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  1. 1
    Simulated Kalman Filter algorithms for solving optimization problems

    Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

    Published 2019
    “…In principle, the optimization problem is regarded as a state estimation process. Each agent acts as a Kalman filter and finds solution to the optimization problem using a standard Kalman Filter framework which comprises of prediction, simulated measurement, and estimation phase that uses the best-so-far solution as a reference. …”
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  2. 2
    Estimation of the denitrification in the lower Mississippi Valley

    Estimation of the denitrification in the lower Mississippi Valley by Saleh, Abdul Razak

    Published 2001
    “…The CREAMS denitrification algorithm was modified to account for the high soil moisture conditions by incorporating a water function.The average annual denitrification value simulated by using modified algorithm was higher than the one predicted by CREAMS algorithm.This result is expected because the modified algorithm uses a water function to reflect the degree of soil saturation.…”
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  3. 3
    Implementation of a modified incremental conductance MPPT algorithm with direct control based on a fuzzy duty cycle change estimator using dSPACE

    Implementation of a modified incremental conductance MPPT algorithm with direct control based on a fuzzy duty cycle change estimator using dSPACE by Radjai, T., Rahmani, L., Mekhilef, Saad, Gaubert, J.P.

    Published 2014
    “…A fuzzy logic estimator (FLE) is used to estimate the new duty cycle used to track the PV array maximum power point. …”
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  4. 4
    Hierarchical Bayesian estimation for stationary autoregressive models using reversible jump MCMC algorithm

    Hierarchical Bayesian estimation for stationary autoregressive models using reversible jump MCMC algorithm by Suparman, S., Rusiman, Mohd Saifullah

    Published 2018
    “…The performance of the algorithm is tested by using simulated data. The test results show that the algorithm can estimate the order and coefficients of the autoregressive model very well. …”
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  5. 5
    Simulated Kalman Filter: A Novel Estimation-based Metaheuristic Optimization Algorithm

    Simulated Kalman Filter: A Novel Estimation-based Metaheuristic Optimization Algorithm by Zuwairie, Ibrahim, Nor Hidayati, Abd Aziz, Nor Azlina, Ab. Aziz, Saifudin, Razali, Mohd Saberi, Mohamad

    Published 2016
    “…An agent in the population finds solution to optimization problem using a standard Kalman Filter framework, which includes a simulated measurement process and a best-so-far solution as a reference. …”
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  6. 6
    Estimation-based Metaheuristics: A New Branch of Computational Intelligence

    Estimation-based Metaheuristics: A New Branch of Computational Intelligence by Nor Hidayati, Abd Aziz, Zuwairie, Ibrahim, Saifudin, Razali, Nor Azlina, Ab. Aziz

    Published 2016
    “…Inspired by the estimation capability of Kalman Filter, Simulated Kalman Filter, SKF, uses a population of agents to make estimations of the optimum. …”
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  7. 7
    Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor

    Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor by Adilah, Abdul Ghapor

    Published 2017
    “…As for the multiple outliers, a clustering algorithm is considered and a dendogram to visualise the clustering algorithm is used. …”
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  8. 8
    Liquid Flow Enhancement using Natural Polymeric Additives: Effect of Concentration

    Liquid Flow Enhancement using Natural Polymeric Additives: Effect of Concentration by Abdulbari, Hayder A., Fiona Ling, Wang Ming

    Published 2016
    “…An agent in the population finds solution to optimization problem using a standard Kalman Filter framework, which includes a simulated measurement process and a best-so-far solution as a reference. …”
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  9. 9
    The compact genetic algorithm for likelihood estimator of first order moving average model

    The compact genetic algorithm for likelihood estimator of first order moving average model by Al-Dabbagh, R.D., Baba, M.S., Mekhilef, Saad, Kinsheel, A.

    Published 2012
    “…Recently Genetic Algorithms (GAs) have frequently been used for optimizing the solution of estimation problems. …”
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  10. 10
    Performance study of direction of arrival (DOA) estimation algorithms for linear array antenna

    Performance study of direction of arrival (DOA) estimation algorithms for linear array antenna by Islam, Md. Rafiqul, Adam, Ibrahim A. H.

