Search Results - (( probable estimation methods algorithm ) OR ( rainfall estimation methods algorithm ))
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The use of radar-rainfall inputs for quantitative precipitation estimation (QPE) in Klang River Basin / Suzana Ramli
Published 2015“…The average value for root mean square error (RMSE) also reduced from 89.90 to 20.30 while the bias denotes average error reduction from 3.20 to 1.22.The improved radar rainfall as quantitative precipitation estimation (QPE) has also been applied in the rainfall-runoff modeling with grid-based Soil Conservation Service Curve Number (SCS-CN) method and GIS utilization. …”
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Simulation algorithm of bayesian approach for choice-conjoint model
Published 2011“…Therefore this research propose simulation algorithm of Bayesian approach for estimating parameter in MPM by Bayesian analysis to avoid computational difficulties in computing the maximum likelihood estimates (MLE).…”
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Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…The rank-based methods, estimating algorithms, and resampling techniques that are developed do not involve the difficulties of the existing estimating procedures. …”
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Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model
Published 2023Conference Paper -
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Tree-based contrast subspace mining method
Published 2020“…Then, the tree-based method, the genetic algorithm based parameter values identification of tree-based method, and followed by the genetic algorithm based tree-based method, for numerical data sets are developed and evaluated. …”
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The research on the signal source number estimation algorithm
Published 2024“…The experimental results show that with the increase of the SNR and the number of array elements, the correct estimation probability of the algorithm also increases correspondingly, which provides a reliable experimental basis and performance evaluation for the estimation. © 2024 Institute of Advanced Engineering and Science. …”
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High-Resolution Downscaling with Interpretable Relevant Vector Machine: Rainfall Prediction for Case Study in Selangor
Published 2024“…This study concluded that Relevance Vector Machine (RVM) models are suitable for forecasting future rainfall since they can support large rainfall extremes and generate reliable daily rainfall estimates based on rainfall extremes. …”
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Prediction of Temerloh River water level for prediction of flood using Artificial Neural Network (ANN) method
Published 2015“…The research will be trained using back propagation method to estimate the flood water level at Temerloh River. …”
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Undergraduates Project Papers -
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Real-Time Flood Inundation Map Generation Using Decision Tree Machine Learning Method: Case Study of Kelantan River Basins
Published 2024“…Therefore, flash flood and short-term flood prediction require numerical rainfall estimation, which employs falls, mudflow, melted ice, etc. …”
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Color Image Segmentation Based on Bayesian Theorem for Mobile Robot Navigation
Published 2009“…The estimation of unknown PDF is a common problem and in this study Gaussian kernel function which is most widely used nonparametric density estimation method has been used for PDF calculation. …”
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Estimation of transformers health index based on condition parameter factor and hidden Markov model
Published 2018“…Next, the emission probabilities for each of the condition parameter factors were derived based on frequency of occurrence method. …”
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Outlier detection in circular regression model using minimum spanning tree method
Published 2019“…Then, the performances of both algorithms were measured using “success” probability. …”
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…These algorithms are inspired by the estimation capability of the well-known Kalman filter estimation method. …”
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Some families of count distributions for modelling zero-inflation and dispersion / Low Yeh Ching
Published 2016“…For parameter estimation, the simulated annealing global optimization routine and an EM-algorithm type approach for maximum likelihood estimation are studied. …”
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Particle swarm optimization for NARX structure selection application on DC motor model: article / Mohd I. Abdullah
“…This paper presents the nonlinear identification of a DC motor using Binary Particle Swarm Optimization (BPSO) algorithm, as a model structure selection method, replacing the typical Orthogonal Least Squares (OLS) used in system identification. …”
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