Search Results - (( using simulation method algorithm ) OR ( risk estimation method algorithm ))
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1
Extreme air pollutant data analysis using classical and Bayesian approaches
Published 2015“…MTM algorithm is an extension of MH algorithm, designed to improve the convergence of MH algorithm by performing parallel computation. …”
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2
Competing risks for reliability analysis using Cox’s model
Published 2007“…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. …”
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3
Em Approach on Influence Measures in Competing Risks Via Proportional Hazard Regression Model
Published 2000“…A generated data where the failure times were taken as exponentially distributed was used to further compare these two methods of estimation. …”
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4
Reproducing kernel Hilbert space method for cox proportional hazard model
Published 2016“…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. …”
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5
Steady state security analysis using artificial neural network
Published 2008“…The performance of the developed model is compared with the unified neural network trained with the full feature set. Simulation results show that the proposed method takes less time for training and has good generalization.…”
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6
Reliability assessment of power system generation adequacy with wind power using population-based intelligent search methods
Published 2017“…The reliability assessment of the adequacy of the generating system is normally calculated by using either analytical or simulation methods. The Monte Carlo simulation (MCS) method enables an accurate evaluation of reliability indices. …”
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7
Entropy in portfolio optimization / Yasaman Izadparast Shirazi
Published 2017“…Details of the algorithms which include entropy estimation which would enhance the application of a proper risk measure like entropy, is provided. …”
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8
Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis
Published 2004“…The Expectation Maximization (EM) algorithm is utilized to obtain the estimate of the parameters in the models. …”
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9
Multi-source data fusion framework for remote triaging and prioritization in telemedicine
Published 2015“…As telemedicine consists of three tiers (Sensors/ sources, Base station and Server), the simulation of the proposed frameworks as fusion algorithm in the base station and as healthcare services algorithm in the server was demonstrated. …”
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10
Time-Uncertainty Analysis by Using Simulation in Project Scheduling Networks
Published 1999“…In this study, Monte Carlo simulation as a tool of risk analysis was used. The merge event bias as one of the essential problems associated with PERT is discussed, along with models and approaches developed by other researchers, namely, Probabilistic Network Evaluation Technique (PNET algorithm), Modified PNET, Back-Forward Uncertainly Estimation procedure (BFUE) and concept based on the robust reliability idea. …”
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11
Application of the generalized likelihood uncertainty estimation (GLUE) approach for assessing uncertainty in hydrological models: A review
Published 2015“…The generalized likelihood uncertainty estimation (GLUE) technique is an innovative uncertainty method that is often employed with environmental simulation models. …”
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12
Integrated applications of building information modeling in project cost management: a systematic review
Published 2023“…A total of 46 related articles were identified and analyzed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses method. …”
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13
Modelling and Forecasting the Kuala Lumpur Composite Index Rate of Returns Using Generalised Autoregressive Conditional Heteroscedasticity Models
Published 2004“…The EM algorithm is applied to split the heterogeneous data, and the estimated parameters are used to correct the outlying data using the Mahalanobis Distance. …”
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14
Dynamic investment model for the restructed power market in the presence of wind source
Published 2014“…In the first step, the hybrid Autoregressive Moving Average – Monte Carlo method proposes to simulate the hourly wind speed as well as the hourly wind turbine generators. …”
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15
Determining malaria risk factors in Abuja, Nigeria using various statistical approaches
Published 2018“…Data collected were used for the multilevel analysis, Markov Chain Monte Carlo (MCMC) simulation via WinBUGS algorithm and influence diagrams for BBNs. …”
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16
Chemometric approaches in the evaluation of trace metals in commercially raised tilapia and preliminary health risk assessment of its consumption / Low Kah Hin
Published 2012“…For safety evaluation, the metal concentrations in the edible muscles were compared with the established legal limits and reasonable maximum exposures were simulated using the Monte Carlo algorithm.…”
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17
Credit scoring for Cooperative of financial services using logistic regression estimated by genetic algorithm
Published 2014“…In this paper the analysis of credit scoring is done using logistic regression model, which is estimated using genetic algorithms. As a numerical illustration, the method used to analyze the credit scoring on a cooperative of financial services in Indonesia. …”
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18
Modeling of cardiovascular diseases (CVDs) and development of predictive heart risk score
Published 2021“…The warppartial least square method was utilized to estimate the multi-layer hypothesized path model. …”
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19
Risk assessment for safety and health algorithm for building construction in Oman
Published 2015“…The RASH algorithm is defined by overall risk, which is equivalent to the sum of Risk Safety Safety, Risk Safety Health, Risk Health Safety, and Risk Health Health. …”
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20
Bayesian logistic regression model on risk factors of type 2 diabetes mellitus
Published 2016“…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. …”
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