and advanced unsupervised learning, such as clustering techniques, as a comparison. …”
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Optimization of a reliable grid-connected PV-based power plant by Rashid, Muhammad Mahbubur, Ali, Mohammad Yeakub, Hasan, Muhammad Hasibul, Mokthar, Nur Syamimi

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Optimization of stiffened panel fatigue life by using finite element analysis by Mazlan, Shahan

“…The multi-objective genetic algorithm which selects the design points based on Pareto optimal design combined with the adaptive multi-objective algorithm method which uses an optimal space-filling was shown to be efficient for time limitation and budget. …”
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Development of algorithm for single axis sun tracking system by Yi, L.Z., Singh, B.S.M., Ching, D.L.C., Jin, C.L.E.

“…In this paper, the focus is on the integration of solar tracking system with performance analyzer system through the development of an algorithm for optimizing the performance of SEGS. The proposed algorithm displays real-time processed data that would enable users to understand the trend of the SEGS output for maintenance prediction and optimization purposes. …”
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Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

“…Since extreme learning machine is a non-iterative estimation procedure, it is faster than gradient-based algorithms which are iterative. …”
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Neural network algorithm development for Ion Sensitive Field Effect Transistor (ISFET) sensor / Muhammad Nasrul Hakim Adenan by Adenan, Muhammad Nasrul Hakim

“…The ANN model performance can be optimized by altering certain parameters in the learning algorithm. The results show that the model is able to predict with 97% accuracy and has strong and precise estimation ability with R-factor of 91.55%.…”
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