Search Results - (( parameters estimation step algorithm ) OR ( java application mining algorithm ))

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    Kinetic Parameter Estimation in Alkylation of Benzene with 1-Decene through Hybrid Particle Swarm Optimization by Mohd Zulkefle, Nurul Farihah

    Published 2012
    “…Parameter estimation was performed by varying the initial guess of PSO algorithm which will conduct global search of the parameters. …”
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    Final Year Project
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    Semiparametric inference procedure for the accelarated failure time model with interval-censored data by Karimi, Mostafa

    Published 2019
    “…A computationally simple two-step iterative algorithm, called estimationapproximation algorithm, is introduced for estimating the parameters of the model on the basis of the rank estimators. …”
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    Thesis
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    PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah by Abdullah, Siti Muniroh

    Published 2017
    “…The parameter estimation step is concerned with the estimation of model parameters once the structure is known. …”
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    Thesis
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    ADAPTIVE LINEAR ALGORITHMS FOR POWER SYSTEM FUNDAMENTAL AND HARMONIC ESTIMATION by MUBARAK MOHMMED, HUSSAM ALHAJ

    Published 2015
    “…Hence, one of the objectives of this thesis is to address and enhance the introduced fundamental frequency adaptive filter method which was based on modified variable step size LMS (MVSS) algorithm using generalized square error normalized LMS algorithm. …”
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    Thesis
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    Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi by Dejamkhooy, Abdolmajid, Asefi, Sajjad

    Published 2018
    “…In the next step, the parameter identification as an optimization problem is solved by Moth-flame optimization, which is a novel nature-inspired heuristic algorithm. …”
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    Article
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    Parameter estimation of stochastic differential equation by Haliza Abd. Rahman, Arifah Bahar, Norhayati Rosli, Madihah Md. Salleh

    Published 2012
    “…Regression spline with Bayesian approach is considered in the first step of a two-step method in estimating the structural parameters for stochastic differential equation (SDE). …”
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    Article
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    Simultaneous Computation of Model Order and Parameter Estimation for System Identification Based on Gravitational Search Algorithm by Kamil Zakwan, Mohd Azmi, Pebrianti, Dwi, Zuwairie, Ibrahim, Shahdan, Sudin, Sophan Wahyudi, Nawawi

    Published 2015
    “…In this paper, a technique termed as Simultaneous Model Order and Parameter Estimation (SMOPE), which is specifically based on Gravitational Search Algorithm (GSA) is proposed to combine model order selection and parameter estimation in one process. …”
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    Conference or Workshop Item
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    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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    Article
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    Em Approach on Influence Measures in Competing Risks Via Proportional Hazard Regression Model by Elfaki, Faiz. A. M.

    Published 2000
    “…The Expectation Maximization (EM) was considered to obtain the estimate of the parameters. These estimates were then compared to the Newton-Raphson iteration method. …”
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    Thesis
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    Analysis of transient multiexponential signals using exponential compensation deconvolution by Jibia, Abdussamad Umar, Salami, Momoh Jimoh Eyiomika

    Published 2012
    “…A three-step procedure for the parameter estimation of transient multiexponential signals is proposed. …”
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    Article
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    SLOW DRIFT MOTIONS IDENTIFICATION OF FLOATING STRUCTURES USING TIME-VARYING INPUT -OUTPUT MODELS by YAZID, EDWAR

    Published 2015
    “…The first step is presenting the backward estimator and combined forward-backward estimator instead of the only forward estimator in the original input-output models; the second step is reformulating the input-output models into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the model 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) to form the PSO-KS, GA-KS and ABC-KS as estimation methods.…”
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    Thesis
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    Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence by S. S. S. , Ranjit

    Published 2011
    “…Block-matching algorithm is the most common technique applied in block-based motion estimation technique. …”
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    Book Chapter
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    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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    Conference or Workshop Item
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    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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    Final Year Project / Dissertation / Thesis
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    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

    Published 2015
    “…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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    Article
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    Combining Recursive Least Square and Principal Component Analysis for Assisted History Matching by Md. Anuar, Nurul Syaza

    Published 2014
    “…Even though RLS is a simple and effective method to estimate parameters, RLS have stability problem when number of parameters is high. …”
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    Final Year Project