Search Results - (( variable detection path algorithm ) OR ( property distribution function algorithm ))
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1
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. …”
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2
IMPLEMENTATION OF BEHAVIOUR BASED NAVIGATION IN A PHYSICALLY CONFINED SITE
Published 2017“…Selected basic behaviour-based algorithms such as wallfollower, obstacle avoidance, escape route and target detection are to be combined and its efficiency is measured. …”
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Final Year Project -
3
Parameter-driven count time series models / Nawwal Ahmad Bukhari
Published 2018“…The first part of the study derives the explicit solutions of the moment properties (mean, variance, skewness and kurtosis) of the distributions together with their respective autocovariance and autocorrelation functions, up to the ith order. …”
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Thesis -
4
On a new transmuted three-parameter lindley distribution and its applications
Published 2024“…The statistical properties of the TTHPLD model, which are based on moments, order statistics, hazard rate functions, reliability functions, and Renyi entropy, have been studied. …”
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5
A real-time integrated fire detection and alarm (FDA) system for network based building automation
Published 2017“…Methods/Analysis: In this work, the shortest path algorithm was chosen for series of buildings connected by a fiber-optic network. …”
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6
LED based NIR spectroscopy for detection of lard adulteration in palm oil via chemometrics / Katrul Nadia Basri
Published 2017“…In order to remove the uninformative variables, cumulative adaptive reweighted sampling (CARS) has been performed. …”
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Thesis -
7
Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…Also, a one-step iterative algorithm, called expected rank algorithm, is introduced which is more complicated than the estimation-approximation algorithm, but more accurate. …”
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8
Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching
Published 2016“…Some of the theoretical properties of the distributions are derived and the distributions' characteristics are studied. …”
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Thesis -
9
Classification and quantification of palm oil adulteration via portable NIR spectroscopy
Published 2017“…In order to remove the uninformative variables, variable selection using cumulative adaptive reweighted sampling (CARS) has been performed. …”
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10
Classification and quantification of palm oil adulteration via portable NIR spectroscopy
Published 2024“…In order to remove the uninformative variables, variable selection using cumulative adaptive reweighted sampling (CARS) has been performed. …”
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11
A Novel Approach Of Groebner Bases Computation For Safety Analysis Of Distributed Discrete Controllers
Published 2019“…One of the favorite topic is the formal verification via model checking, which is to verify whether a mathematical model of a system meets the formal specification that describes the property to be checked. In this research, our main objective is to generate a new model checking computation method based on Groebner bases algorithm for safety property analysis of distributed discrete controllers. …”
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Technical Report -
12
Modeling The Modified Internal Rate Of Return (Mirr) For Long-Term Investment Strategy By The Assumption Of Gamma Distribution
Published 2023“…However, simultaneously estimating all three parameters (shape, scale, and growth) through the maximum-likelihood function is computationally complex. Alternative approaches such as the Simulated Annealing (SA) algorithm, which maximizes the log-likelihood function, and Bayesian MCMC estimation are considered. …”
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13
A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…In addition, the classifier is also optimized such that it has a good generalization property. The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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Thesis -
14
An improved bat algorithm with artificial neural networks for classification problems
Published 2016“…Then, the proposed BAGD algorithm is frnther hybridized with Simulated Annealing (SA) and Genetic Algorithm (GA) to perform two stage optimization in which the former algorithm finds the optimal solution and the latter algorithm starts from where the first one is converged. …”
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15
A New Cryptosystem Based on Decimal Numbers and Nonlinear Function
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16
High performance visualization of human tumor growth software
Published 2008“…The platform for high performance computing of the parallel algorithms run on a distributed parallel computer system. …”
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17
Enhanced Automated Framework For Cattle Tracking And Classification
Published 2022“…Mean-shift strength is its sensitivity to object’s movement and colour distribution by using similarity function but, with inability to track object’s non-linear movement and full occlusion as its weakness.…”
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Thesis -
18
High performance simulation for brain tumors growth using parabolic equation on heterogeneous parallel computer systems
Published 2007“…This paper focuses on the implementation of parallel algorithm for the simulation of brain tumours growth using one dimensional parabolic equation, design on a distributed parallel computer system. …”
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19
Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system
Published 2023“…AOA makes use of the distribution properties of mathematics’ primary arithmetic operators, including multiplication, division, addition, and subtraction. …”
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20
Predicting the popularity of tweets using the theory of point processes.
Published 2019“…The mode of the posterior distribution is used as the estimator of the finite-dimensional parameter, and suitable functionals of the predictive distribution for the number of retweets implied by the estimated model are used to predict the tweet popularity. …”
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