    Published 2009
    “…The analysis is based on linear array antenna and the calculation of the pseudospectra function of the estimation algorithms. Matlab is used for simulating the algorithms.…”
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  11. 11
    Enhancing the cuckoo search with levy flight through population estimation

    Enhancing the cuckoo search with levy flight through population estimation by Mohd Nawi, Nazri, Shahuddin, Shah Liyana, Rehman, Muhammad Zubair, Khan, Abdullah

    Published 2016
    “…This paper proposed the use of population estimation in a new meta-heuristic called Cuckoo search (CS) algorithm to minimize the training error, achieve fast convergence rate and to avoid local minimum problem. …”
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  12. 12
    Simulation of shortest path using a-star algorithm / Nurul Hani Nortaja

    Simulation of shortest path using a-star algorithm / Nurul Hani Nortaja by Nurul Hani , Nortaja

    Published 2004
    “…The steps to calculate a shortest path using A • algorithm is shown by using appropriate examples and related figures. …”
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  13. 13
    Enhancing simulated kalman filter algorithm using current optimum opposition-based learning

    Enhancing simulated kalman filter algorithm using current optimum opposition-based learning by Kamil Zakwan, Mohd Azmi, Zuwairie, Ibrahim, Pebrianti, Dwi, Mohd Falfazli, Mat Jusof, Nor Hidayati, Abdul Aziz, Nor Azlina, Ab. Aziz

    Published 2019
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  14. 14
    Identification of hammerstain model using stochastic perturbation simultaneous approximation

    Identification of hammerstain model using stochastic perturbation simultaneous approximation by Nurriyah, Mohd Noor

    Published 2016
    “…However, the system order assumed to be known For handling it, piecewise-linear function are used as a tool to approximate the unknown non-linear function. …”
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  15. 15
    COMPARATIVE ANALYSIS OF OPTICAL FLOW MEASUREMENT TECHNIQUE

    COMPARATIVE ANALYSIS OF OPTICAL FLOW MEASUREMENT TECHNIQUE by NIZAM AKBAR, AMAR NAZMI ZULKARNAIN

    Published 2017
    “…The four algorithms were used to estimate the flow rate where five simulations with five different flow rates were measured in order to determine the accuracy of each algorithm. …”
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  16. 16
    Simulation-Based Power Estimation for High Throughput SHA-256 Design on Unfolding Transformation

    Simulation-Based Power Estimation for High Throughput SHA-256 Design on Unfolding Transformation by Shamsiah, Suhaili, Norhuzaimin, Julai, Asrani, Lit, Maimun Binti, Huja Hussin, Mohamad Faizrizwan bin, Mohd Sabri

    Published 2022
    “…The algorithms are successfully designed using the Altera Quartus II platform. …”
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  17. 17
    Predictive modelling of machining parameters of S45C mild steel

    Predictive modelling of machining parameters of S45C mild steel by Abbas, Adnan Jameel

    Published 2016
    “…The simulation results of GA, PSO and AIS showed that the GA1 algorithm which used the first main temperature objective function gives the best temperature value (35. 7 0C) compared with other algorithms, followed by PSO1 (70.2 0C), then AIS1 (112.8 0C). …”
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  18. 18
    A multiobjective simulated Kalman filter optimization algorithm

    A multiobjective simulated Kalman filter optimization algorithm by A. Azwan, A. Razak, Mohd Falfazli, Mat Jusof, Ahmad Nor Kasruddin, Nasir, Mohd Ashraf, Ahmad

    Published 2018
    “…It is a further enhancement of a single-objective Simulated Kalman Filter (SKF) optimization algorithm. …”
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  19. 19
    Estimation of Response Transfer Functions of Offshore Structures Using the Time-Varying ARX Model

    Estimation of Response Transfer Functions of Offshore Structures Using the Time-Varying ARX Model by Yazid, Edwar, Liew, M. S., Parman, Setyamartana, Kurian, V.J.

    Published 2013
    “…Here, we outline a practical algorithm for TVARX model which uses expectation-maximization (EM) algorithm based on Kalman smoother to generate the transfer function. …”
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  20. 20
    Nlfxlms and thf-nlfxlms algorithms for wiener-hammerstein nonlinear active noise control

    Nlfxlms and thf-nlfxlms algorithms for wiener-hammerstein nonlinear active noise control by Srazhidinov, Radik

    Published 2016
    “…In recent works, it was shown that the SEF can be approximated using tangential hyperbolic function (THF) for Hammerstein and Wiener NLFXLMS algorithms, such that the degree of nonlinearity can be estimated using modelling approach. …”
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