Search Results - (( java implementation path algorithm ) OR ( using competency model algorithm ))
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Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer
Published 2017“…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment
Published 2021“…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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Smart appointment organizer for mobile application / Mohd Syafiq Adam
Published 2009“…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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Academic leadership bio-inspired classification model using negative selection algorithm
Published 2015“…Managing employee’s competency is considered as the top challenge for human resource professional especially in the process to determine the right person for the right job that is based on their competency.As an alternative approach, this article attempts to propose academic leadership bio-inspired classification model using negative selection algorithm to handle this issue.This study consists of three phases; data preparation, model development and model analysis. …”
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Statistical process control for failure crushing time data using competing risks model.
Published 2011“…EM algorithm method is used to estimate the parameter of the model. …”
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Statistical process control for failure crushing time data using competing risks model
Published 2011“…EM algorithm method is used to estimate the parameter of the model. …”
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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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Cutpoint determination methods in competing risks subdistribution model
Published 2009“…In the analysis involving clinical and psychological data, by transforming a continuous predictor variable into a categorical variable, usually binary, a more interpretable model can be established. 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. …”
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Cutpoint determination methods in competing risks subdistribution model
Published 2009“…In the analysis involving clinical and psychological data, by transforming a continuous predictor variable into a categorical variable, usually binary, a more interpretable model can be established. 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. …”
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Furniture form innovation and human–machine comfort evaluation model based on genetic algorithm
Published 2024“…Afterward, a mathematical version is used to symbolize the layout preference problems, and the layout scheme selection method is simulated. …”
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Multiple equations model selection algorithm with iterative estimation method
Published 2016“…In particular, an algorithm on model selection for seemingly unrelated regression equations model using iterative feasible generalized least squares estimation method is proposed. …”
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Permodelan Rangkaian Neural Buatan Untuk Penilaian Kendiri Teknologi Maklumat Guru Pelatih
Published 2001“…Data containing eleven predictive variables was used to train and test neural network model. The research procedures chosen were the multi-layered perceptron with back propagation algorithmic learning. …”
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Parametric and Semiparametric Competing Risks Models for Statistical Process Control with Reliability Analysis
Published 2004“…Residual-based approaches are used to assess the validity of the two models (MW, CC) assumptions. …”
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Em Approach on Influence Measures in Competing Risks Via Proportional Hazard Regression Model
Published 2000“…In a conventional competing risk s model, the time to failure of a particular experimental unit might be censored and the cause of failure can be known or unknown. …”
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Field data-based mathematical modeling by Bode equations and vector fitting algorithm for renewable energy applications
Published 2018“…The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model.…”
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Spiral-sooty tern optimization algorithm for dynamic modelling of a twin rotor system
Published 2022“…A spiral model is incorporated into the Sooty-Tern Optimization Algorithm (STOA) structure. …”
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Characteristic wavelength optimization for partial least squares regression using improved flower pollination algorithm
Published 2023“…Wavelength selection is crucial to the success of near-infrared (NIR) spectroscopy analysis as it considerably improves the generalization of the multivariate model and reduces model complexity. This study proposes a new wavelength selection method, interval flower pollination algorithm (iFPA), for spectral variable selection in the partial least squares regression (PLSR) model. …”
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