Search Results - time estimation ((using algorithm) OR (((means algorithm) OR (learning algorithm))))

Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

“…The multi-class classification strategy is used to ensure quick estimation of the multi-class NN algorithms. …”
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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

“…The first research objective is to develop a new deep learning algorithm by a hybrid of DNN and K-Means Clustering algorithms for estimating the Lorenz chaotic system. …”
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Real time long range (LoRa) based indoor positioning system using Deep Gaussian Process (DGP) algorithm / Ng Tarng Jian by Ng, Tarng Jian

“…The study addresses challenges posed by signal fluctuations, non-line-of-sight propagation, and the need for continuous positioning estimation in dynamic environments. Through experimental evaluation and comparison of various machine learning algorithms, including Deep Gaussian Process (DGP) regression, the research demonstrates the effectiveness of DGPs in achieving precise single-point estimation, by keeping the mean absolute error to below 5 meters. …”
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Machine learning based-model to predict catalytic performance on removal of hazardous nitrophenols and azo dyes pollutants from wastewater by Khan M.S.J., Sidek L.M., Kumar P., Alkhadher S.A.A., Basri H., Zawawi M.H., El-Shafie A., Ahmed A.N.

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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm by Manoharan P., Ravichandran S., Kavitha S., Tengku Hashim T.J., Alsoud A.R., Sin T.C.

“…This study proposed an improved parameter estimation procedure for PEMFCs by using the GOOSE algorithm, which was inspired by the adaptive behaviours found in geese during their relaxing and foraging times. …”

Ensemble Dual Algorithm Using RBF Recursive Learning for Partial Linear Network by Md Akib, Afif, Saad, Nordin, Asirvadam, Vijanth

“…A new learning algorithm called the ensemble dual algorithm for estimating the mass-flow rate of the flow after leakage is proposed. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

“…While the firefly algorithm solution is superior, it has a higher time complexity compared to other algorithms used when there are more hidden layers and neurons. …”
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Software effort estimation using machine learning technique by Rahman, Mizanur, Roy, Partha Protim, Ali, Mohammad, Gonçalves, Teresa, Sarwar, Hasan

“…In order to better effectively evaluate predictions, this study recommends various machine learning algorithms for estimating, including k-nearest neighbor regression, support vector regression, and decision trees. …”
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The enhanced BPNN-NAR and BPNN-NARMA models for Malaysian aggregate cost indices with outlying data by Ahmad Kamaruddin, Saadi, Md Ghani, Nor Azura, Mohamed Ramli, Norazan

“…In theory, the most common training algorithm for Backpropagation algorithms leans on reducing ordinary least squares estimator (OLS) or more specifically, the mean squared error (MSE). …”
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Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli by Ahmad Kamaruddin, Saadi, Md. Ghani, Nor Azura, Mohamed Ramli, Norazan

“…Most of the previous studies seek to improve the learning algorithm of backpropagation neural networks by adapting the M-estimators predominantly. …”
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Using Machine Learning Algorithms to Estimate the Compressive Property of High Strength Fiber Reinforced Concrete by Dai, L., Wu, X., Zhou, M., Ahmad, W., Ali, M., Sabri, M.M.S., Salmi, A., Ewais, D.Y.Z.

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Creating Air Temperature Models for High-Elevation Desert Areas Using Machine Learning by Forooshani, Massoud, Gegov, Alexander, Pepin, Nick, Adda, Mo

“…This is particularly important in high-elevation regions. In this study, we estimate Ta in the high-elevation desert zone of Kilimanjaro (>4500m) using four models (five models including the benchmark model) with unique sets of inputs using five machine learning (ML) algorithms. …”
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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer by Most. Julakha, Jahan Jui

“…his thesis implements a novel nature-inspired metaheuristic optimization algorithm, namely the modified Multi-Verse Optimizer (mMVO) algorithm, to identify the continuous-time model of Hammerstein system. …”
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Interaction effect of process parameters and Pd-electrocatalyst in formic acid electro-oxidation for fuel cell applications: Implementing supervised machine learning algorithms by Hossain S.K.S., Ali S.S., Rushd S., Ayodele B.V., Cheng C.K.

Predictive modelling of nanofluids thermophysical properties using machine learning by Olanrewaju, Alade Ibrahim

“…This thesis aimed to develop machine learning algorithms to estimate the thermophysical properties of commonly used nanofluids. …”
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Adaptive complex neuro-fuzzy inference system for non linear modeling and time series prediction by Shoorangiz, Mohammadreza

“…Second part has been done by proposing a novel learning rule containing genetic algorithm, Levenberg-Marquardt technique and least square estimation. …”
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An improved machine learning model of massive Floating Car Data (FCD) based on Fuzzy-MDL and LSTM-C for traffic speed estimation and prediction by Ahanin, Fatemeh

“…This thesis uses Fuzzy C-Mean and concept of MDL to constitute patterns and estimate the missing traffic state based on n previous states. …”
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Fault classification in transmission line using single layer feed-forward network trained by extreme learning machine / Muhamad Azfar Abd Ghafar by Abd Ghafar, Muhamad Azfar

“…In this paper, the energy and mean features are been selected. The SLFN is trained by an algorithm named Extreme Learning Machine (ELM). …”
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Fault classification in transmission line using single layer feed-forward network trained by extreme learning machine / Muhamad Azfar Abd Ghafar by Abd Ghafar, Muhamad Azfar

“…In this paper, the energy and mean features are been selected. The SLFN is trained by an algorithm named Extreme Learning Machine (ELM). …”
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A review article on software effort estimation in agile methodology by Sudarmaningtyas, Pantjawati, Rozlina, Mohamed

“…The results showed the top three estimation that is applied in Agile, are machine learning (37%), Expert Judgement (26%), and Algorithmic (21%). …”
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