Search Results - (( simulation optimization means algorithm ) OR ( data estimation methods algorithm ))

System identification using Extended Kalman Filter by Alias, Ahmad Hafizi

“…Besides, Extended Kalman Filter (EKF) algorithm was selected in this project as an algorithm for offline estimation data purposes. …”
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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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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.

“…The statistical error estimation exhibits a mean absolute error of 11.5, and root mean squared error of 0.87. …”
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Extraction of photovoltaic module model's parameters using an improved hybrid differential evolution/electromagnetism-like algorithm by Muhsen D.H., Ghazali A.B., Khatib T., Abed I.A.

Robust estimation methods for fixed effect panel data model having block-concentrated outliers by Abu Bakar @ Harun, Nor Mazlina

“…The Ordinary Least Squares (OLS) is the commonly used method to estimate the parameters of fixed effect panel data model. …”
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Combining Recursive Least Square and Principal Component Analysis for Assisted History Matching by Md. Anuar, Nurul Syaza

“…Next, using simulated data together with historical data, objective function will be computed. …”
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Entropy in portfolio optimization / Yasaman Izadparast Shirazi by Yasaman Izadparast, Shirazi

“…Details of the algorithms which include entropy estimation which would enhance the application of a proper risk measure like entropy, is provided. …”
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Tracking moving targets in wireless sensor networks using extended diffusion strategies of distributed Kalman filter by Solouk, Vahid, Taghizadeh, Hamid, Moghanjoughi, Ayyoub Akbari, Razm, S. K.

“…The proposed algorithms provide precise state estimates in a moment as global state estimates using various updates at each step. …”
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A Subspace Approach for Extracting Signals Highly Corrupted by Colored Noise by Yusoff, Mohd Zuki, Hussin, Fawnizu Azmadi

“…SNR values can be as low as -10 dB in real clinical environments. The simulation results produced by the post-modified SSA2 algorithm, show a higher degree of consistencies in detecting the VEP's P100, P200, and P300 peaks, in comparisons to the pre-modified SSA1 method. …”
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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

“…The fault identification prior to reclosing is based on optimized artificial neural network associated with three training algorithms, namely, Standard Error Back-Propagation, Levenberg Marquardt and Resilient Back-Propagation algorithms. …”
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Enhancing time series prediction with Hybrid AFSA-TCN: A unified approach to temporal data and optimization by Nur Alia Shahira, Mohd Zaidi, Zuriani, Mustaffa, Muhammad Arif, Mohamad

“…Time series data, with its sequential dependencies presents a unique challenge for traditional machine learning methods such as Random Forest (RF), Support Vector Machines (SVM), and Decision Trees (DT), which often struggle to capture temporal patterns effectively. …”
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Development of robust procedures for partial least square regression with application to near infrared spectral data by Silalahi, Divo Dharma

“…The results of the simulation study and two NIR spectral data sets, namely the NIR spectral of oil palm (Elaeis guineensis Jacq.) fresh and dried ground fruit mesocarp, show that all the proposed methods are superior compared to the existing methods in this study.…”
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The classification of wink-based eeg signals by means of transfer learning models by Jothi Letchumy, Mahendra Kumar

“…It was demonstrated from the simulation investigation that the CWT model could yield a better signal transformation amongst the preprocessing algorithms. …”
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Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

“…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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Pid-aco vibration controller with magnetorheological damper for wind turbine tower / Mahmudur Rahman by Mahmudur , Rahman

“…The FDM dynamic model is found 100% fit to estimated data with reasonably good value of mean squared error (MSE) and Cross Signature Assurance Criterion (CSAC). …”
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Impact of evolutionary algorithm on optimization of nonconventional machining process parameters by B V, Raghavendra, R Annigiri, Anandkumar, Srikatamurthy, JS

“…Using a Python environment, three evolutionary algorithms such as, Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Firefly Algorithm (FA), were simulated to evaluate their effectiveness in minimizing surface roughness (Ra). …”
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Determining optimal location of static VAR compensator by means of genetic algorithm by Karami, Mahdi, Mariun, Norman, Ab Kadir, Mohd Zainal Abidin

“…This method is employed to optimize the stability of power system by means of maximizing distance to collapse point. …”
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Studying the Effect of Training Levenberg Marquardt Neural Network by Using Hybrid Meta-Heuristic Algorithms by Abubakar, A., Khan, A., Nawi, N.M., Rehman, M.Z., Teh, Y.W., Chiroma, H., Herawan, T.

“…The simulation results show that the APSO-LM algorithm shows better performance than baseline algorithms in terms of convergence speed and Mean Squared Error (MSE).…”
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Efficient Time-Varying q-Parameter Design for q-Incremental Least Mean Square Algorithm with Noisy Links by Arif, M., Khan, S.S., Qadri, S.S.U., Naseem, I., Moinuddin, M.

“…The analytical results are validated through simulation. Finally, extensive simulations have been done to evaluate the performance of the proposed algorithm for various choices of optimal q-values. …”
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Optimalisation of a job scheduler in the grid environment by using fuzzy C-mean by Lorpunmanee, Siriluck, Abdullah, Abdul Razak

“…Simulation runs demonstrate that our algorithm leads to better results than the traditional algorithms for scheduling policies used in Grid environment.…”
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