Search Results - (( java application sensor algorithm ) OR ( series estimation using algorithm ))

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

“…In this thesis, we propose Least Absolute Shrinkage and Selection Operator (LASSO) type estimators to perform simultaneous parameter estimation and model selection for five specific univariate and multivariate time series models, and develop several algorithms to compute these estimators. …”
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Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…The process begins through the monitoring of plants using sensors connected to the Arduino device. Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. …”
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Machine Learning Regression Approach for Estimating Energy Consumption of Appliances in Smart Home by Husin N.S.I.M., Mostafa S.A., Jaber M.M., Gunasekaran S.S., Al-Shakarchi A.H., Abdulsattar N.F.

“…This paper attempts to use machine learning algorithms to estimate the energy consumption of appliances in a smart home environment. …”

Evaluation of a spacecraft attitude and rate estimation algorithm by Abdullah, Mohammad Nizam Filipski, Varatharajoo, Renuganth

“…Practical implications: Because the simulation set‐up is clearly stated, the results of this evaluation can be used as a benchmark for other estimation algorithms. …”
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Unscented Kalman filter for noisy multivariate financial time-series data by Jadid Abdulkadir, S., Yong, S.-P.

“…In this paper, we consider the process of applying Unscented Kalman Filtering algorithm to multivariate financial time series data to determine if the algorithm could be used to smooth the direction of KLCI stock price movements using five different measurement variance values. …”
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Unscented Kalman filter for noisy multivariate financial time-series data by Jadid Abdulkadir, S., Yong, S.-P.

“…In this paper, we consider the process of applying Unscented Kalman Filtering algorithm to multivariate financial time series data to determine if the algorithm could be used to smooth the direction of KLCI stock price movements using five different measurement variance values. …”
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Unscented Kalman filter for noisy multivariate financial time-series data by Jadid Abdulkadir, S., Yong, S.-P.

“…In this paper, we consider the process of applying Unscented Kalman Filtering algorithm to multivariate financial time series data to determine if the algorithm could be used to smooth the direction of KLCI stock price movements using five different measurement variance values. …”
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Unscented Kalman filter for noisy multivariate financial time-series data by Jadid Abdulkadir, S., Yong, S.-P.

“…In this paper, we consider the process of applying Unscented Kalman Filtering algorithm to multivariate financial time series data to determine if the algorithm could be used to smooth the direction of KLCI stock price movements using five different measurement variance values. …”
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Unscented Kalman filter for noisy multivariate financial time-series data by Jadid Abdulkadir, S., Yong, S.-P.

“…In this paper, we consider the process of applying Unscented Kalman Filtering algorithm to multivariate financial time series data to determine if the algorithm could be used to smooth the direction of KLCI stock price movements using five different measurement variance values. …”
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Properties of selected garma models and their estimation procedures by Ramiah Pillai, Thulasyammal

“…The focus of this study is to investigate the properties specically the variance and autocovariance of the GARMA (p; q; ±1; ±2) models. We also study the estimation of the parameters of these models. Evaluation of the performance of two estimators based on the Hannan-Rissanen Algorithm Estimator (HRA) and the Whittle's Estimator (WE) through a series of simulation studies have been conducted in this thesis. …”
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Parameter estimation in double exponential smoothing using genetic algorithm / Foo Fong Yeng, Lau Gee Choon and Zuhaimy Ismail by Foo, Fong Yeng, Lau, Gee Choon, Ismail, Zuhaimy

“…The objective of this research is to estimate the Double Exponential Smoothing by using Genetic Algorithm Mechanism. …”
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Estimation of unemployement in Malaysia using fourth-order taylor’s series method and fourthorder runge kutta method / Nur Batrisyia Suhaimi by Suhaimi, Nur Batrisyia

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An investigation of structural breaks on spot and futures crude palm oil returns by Zainudin, Rozaimah, Shaharudin, Roselee Shah

“…Using the Inclan and Tioa Iterated Cumulative Sums of Squares (ICSS) algorithm procedures, we proceed to identify any structural changes in series variance. …”
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An Illustration of Generalised ARMA (GARMA) Time Series Modelling of Forest Area in Malaysia. by Pillai , Thulasyammal Ramiah, Shitan, Mahendran

“…The estimation of the model was done using Hannan-Rissanen Algorithm, Whittle's Estimation and Maximum Likelihood Estimation. …”
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Design Of Robot Motion Planning Algorithm For Wall Following Robot by Ali Hassan, Muhamad Khairul

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Parameter-driven count time series models / Nawwal Ahmad Bukhari by Nawwal , Ahmad Bukhari

“…Simulation shows that MCEM algorithm and particle method are useful for the parameter estimation of the Poisson model. …”
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Identifying homogeneous rainfall catchments for non-stationary time series using TOPSIS algorithm and bootstrap K-sample Anderson-Darling test by Chuan, Zun Liang, Noriszura, Ismail, Wan Nur Syahidah, Wan Yusoff, Soo-Fen, Fam, Mohd Akramin, Mohd Romlay

“…The Cophenetic Correlation Coefficients (CCC) from ten similarity measures are used as attributes for the TOPSIS algorithm to identify the most suitable AHC algorithm out of seven algorithms considered. …”
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Occupancy grid map algorithm with neural network using array of infrared sensors by N A, Yatim, N, Buniyamin, Z M, Noh, Nur Aqilah, Othman

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The enhanced BPNN-NAR and BPNN-NARMA models for Malaysian aggregate cost indices with outlying data by Ahmad Kamaruddin, Saadi, Md Ghani, Nor Azura, Mohamed Ramli, Norazan

“…In theory, the most common training algorithm for Backpropagation algorithms leans on reducing ordinary least squares estimator (OLS) or more specifically, the mean squared error (MSE). …”
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SYSTEM IDENTIFICATION AND MODEL PREDICTIVE CONTROL FOR INTERACTING SERIES PROCESS WITH NONLINEAR DYNAMICS by SETYO WIBOWO, TRI CHANDRA

“…The subspace system identification method is used to estimate the linear model parameters. The developed model is designed to be robust against plant nonlinearities. …”
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