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20 articles for “Monte Carlo Algorithm”
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Research ArticleOpen accessIn the abstractStar Catalog Generation for Satellite Attitude Navigation Using Density Based ClusteringMuhammad Arif Saifudin, Bib Paruhum Silalahi, Imas Sukaesih SitanggangA new method to generate star catalog using density-based clustering is proposed. It identifies regions of a high star density by using Density-Based Spatial Clustering of Application with Noise (DBSCAN) algorithm. Reducing the number stars performed by storing the brightest star in each cluster. The brightest star and all non-clustered members are then stored as a navigation star candidate. Monte … …Journal of Computer Science, Vol. 11, Issue 12 · 1 Feb 2016 · 6,970 accessesView PDFCite
Research ArticleOpen accessIn the abstractESTIMATED AND ANALYSIS OF THE RELATIONSHIP BETWEEN THE ENDOGENOUS AND EXOGENOUS VARIABLES USING FUZZY SEMI-PARAMETRIC SAMPLE SELECTION MODELL. MuhamadSafiih, A. A. Kamil, M. T. Abu OsmanAn important progress within the last decade in the development of the selectivity model approach to overcome the inconsistent results if the distributional assumptions of the errors terms are made this problem is through the use of semi-parametric method. However, the uncertainties and ambiguities exist in the models, particularly the relationship between the endogenous and exogenous variables. A new framework … …American Journal of Applied Sciences, Vol. 11, Issue 9 · 15 Jul 2014 · 6,786 accessesView PDFCite
Research ArticleOpen accessIn the abstractBayesian Models for Time Series with Covariates, Trend, Seasonality, Autoregression and OutliersPitsanu Tongkhow, Nantachai KantananthaBayesian methods furnish an attractive approach to time series data analysis. This article proposes the forecasting models that can detect trend, seasonality, auto regression and outliers in time series data related to some covariates. Cumulative Weibull distribution functions for trend, dummy variables for seasonality, binary selections for outliers and latent autoregression for autocorrelated time series data are used for the … …Journal of Computer Science, Vol. 9, Issue 3 · 16 Apr 2013 · 6,653 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Performance Metric for Building an Optimized ClassifierMohammad Hossin, Md Nasir Sulaiman, Aida Mustapha, Norwati MustaphaProblem statement: Typically, the accuracy metric is often applied for optimizing the heuristic or stochastic classification models. However, the use of accuracy metric might lead the searching process to the sub-optimal solutions due to its less discriminating values and it is also not robust to the changes of class distribution. Approach: To solve these detrimental effects, we propose a novel … …Journal of Computer Science, Vol. 7, Issue 4 · 4 Apr 2011 · 8,477 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Rigorous Mathematical Approach for Petrophysical Properties EstimationDario VibertiProblem statement: Over the last few decades, the oil industry has shown a growing interest in the new risk analysis methodologies aimed at the evaluation of the uncertainties associated with reservoir exploitation. In particular, the effort is made to take all possible sources of uncertainties into account so that not only the strengths but also the potential weaknesses of each … …American Journal of Applied Sciences, Vol. 7, Issue 11 · 8 Nov 2010 · 7,976 accessesView PDFCite
Research ArticleOpen accessIn the abstractCalculation of Total Cost, Tolerance Based on Taguchi's, Asymmetric Quality Loss Function ApproachR. Sampath Kumar, N. Alagumurthi, R. RameshProblem statement: Current world market force the manufacturing sectors to develop high quality product and process design with minimum possible cost. About 80% of problems in production units may be attributed to 20% of design tolerance causes. While design typically represents the smallest actual cost elements in products (around 5%), it leverages the largest cost influence (around 70%). So design … …American Journal of Engineering and Applied Sciences, Vol. 2, Issue 4 · 31 Dec 2009 · 8,045 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Stochastic Knapsack Problem with Continuous Random CapacitySuwitchporn Witchakul, Prapaisri Sudas Na Ayudhaya, Peerayuth CharnsethikulProblem Statement: The problem of allocating a set of items in order to maximize the toal linear profit under uncertain capacity referred as a stochastic knapsack problem with continuous random capacity was studied theoretically and computationally. Approach: Two optimization based heuristic algorithms were proposed and developed for solving the problem and both efficiency and effectiveness are compared with the general … …Journal of Mathematics and Statistics, Vol. 4, Issue 4 · 31 Dec 2008 · 6,946 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Survey of Protein Fold Recognition AlgorithmsMohammed Said Abual-Rub, Rosni AbdullahProblem statement: Predicting the tertiary structure of proteins from their linear sequence is really a big challenge in biology. This challenge is related to the fact that the traditional computational methods are not powerful enough to search for the correct structure in the huge conformational space. This inadequate capability of the computational methods, however, is a major obstacle in facing … …Journal of Computer Science, Vol. 4, Issue 9 · 30 Sep 2008 · 6,877 accessesView PDFCite
Research ArticleOpen accessIn the abstractStochastic Inflow Simulation for Searching Rule CurvesAnongrit Kangrang, Anujit Phumphan, Witsanukorn ChaiyapoomRule curves are basic monthly guidelines for long term reservoir operation. Generally, the optimal rule curves are searched by reservoir simulation model and optimization techniques. A traditional reservoir simulation does not consider the risk of reservoir operation caused by natural uncertainty from inflow. A stochastic simulation model embedded genetic algorithm model is developed for searching the optimal rule curves in … …American Journal of Applied Sciences, Vol. 5, Issue 3 · 31 Mar 2008 · 7,303 accessesView PDFCite
Research ArticleOpen accessIn the abstractSpeedup of Particle Transport Problems with a Beowulf ClusterZhongxiang Zhao, G. Ivan MaldonadoThe MCNP code is a general Monte Carlo N-Particle Transport program that is widely used in health physics, medical physics and nuclear engineering for problems involving neutron, photon and electron transport[1]. However, due to the stochastic nature of the algorithms employed to solve the Boltzmann transport equation, MCNP generally exhibits a slow rate of convergence. In fact, engineers and scientists … …American Journal of Applied Sciences, Vol. 3, Issue 8 · 31 Dec 2006 · 6,918 accessesView PDFCite