Search Results - (( model estimation method algorithm ) OR ( risk estimation methods algorithm ))

Modeling of cardiovascular diseases (CVDs) and development of predictive heart risk score by Mirza Rizwan, Sajid

“…The warppartial least square method was utilized to estimate the multi-layer hypothesized path model. …”
Get full text
Get full text

Credit scoring for Cooperative of financial services using logistic regression estimated by genetic algorithm by Mustafa, Mamat, Sukono, Firman, Asep, Sholahuddin

“…In this paper the analysis of credit scoring is done using logistic regression model, which is estimated using genetic algorithms. …”
Get full text
Get full text

Bayesian logistic regression model on risk factors of type 2 diabetes mellitus by Chiaka, Emenyonu Sandra

“…The significant variables determined by maximum likelihood method were then estimated using the BLR method. The BLR approach via Gibbs sampler and the random walk metropolis algorithm suggests that family history of diabetes, waist circumference and the body mass index are the significant risk factors associated with the type 2 diabetes mellitus. …”
Get full text
Get full text

Em Approach on Influence Measures in Competing Risks Via Proportional Hazard Regression Model by Elfaki, Faiz. A. M.

“…A generated data where the failure times were taken as exponentially distributed was used to further compare these two methods of estimation. From the simulation study for this particular case, we can conclude that the EM algorithm proved to be more superior in terms of mean value of parameter estimates, bias and root mean square error. …”
Get full text
Get full text

Extreme air pollutant data analysis using classical and Bayesian approaches by Mohd Amin, Nor Azrita

“…In general, both methods are performing well for analyzing extreme model but numerical results show that MTM method performs slightly better than MH method in terms of efficiency and convergency to the stationary distribution. …”
Get full text
Get full text

Modeling Earthquake Bond Prices with Correlated Dual Trigger Indices and the Approximate Solution Using the Monte Carlo Algorithm by Riza Andrian Ibrahim, Sukono, Herlina Napitupulu, Rose Irnawaty Ibrahim

Reproducing kernel Hilbert space method for cox proportional hazard model by Abdul Manaf, Nur'azah

“…Then, we apply the kernel method to the survival data. Finally, we propose an algorithm of minimization of the loss function in the general Cox model. …”
Get full text
Get full text
Get full text

Full waveform inversion based on genetic local search algorithm with hybrid-grid scheme by Hamamoto, M., Rahim Md Arshad, A., Prasad Ghosh, D.

“…This results in low-resolution model less than optimum solution. Therefore, we propose an FWI method based on genetic local search algorithm with hybrid-grid scheme (HGLS-FWI). …”
Get full text
Get full text

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. …”
Get full text
Get full text
Get full text

Data mining techniques for disease risk prediction model: A systematic literature review by Ahmad W.M.T.W., Ghani N.L.A., Drus S.M.

Statistical process control for failure crushing time data using competing risks model by Elfaki, Faiz Ahmed Mohamed, Daoud, Jamal Ibrahim, Azram, Mohammad, Daud, Isa, Ibrahim, N.A., Usman, Mustofa

“…EM algorithm method is used to estimate the parameter of the model. …”
Get full text
Get full text
Get full text

Statistical process control for failure crushing time data using competing risks model. by Elfaki, F.A.M., Daud, Isa, Ibrahim, Noor Akma, Daud, J., Azram, M., Usman, M.

“…EM algorithm method is used to estimate the parameter of the model. …”
Get full text
Get full text
Get full text

Competing risks for reliability analysis using Cox’s model by Mohamed Elfaki, Faiz Ahmed, Daud, Isa, Ibrahim, Nor Azowa, Abdullah, M. Y., Usman, Mustofa

“…This paper seeks to show that, with a large sample size based on expectation maximization (EM) algorithm, both models give similar results. Design/methodology/approach – The parameters of the models have been estimated by method of maximum likelihood based on EM algorithm. …”
Get full text
Get full text
Get full text

Application of the generalized likelihood uncertainty estimation (GLUE) approach for assessing uncertainty in hydrological models: A review by Mirzaei, M., Huang, Y.F., El-Shafie, A., Shatirah, A.

“…The generalized likelihood uncertainty estimation (GLUE) technique is an innovative uncertainty method that is often employed with environmental simulation models. …”
Get full text
Get full text
Get full text

Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis by Mohamed Elfaki, Faiz Ahmed

“…The Expectation Maximization (EM) algorithm is utilized to obtain the estimate of the parameters in the models. …”
Get full text
Get full text

A novel approach to human motion estimation with applications in human-robot safety by Motlagh, O., Tang, Sai Hong, Ismail, Napsiah, Ramli, Abdul Rahman, Samin, Razali

Get full text
Get full text
Get full text

Integrated applications of building information modeling in project cost management: a systematic review by M. Farouk, Abdelrahman, Rahimi, A. Rahman

“…On the contrary, integrated approaches for cost estimation include integration with cost-plus pricing, discrepancy analysis, construction progress curves, estimation standards, algorithms, declarative mappings, life cycle sustainability assessment, ontology, Web-based frameworks and structured query language. …”
Get full text
Get full text
Get full text

Steady state security analysis using artificial neural network by Mohd Nor, Nurul Huda

“…The cases where operating violations are observed are considered as alert , while the cases for which the load flow algorithm exhibits a diverging algorithmically solution, are considered as emergency. …”
Get full text
Get full text

A framework for automatic modelling of survival using fuzzy inference. by Hamdan, Hazlina, Garibaldi, Jonathan M.

“…We demonstrate that the proposed framework can be successfully applied to estimate the hazard and survival curves between different prognostic factors, and model survival times, while providing models with explicit explanation capabilities.…”
Get full text
Get full text

Real-Time Flood Inundation Map Generation Using Decision Tree Machine Learning Method: Case Study of Kelantan River Basins by Sidek L.M., Basri H., Marufuzzaman M., Deros A.M., Osman S., Hassan F.A.

“…So, in this research, a real-time flood inundation map (FIM) is used to develop the ML-based visualization (ML_V) method to characterize the collected dataset. Additionally, to predict the flood depth, a trained Decision Tree (DT)-based sorting algorithm is used in this method. …”