Search Results - (( java implementation phase algorithm ) OR ( parameter reflection model algorithm ))
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…All the algorithm for the engine has been developed by using Java script language. …”
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Evaluation of lightning current and ground reflection factor using measured electromagnetic field
Published 2014“…In this paper, an inverse procedure algorithm is proposed to evaluate lightning return stroke current wave shapes at different heights along a lightning channel, as well as the ground reflection factor using measured electromagnetic fields at an observation point while the current model can be set for different models based on the general form of the engineering current models. …”
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Estimation of photovoltaic models using an enhanced Henry gas solubility optimization algorithm with first-order adaptive damping Berndt-Hall-Hall-Hausman method
Published 2024“…Then in terms of methodology, the Enhanced Henry Gas Solubility Optimization (EHGSO) algorithm is combined with the Sine-Cosine mutualism phase of Symbiotic Organisms Search (SOS) for efficiently estimating the unknown parameters of PV models. …”
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Automatic control of flotation process using computer vision
Published 2015“…Finally, a control strategy implementing the developed froth model and prediction system was introduced for direct optimization of metallurgical parameters. …”
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Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar
Published 2006“…Although from human logical thinking, the route can be generated easily but the calculation of checking the route whether it is optimal route or not is difficult and will take long time to be implemented. This research study with the development of the Optimal Route Checking Using Genetic Algorithm system should solve this scenario. …”
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Hybrid optimization approach to estimate random demand
Published 2012“…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
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New completion time algorithms for sequence based scheduling in multiproduct batch processes using matrix
Published 2008“…All these parameters directly or indirectly affect the makespan, i.e. completion time of a batch process. …”
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Modeling financial environments using geometric fractional Brownian motion model with long memory stochastic volatility
Published 2018“…All parameters involved in the developed model are estimated by using innovation algorithm. …”
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Fitting time-varying coefficients SEIRD model to Covid-19 cases in Malaysia
Published 2023“…However, this feature leads to an increasing number of unknowns needed to be solved to fit the model with the actual data. Several optimization algorithms under Python’s LMfit package, such as Levenberg-Marquardt, Nelder-Mead, Trust-Region Reflective and Sequential Linear Squares Programming; are employed to estimate the related parameters, in such that the numerical solution of the ODEs will fit the data with the slightest error. …”
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Modified word representation vector based scalar weight for contextual text classification
Published 2024“…For this experiment, the modified word vectors serve as input to train a Machine Learning (ML) model for the text classification process, aiming for the developed ML model to have a significantly smaller parameter count. …”
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An intermediate significant bit (ISB) watermarking technique using neural networks
Published 2016“…This paper considers this issue to determine the threshold values of these two parameters in reflecting the amount of strength and weakness of the watermarking algorithms. …”
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Oil palm maturity classifier using spectrometer and machine learning
Published 2021“…The model was validated by predicting ripeness level for another FFB reflectance dataset. …”
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Prediction and investigation of surface response in high speed end milling of Ti-6Al-4V and optimization by genetic algorithm
Published 2010“…The developed quadratic prediction model on surface roughness was coupled with the genetic algorithm to optimize the cutting parameters for the minimum surface roughness.…”
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Ocean Colour Remote Sensing Of Case 2 Waters Using An Optimised Neural Network
Published 2016“…Model NN dan parameter latihan dioptimumkan dengan input yang dipilih berdasarkan analisis korelasi (CA) dan analisis komponen utama (PCA). …”
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Channel Modeling and Direction-of-Arrival Estimation in Mobile Multiple-Antenna Communication Systems
Published 2005“…Two main topics are studied, channel modeling and estimation of channel parameters. This thesis first describes the modeling of the reflected power distribution due to the scatterers close to the mobile stations, in terms of the received signal azimuth at the base station with multiple-antenna. …”
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An intermediate significant bit (ISB) watermarking technique using neural networks
Published 2016“…This paper considers this issue to determine the threshold values of these two parameters in reflecting the amount of strength and weakness of the watermarking algorithms. …”
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Identification of Continuous-Time Hammerstein Systems by Simultaneous Perturbation Stochastic Approximation
Published 2016“…The results demonstrate that the proposed algorithm is useful to obtain accurate models, even for high-dimensional parameter identification.…”
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