Search Results - (( based estimation method algorithm ) OR ( parameter solution learning algorithm ))

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

“…The most popular method to solve parameter estimation problem is using optimization algorithm that easily trap to local minima and poor in exploitation to find the good solutions. …”
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RECURSIVE LEARNING ALGORITHMS ON RBF NETWORKS FOR NONLINEAR SYSTEM IDENTIFICATION by CATUR ANDRYANI, NUR AFNY

“…This thesis proposes derivative free learning, using finite difference, methods for fixed size RBF network in comparison to gradient based learning for the application of system identification. …”
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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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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

“…Consequently, the study involved exploiting optimization techniques to enhance the training artificial intelligence algorithm for streamflow forecasting from a gradient-based to a stochastic population-based approach in several aspects, including solution quality, computational effort, and parameter sensitivity on streanflow in Johor, Malaysia. …”
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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer by Most. Julakha, Jahan Jui

“…The numerical and experimental results also showed that both Hammerstein model subsystems are defined effectively using the mMVO-based method, particularly in quadratic output estimation error and a differentiation parameter index. …”
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Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources by Kumar, A., Ridha, S., Narahari, M., Ilyas, S.U.

“…However, machine and deep learning methods have higher accuracy but rely heavily on the quality and amount of training data, and the solution may become inconclusive if data is sparse. …”
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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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Estimation of Examinees' Ability Through Computer Adaptive Testing Based on Neural Network Approach by Kazemi, Azam

“…In the second phase, estimation of examinees’ ability has been obtained with multi-layer feed forward neural network with back propagation algorithm. …”
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REGION-BASED ADAPTIVE DISTRIBUTED VIDEO CODING CODEC by ABDELRAHMAN ELAMIN, ABDELRAHMAN ELAMIN

“…However, the rate cannot be exactly calculated at the encoder, instead it can only be estimated. This work also prbposes a feedback-free region-based adaptive DVC solution in pixel domain based on machine learning approach to estimate the side information. …”
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Application of boundary-fitted convolutional neural network to simulate non-Newtonian fluid flow behavior in eccentric annulus by Kumar, A., Ridha, S., Ilyas, S.U., Dzulkarnain, I., Pratama, A.

“…The algorithms also explain the effect of geometric and rheological parameters on the fluid flow attributes. …”
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Support vector machine and its applications for linear and nonlinear regression in the presence of outliers of high dimensional data by Sleabi, Waleed Dhhan

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A harmony search-based learning algorithm for epileptic seizure prediction by Kee, Huong Lai, Zainuddin, Zarita, Ong, Pauline

“…In this work, the harmony search algorithm is employed to find the optimal solution for both synaptic weight values and bias terms in the learning of wavelet neural network. …”
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Semiparametric inference procedure for the accelarated failure time model with interval-censored data by Karimi, Mostafa

“…The rank-based methods, estimating algorithms, and resampling techniques that are developed do not involve the difficulties of the existing estimating procedures. …”
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On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B., Alsewari, Abdulrahman A.

“…In doing so, this paper reviews two existing parameter free optimization algorithms involving Teaching Learning Based Optimization (TLBO) and Fruitfly Optimization Algorithm (FOA) in an effort to promote their adoption for CIT.…”
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Accelerated mine blast algorithm for ANFIS training for solving classification problems by Mohd Salleh, Mohd Najib, Hussain, Kashif

“…ANFIS accuracy depends on the parameters it is trained with. Keeping in view the drawbacks of gradients based learning of ANFIS using gradient descent and least square methods in two-pass learning algorithm, many have trained ANFIS using metaheuristic algorithms. …”
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A modified generalized RBF model with EM-based learning algorithm for medical applications by Ma, Li Ya, Abdul Rahman, Abdul Wahab, Quek, Chai

“…An EM-based training algorithm is also introduced, which uses fewer parameters compared to some classical supervised learning methods. …”
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Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence by S. S. S. , Ranjit

“…There are several block-matching algorithm based on block-based motion estimation techniques have been developed. …”
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Advances of metaheuristic algorithms in training neural networks for industrial applications by Chong H.Y., Yap H.J., Tan S.C., Yap K.S., Wong S.Y.

Optimized PV-Battery Systems using Backtracking Search Algorithm for Sustainable Energy Solutions by Abdolrasol M.G.M., Jern Ker P., Hannan M.A., Tiong S.K., Ayob A., Almadani J.F.S.

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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

“…The improved algorithm is based on hybridization of quasi opposition-based learning in enhanced scatter search (QOBLESS) method. …”
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