Search Results - (( java application scheduling algorithm ) OR ( parametric estimation method algorithm ))
Search alternatives:
- application scheduling »
- parametric estimation »
- estimation method »
- java application »
- method algorithm »
-
1
Semiparametric estimation with profile algorithm for longitudinal binary data
Published 2013“…We use profile algorithm in the estimation of both parametric and nonparametric components. …”
Get full text
Get full text
Article -
2
Non-Parametric and Parametric Estimations of Cure Fraction Using Right-and Interval-Censored Data
Published 2011“…The major research findings were as follows: 1) the non-parametric and parametric estimation methods using the right and interval censoring types produced highly efficient cure rate parameters when the censoring rate was decreased to the minimum possible; 2) Non-parametric estimation of the cure fraction using interval censored data based on Turnbull estimator resulted in more precise cure fraction than the Kaplan Meier estimator considering the interval midpoint to represent the exact life time; 3) The parametric estimation of the cure fraction based on the exponential distribution and right and interval censoring types produced more consistent estimates than the Weibull distribution especially in case of heavy censoring; 4) Parametric estimation of the cure fraction was more efficient when some covariates had been involved in the analysis than when covariates had been excluded; and 5) the nonparametric estimation method is the viable alternative to the parametric one when the data set contains substantial censored observations while in the case of low censoring the parametric method is more attractive.…”
Get full text
Get full text
Thesis -
3
Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…The CPU profiler of JavaTM VisualVM measures the number of invocations of scheduling event handlers (procedures) in each algorithm as well as the total time spent in all invocations of this handler. …”
Get full text
Get full text
Conference or Workshop Item -
4
A Toolkit for Simulation of Desktop Grid Environment
Published 2014“…In this type of environment it is nearly impossible to prove the effectiveness of a scheduling algorithm. Hence the main objective of this study is to develop a desktop grid simulator toolkit for measuring and modeling scheduler algorithm performance. …”
Get full text
Get full text
Final Year Project -
5
-
6
Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT
Published 2006“…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
Get full text
Get full text
Thesis -
7
Parametric maximum likelihood estimation of cure fraction using interval-censored data
Published 2013“…The parametric maximum likelihood estimation method was used for estimation of the cure fraction based on application of the bounded cumulative hazard (BCH) model to interval-censored data. …”
Get full text
Get full text
Get full text
Article -
8
-
9
Improving Class Timetabling using Genetic Algorithm
Published 2006“…This paper reports the power fill techniques using GA in scheduling. Class timetabling problem is one of the applications in scheduling. …”
Get full text
Get full text
Get full text
Thesis -
10
Examination timetabling using genetic algorithm case study: KUiTTHO
Published 2005“…This paper reports the powerful techniques using GA in scheduling. Examination timetabling problem is one of the applications in scheduling. …”
Get full text
Get full text
Thesis -
11
Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO
Published 2005“…This paper reports the powerful techniques using GA in scheduling. Examination timetabling problem is one of the applications in scheduling. …”
Get full text
Get full text
Get full text
Thesis -
12
An intelligent framework for modelling and active vibration control of flexible structures
Published 2004“…Parametric approaches include linear parametric modelling of the system using recursive least squares (RLS) and genetic algorithms (GAS); and non-parametric approaches include multi-layered perceptron neural networks (MLP-NNs) and adaptive neuro-fuzzy inference systems (ANFIS) are employed. …”
Get full text
Get full text
Get full text
Thesis -
13
GEE-smoothing spline in semiparametric model with correlated nominal data
Published 2010“…We use profile algorithm in the estimation of both parametric and nonparametric components. …”
Get full text
Get full text
Conference or Workshop Item -
14
-
15
Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
Get full text
Get full text
Article -
16
Semiparametric binary model for clustered survival data
Published 2014“…A backfitting algorithm is used in the derivation of the estimating equation for the parametric and nonparametric components of a semiparametric binary covariate model. …”
Get full text
Get full text
Conference or Workshop Item -
17
Analysis of the ECG signal using SVD-based parametric modelling technique
Published 2011“…A two-stage procedure is then used to estimate the EDS model parameters. Prony’s algorithm is first used to obtain initial estimates of the model, while the Gauss-Newton method is applied to solve the non-linear least-square optimisation problem. …”
Get full text
Get full text
Get full text
Proceeding Paper -
18
Parametric cure fraction models for interval-censoring with a change-point based on a covariate threshold
Published 2015“…The proposed model has sound motivation in relapse of cancer and can be used in other disease models. The parametric maximum likelihood estimation method is employed to verify the performance of the MCM within the framework of the expectation-maximization (EM) algorithm while the estimation methods for other models are employed in a simpler and straightforward setting. …”
Get full text
Get full text
Thesis -
19
Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor
Published 2017“…This study begins by proposing a robust technique for estimating the slope parameter in LFRM. In particular, the focus is on the non-parametric estimation of the slope parameter and the robustness of this technique is compared with the maximum likelihood estimation and the Al-Nasser and Ebrahem (2005) method. …”
Get full text
Get full text
Get full text
Thesis -
20
