Search Results - (( simulation competing values algorithm ) OR ( java implication tree algorithm ))
Search alternatives:
- simulation competing »
- values algorithm »
- java implication »
- implication tree »
- tree algorithm »
-
1
Competing risks for reliability analysis using Cox’s model
Published 2007“…Also, the modification of the two models showed better results compared with Crowder et al., especially for the second causes of failure. Originality/value – A modification of the two competing risk models has mostly been applied in failure time data and simulation data. …”
Get full text
Get full text
Get full text
Article -
2
Cutpoint determination methods in competing risks subdistribution model
Published 2009“…Thus, we consider the problem of obtaining a threshold value of a continuous covariate given a competing risk survival time response using a binary partitioning algorithm as a way to optimally partition data into two disjoint sets. …”
Get full text
Get full text
Article -
3
Cutpoint determination methods in competing risks subdistribution model
Published 2009“…Thus, we consider the problem of obtaining a threshold value of a continuous covariate given a competing risk survival time response using a binary partitioning algorithm as a way to optimally partition data into two disjoint sets. …”
Get full text
Get full text
Get full text
Article -
4
Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation
Published 2022“…This thesis proposes and simulates the three novel optimization algorithms to handle DG allocation, different single-objective, and multi-objective OPF problems. …”
Get full text
Get full text
Thesis -
5
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. 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
Thesis -
6
Development of FRID based 2d localization simulation for autonomous guided vehicle tracking in indoor environment
Published 2018“…The localization techniques are based on measuring the distance using path loss model from RSSI values provided by RFID and coordinates calculation using trilateration algorithm with multiple reference points. …”
Get full text
Get full text
Get full text
Get full text
Article -
7
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. …”
Get full text
Get full text
Thesis -
8
Finite impulse response optimizers for solving optimization problems
Published 2019“…Simulated Kalman filter (SKF) algorithm is one of the algorithms under this classification. …”
Get full text
Get full text
Thesis -
9
Finite impulse response optimizers for solving optimization problems
Published 2019“…Simulated Kalman filter (SKF) algorithm is one of the algorithms under this classification. …”
Get full text
Get full text
Thesis -
10
-
11
A New Model For Network-Based Intrusion Prevention System Inspired By Apoptosis
Published 2024thesis::doctoral thesis -
12
Blockchain based security framework for device authentication and data communication in decentralized IoT network
Published 2023“…The receiver would compare the hash value to that stored in the authentication table to authenticate the sender. …”
Get full text
Get full text
Thesis -
13
Self-configured link adaptation using channel quality indicator-modulation and coding scheme mapping with partial feedback for green long-term evolution cellular systems
Published 2015“…To achieve this objective, an iterative approach based on swarm intelligence is used to find the optimal CQI threshold at which the competing criteria are optimized. Since the developed downlink scheduler and the partial feedback scheme affect the QoS, self-configured versions of both algorithms are developed to provide QoS provisioning. …”
Get full text
Get full text
Thesis -
14
Modelling and Forecasting the Kuala Lumpur Composite Index Rate of Returns Using Generalised Autoregressive Conditional Heteroscedasticity Models
Published 2004“…It is found that this method has a clear edge over its rival because PCA uses actual values of the goodness of fit test criteria (LogL, SBC, and AIC in estimation and RMSE, MAE, AMAPE and MAPE in forecasting) and hence the inability to specify exactly the relative positions of each of the competing models as faced by the ranking method may be overcome. …”
Get full text
Get full text
Thesis
