Search Results - (( normal distribution methods algorithm ) OR ( parameter estimation tool algorithm ))

Machine condition monitoring and fault diagnosis using spectral analysis techniques by Salami, Momoh Jimoh Eyiomika, Abdul Muthalif, Asan Gani, Pervez, T.

“…Vibration data are collected from the piezoelectric accelerometers placed at locations that provide rigid vibration transmission to them. Both normal and fault signals are analyzed using the singular value decomposition (SVD) algorithm so as to compute the parameters of the auto regressive moving average (ARMA) models. …”
Get full text
Get full text

Optimal parameter estimation of MISO system based on fuzzy numbers / Razidah Ismail ... [et al.] by Ismail, Razidah, Ahmad, Tahir, Ahmad, Shamsuddin, Ahmad, Rashdi Shah

“…This situation can be taken into account by using fuzzy numbers, which has been proved to be a very useful tool. Thus, this paper discusses the development of a Fuzzy State Space algorithm for optimal parameter estimation in multiple-input single-output (MISO) system based on fuzzy numbers. …”
Get full text
Get full text

Parameter estimation of multivariable system using Fuzzy State Space Algorithm / Razidah Ismail … [et al.] by Ismail, Razidah, Ahmad, Tahir, Harish, Noor Ainy, A. Halim, Rosenah

Get full text
Get full text

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

“…The artificial neural network type Network Fitting Tool (NFTOOL) is used as a modeling technique for manipulating the ideal algorithm parameters. …”
Get full text
Get full text
Get full text

Fitness-guided particle swarm optimization with adaptive Newton-Raphson for photovoltaic model parameter estimation by Premkumar M., Ravichandran S., Hashim T.J.T., Sin T.C., Abbassi R.

Improved performance in distributed estimation by convex combination of DNSAF and DNLMS algorithms by Ahmad Pouradabi, Amir Rastegarnia, Azam Khalili, Ali Farzamnia

“…Diffusion normalized least mean square (DNLMS) algorithm has low misadjustment error, but it is slow in convergence. …”
Get full text
Get full text
Get full text
Get full text

Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
Get full text
Get full text

Cutting Parameters Optimization of Mild Steel via AIS Heuristics Algorithm by Minhat, Mohamad, Abd Rahman, Md Nizam, Abbas, Adnan Jameel

“…The optimum cutting parameters (cutting velocity, depth of cut and feed rate) calculated by (AIS) algorithm to obtain the simulated and ideal cutting temperature and surface roughness. …”
Get full text
Get full text

A study on advanced statistical analysis for network anomaly detection by Ngadi, Md. Asri, Idris, Mohd. Yazid, Abdullah, Abd. Hanan

“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
Get full text

Confidence intervals (CI) for concentration parameter in von Mises distribution and analysis of missing values for circular data / Siti Fatimah binti Hassan by Hassan, Siti Fatimah

“…For example, the distribution analogues to the normal distribution in linear data is known as circular normal distribution. …”
Get full text
Get full text

Statistical approach on grading: mixture modeling by Md. Desa, Zairul Nor Deana

“…Statistical approaches which use the Standard Deviation and conditional Bayesian methods are considered to assign the grades. In the conditional Bayesian model, we assume the data to follow the Normal Mixture distribution where the grades are distinctively separated by the parameters: means and proportions of the Normal Mixture distribution. …”
Get full text
Get full text

Processing time estimation in precision machining industry using AI / Lim Say Li by Lim, Say Li

“…These time estimations are usually done and revised by a tooling process expert. …”
Get full text
Get full text

Identification of non-equilibrium growth for bitcoin exchange rate: mathematical derivation method in Islamic financial engineering by Rosbi, Sofian, Abu Bakar, Nashirah

“…Graphical method indicates the first difference of data distribution is a non-normal distribution. …”
Get full text
Get full text
Get full text

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

“…A numerical example is given to illustrate that the SPSA based algorithms can give accurate parameter estimate of the Hammerstein models with high probability through detailed simulation.…”
Get full text
Get full text

Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares by Uraibi, Hassan Sami

“…One of the important assumptions of the linear model is that the error terms are normally distributed. Unfortunately, many researchers are not aware that the performance of the OLS can be very poor when the data set that one often makes a normal assumption, has a heavy-tailed distribution which may arise as a result of the presence of outliers. …”
Get full text
Get full text

Combining Recursive Least Square and Principal Component Analysis for Assisted History Matching by Md. Anuar, Nurul Syaza

“…Even though RLS is a simple and effective method to estimate parameters, RLS have stability problem when number of parameters is high. …”
Get full text
Get full text

Dynamic robust bootstrap method based on LTS estimators by Midi, Habshah, Uraibi, Hassan Sami, Al-Talib, Bashar Abdul Aziz Majeed

“…In order to make reliable inferences about the parameters of a model, require that the parameter estimates are normally distributed. Nevertheless, in real situations, many estimates are not normal and the use of bootstrap method is more appropriate as it does not rely on the normality assumption. …”
Get full text
Get full text

Statistical approach on grading the student achievement via normal mixture modeling by Md. Desa, Zairul Nor Deana, Mohamad, Ismail, Mohd. Khalid, Zarina, Md. Zin, Hanafiah

“…Statistical approaches which used the Standard Deviation (GC) and conditional Bayesian methods are considered to assign the grades. In the conditional Bayesian model, we assume the data to follow the Normal Mixture distribution where the grades are distinctively separated by the parameters: means and proportions of the Normal Mixture distribution. …”
Get full text
Get full text
Get full text

Design of super twisting algorithm for chattering suppression in machine tools by Chiew, Tsung Heng, Jamaludin, Zamberi, Bani Hashim, Ahmad Yusairi, Abdullah, Lokman, Rafan, Nur Aidawaty

Get full text
Get full text
Get full text
Get full text

Improving the Muskingum flood routing method using a hybrid of particle swarm optimization and bat algorithm by Ehteram M., Othman F.B., Yaseen Z.M., Afan H.A., Allawi M.F., Malek M.B.A., Ahmed A.N., Shahid S., Singh V.P., El-Shafie A.