Search Results - (( data distribution function algorithm ) OR ( variable optimization max algorithm ))
Search alternatives:
- variable optimization »
- function algorithm »
- data distribution »
- optimization max »
- max algorithm »
-
1
Maximum 2-satisfiability in radial basis function neural network
Published 2020“…Correctly, this logic plays a prominent role in numerous applications as a combinatorial optimization logic. MAX2SAT is a case of MAX-kSAT and is written in Conjunctive Normal Form (CNF) with two variables in each clause. …”
Get full text
Get full text
Get full text
Article -
2
Prediction and multi-criteria-based schemes for seamless handover mechanism in mobile WiMAX networks
Published 2013“…Mobile WiMAX introduces several interesting advantages including last mile wireless access, variable and high data rate, point to multi-point communication, large frequency range and QoS (Quality of Service) for various types of applications. …”
Get full text
Get full text
Thesis -
3
Single Fitness Function to Optimize Energy using Genetic Algorithms for Wireless Sensor Network
Published 2024journal::journal article -
4
Design Optimization of a Gas Turbine Engine for Marine Applications: Off-Design Performance and Control System Considerations
Published 2022“…Meta-heuristic optimizations, namely a genetic algorithm (GA) and a whale optimization algorithm (WOA), are applied to optimize the designed control system. …”
Get full text
Get full text
Article -
5
-
6
Interference avoidance routing and scheduling using multiple transceivers for IEEE 802.16 mesh network
Published 2010“…Here, a routing tree is constructed based on the energy/bit minimization routing (EbMR). This algorithm looks for a short path from the subscriber station (SS) node to BS, while the optimal path is achieved when the whole path has the lowest EbMR. …”
Get full text
Get full text
Thesis -
7
Hierarchical Bayesian estimation for stationary autoregressive models using reversible jump MCMC algorithm
Published 2018“…In the hierarchical Bayesian approach, the order and coefficients of the autoregressive model are assumed to have a prior distribution. The prior distribution is combined with the likelihood function to obtain a posterior distribution. …”
Get full text
Article -
8
Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…Thereafter, a multi-objective hybrid algorithm (MOHA), an extension of the self-adaptive hybrid algorithm is proposed and tested on the established multi-objective (MO) test functions. …”
Get full text
Get full text
Thesis -
9
A new Gompertz-three-parameter-lindley distribution for modeling survival time data
Published 2025“…The statistical properties of the proposed distribution including the shape properties, cumulative distribution, quantile functions, moment generating function, failure rate function, mean residual function, and stochastic orders are studied. …”
Get full text
Get full text
Get full text
Article -
10
Reliability Analysis and Prediction of Time to Failure Distribution of an Automobile Crankshaft
Published 2015“…The developed stochastic algorithm has the capability to measure the parametric distribution function and validate the predict the reliability rate, mean time to failure and hazard rate. …”
Get full text
Get full text
Get full text
Get full text
Article -
11
Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…The main contribution of this research is developing statistical approaches, and introducing new algorithms and resampling methods for analysing interval-censored data through AFT models.…”
Get full text
Get full text
Get full text
Thesis -
12
Slice sampler algorithm for generalized pareto distribution
Published 2018“…In this paper, we developed the slice sampler algorithm for the generalized Pareto distribution (GPD) model. …”
Get full text
Get full text
Article -
13
Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems
Published 2014“…In order to evaluate the scalability at specific data size the appropriate regression models are fitted through the measured data as functions of number of workers. …”
Get full text
Get full text
Thesis -
14
Parameter-driven count time series models / Nawwal Ahmad Bukhari
Published 2018“…A key property of our model is that the distributions of the observed count data are independent, conditional on the latent process, although the observations are correlated marginally. …”
Get full text
Get full text
Get full text
Thesis -
15
Sizing and placement of solar photovoltaic plants by using time-series historical weather data
Published 2018“…To predict the output from the PV modules, 15 years of solar data were modeled with the aid of a beta probability density function. …”
Get full text
Get full text
Article -
16
Sizing and placement of solar photovoltaic plants by using time-series historical weather data
Published 2018“…To predict the output from the PV modules, 15 years of solar data were modeled with the aid of a beta probability density function. …”
Get full text
Get full text
Article -
17
Optimal network reconfiguration and intelligent service restoration prediction technique based on Cuckoo search spring algorithm / Mohamad Izwan Zainal
Published 2022“…In addition, objective function using the same CSSA algorithm were applied i.e., Vmin and Ploss as the objective function, and multi-objective involves Vmin and Ploss as the objective function. …”
Get full text
Get full text
Thesis -
18
Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching
Published 2016“…A popular distribution for the modelling of discrete count data is the Poisson distribution. …”
Get full text
Get full text
Thesis -
19
Discovery of SIP/DRIP approach in distributed inter process communication
Published 2023“…This paper made experiments on the combination of SIP/DRIP algorithm with DIPC distributed system to increase the computation speed of the method. …”
Conference paper -
20
Bayesian inference for the bivariate extreme model
Published 2016“…Maximum likelihood method and a Markov chain Monte Carlo (MCMC) technique, Multiple-try Metropolis algorithm are implemented into the data analysis. MTM algorithm is the new alternative in the field of Bayesian extremes for summarizing the posterior distribution. …”
Get full text
Get full text
Conference or Workshop Item
