Search Results - (( parameter estimation missing algorithm ) OR ( java application during algorithm ))
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Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor
Published 2017“…This research focuses on the parameter estimation, outlier detection and imputation of missing values in a linear functional relationship model (LFRM). …”
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Estimating Missing Precipitation to Optimize Parameters for Prediction of Daily Water Level Using Artificial Neural Network
Published 2006“…It has been found that the ANN has the potential to solve the problems of estimation missing precipitatio in predicting daily water level. …”
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Final Year Project Report / IMRAD -
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Missing value estimation methods for data in linear functional relationship model
Published 2017“…With the rapid growth of computing capabilities, advanced methods in particular those based on maximum likelihood estimation has been suggested to best handle the missing values problem. …”
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Interpolation and Extrapolation Techniques Based Neural Network in Estimating the Missing Ionospheric TEC Data
Published 2024Proceedings Paper -
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Interpolation and extrapolation techniques based Neural Network in estimating the missing ionospheric TEC data
Published 2024“…A multilayer feed-forward network with a back propagation algorithm is applied to estimate the TEC over Parit Raja (Lat. 1�52?…”
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Modification Of Regression Models To Solve Heterogeneity Problem Using Seaweed Drying Data
Published 2023“…After the heterogeneity parameters were excluded from the model, the support vector machine with the MM estimator showed that better significant results were obtained with 2.09% outliers. …”
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Electric vehicle battery state of charge estimation using metaheuristic-optimized CatBoost algorithms
Published 2025“…This study presents a hybrid approach combining the CatBoost algorithm with metaheuristic optimization techniques to enhance SoC estimation accuracy and robustness. …”
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Crown counting and mapping of missing oil palm tree using airborne imaging system
Published 2019“…The undetected group of missing oil palms trees are estimated based on the planting pattern design. …”
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Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data
Published 2018“…The new procedure called Bayesian Random Forest (BRF) focuses on modification of terminal node parameter estimation and selection of random subsets for splitting. …”
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SUDOKU HELPER
Published 2015“…In this paper research, author presents an algorithm to provide a tutorial for any Sudoku player who got stuck during the solving process. …”
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Final Year Project -
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A generalized mixed model framework for assessing fingerprint individuality in presence of varying image quality
Published 2014“…We develop algorithms based on the Laplace approximation of the likelihood and infer the unknown parameters based on this approximate likelihood. …”
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Designing of skull defect implants using C1 rational cubic Bezier and offset curves
Published 2015“…Its offset curve is used to generate the inner wall. A metaheuristic algorithm, called harmony search (HS) is a derivative-free real parameter optimization algorithm inspired from the musical improvisation process of searching for a perfect state of harmony. …”
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Talkout : Protecting mental health application with a lightweight message encryption
Published 2022“…The investigation of lightweight message encryption algorithms is conducted with systematic quantitative literature and experiment implementation in Java and Android running environment. …”
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Academic Exercise -
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Predicting the maturity and organic richness using artificial neural networks (ANNs): A case study of Montney Formation, NE British Columbia, Canada
Published 2021“…The results of feedforward neural network (FFNN) with back-propagation algorithm and the BR regularization technique for 9 input parameters produced satisfactory performances in TOC prediction (R2 = 94 and 89) in training and validation phases, respectively, and for the Tmax prediction (R2 = 88 and 86) with 5 input parameters in the training and validation phases, respectively. …”
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A malware analysis and detection system for mobile devices / Ali Feizollah
Published 2017“…We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
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