Search Results - (( data optimization method algorithm ) OR ( parameter adaptation case algorithm ))

Accuracy enhancement for zone mapping of a solar radiation forecasting based multi-objective model for better management of the generation of renewable energy by Ehteram M., Ahmed A.N., Fai C.M., Afan H.A., El-Shafie A.

Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman Smoother adaptive filter by ., Edwar Yazid, Mohd Shahir Liew, Setyamartana Parman, Velluruzhati

“…The first step is combining the forward and backward estimator in the original Volterra model; the second step is reformulating the Volterra model into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the kernel coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC). …”
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Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman smoother adaptive filter by Yazid, E., Liew, M.S., Parman, S., Kurian, V.J.

“…The first step is combining the forward and backward estimator in the original Volterra model; the second step is reformulating the Volterra model into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the kernel coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC). …”
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Self-Adaptive Autoreclosing Scheme usingI Artificial Neural Network and Taguchi's Methodology in Extra High Voltage Transmission Systems by Desta, Zahlay Fitiwi

“…In addition, Taguchi's methodology is employed in optimizing the parameters of each algorithm used for training, and in deciding the number of hidden neurons of the neural network. …”
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Adaptive Fast Orthogonal Search (FOS) algorithm for forecasting streamflow by Osman A., Afan H.A., Allawi M.F., Jaafar O., Noureldin A., Hamzah F.M., Ahmed A.N., El-shafie A.

“…Data handling; Forecasting; Nonlinear systems; Regression analysis; Religious buildings; Rivers; Stochastic systems; Stream flow; Fast orthogonal searches; Forecasting accuracy; Forecasting models; High dams; Optimization modeling; Optimization scheme; Pole zero cancellation; Streamflow forecasting; Stochastic models; algorithm; artificial intelligence; hydrological modeling; identification method; optimization; river basin; streamflow; Aswan Dam; Nile River…”

Neural network approach for global solar irradiance prediction at extremely short-time-intervals using particle swarm optimization algorithm by Aljanad A., Tan N.M.L., Agelidis V.G., Shareef H.

Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller by Zaridah, Mat Zain

“…This algorithm encode a potential solution to a specific problem on a simple chromosome like data structure and apply recombination operators to this structure to preserve critical information. …”
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Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems by Uvaraja, Vikneswary

“…The MTS algorithm is coded in ANSI-C language and tested on benchmark data from Mandl's Swiss Network and Mumford's larger data. …”
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks by Ukasyah bin Mahamod

Deep continual learning for predicting blast-induced overbreak in tunnel construction / He Biao by He , Biao

“…Third, the integration of metaheuristic algorithms further ascertains the optimal blasting parameters for overbreak minimization under specific rock sections. …”
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Time series modeling of water level at Sulaiman Station, Klang River, Malaysia by Galavi, Hadi

“…The estimation of parameters of the model is accomplished using the hybrid learning algorithm consisting of standard neural network backpropagation algorithm and least squares method. …”
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Inversion of 2D and 3D DC resistivity imaging data for high contrast geophysical regions using artificial neural networks / Ahmad Neyamadpour by Neyamadpour, Ahmad

“…In the case of 3D study of pole - dipole data, the gradient descent with momentum and an adaptive learning rate algorithm is found to be the most efficient paradigm. …”
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An adaptive flower pollination algorithm for minimizing software testing redundancy by M. N., Kabir, Ali, Jahan, Alsewari, Abdulrahman A., Kamal Z., Zamli

“…We tested the adaptive flower pollination algorithm on a number of experiments in software tests. …”
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

“…For its fast convergence and for its efficient search procedure, the self-adaptation is proposed in the parameters of the proposed hybrid algorithm. …”
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A hybrid SP-QPSO algorithm with parameter free adaptive penalty method for constrained global optimization problems by Fatemeh, D. B., Loo, C. K., Kanagaraj, G., Ponnambalam, S. G.

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Fuzzy adaptive emperor penguin optimizer for global optimization problems by Md Abdul, Kader

“…To alleviate this parameter tuning problem, an adaptive mechanism can be introduced in EPO. …”
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Performance study of adaptive filtering algorithms for noise cancellation of ECG signal by Islam S.Z., Islam S.Z., Jidin R., Ali M.A.M.

“…Moreover, nullifying AC and DC noises using the two adaptive algorithms-the LMS and the RLS from the ECG is a new study in biomedical science. …”

A self-adaptive agent-based simulation modelling framework for dynamic processes by Ling, Loo Yim, Dr.

“…Key parameters for dynamic processes of different domains were formulated for the construction of self-adaptive simulation algorithms and modelling. …”

LASSO-type estimations for threshold autoregressive and heteroscedastic time series models. by Muhammad Jaffri Mohd Nasir

“…A new algorithm of coordinate gradient descent (CGD) is developed to optimize the adaptive LASSO. …”
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An experimental study of a fuzzy adaptive emperor penguin optimizer for global optimization problem by Kader, Md. Abdul, Zamli, Kamal Z., Alkazemi, Basem Yousef

“…As the name suggests, FAEPO can adaptively tune the parameters f and l throughout the search based on three measures (i.e., quality, success rate, and diversity of the current search) via fuzzy decisions. …”
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