Search Results - (( data estimation method algorithm ) OR ( parameter estimation tree algorithm ))
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1
Tree-based contrast subspace mining method
Published 2020“…The research works involve first preparing the real world numerical and categorical data sets. 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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2
Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari
Published 2015“…We derive the maximum likelihood estimation of parameters as well as the variance-covariance of parameters. …”
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3
Real-Time State of Charge Estimation of Lithium-Ion Batteries Using Optimized Random Forest Regression Algorithm
Published 2024“…Hence, a differential search algorithm (DSA) is employed to search for the optimal values of trees and leaves in the RFR algorithm. …”
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4
Application of Decision Tree Algorithm for Predicting Monthly Pan Evaporation Rate
Published 2023Conference Paper -
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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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6
Bayesian random forests for high-dimensional classification and regression with complete and incomplete microarray data
Published 2018“…Random Forests (RF) are ensemble of trees methods widely used for data prediction, interpretation and variable selection purposes. …”
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7
Processing and classification of landsat and sentinel images for oil palm plantation detection
Published 2022“…It first focuses on the correction algorithm needed to estimate the true surface reflectance value of the satellite image data before the image is filtered to reduce any noise. …”
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A comparative study of supervised machine learning approaches for slope failure production
Published 2023“…Generally, slope failure can be estimated based on traditional methods such as limit equilibrium method (LEM) or finite equilibrium method (FEM). …”
Conference Paper -
9
Individual-tree segmentation and extraction based on LiDAR point cloud data
Published 2024“…Specifically, the watershed algorithm achieved a coefficient of determination of 0.88 and an RMSE of 0.93 meters, indicating greater precision in estimating tree parameters. …”
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10
Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor
Published 2017“…This study begins by proposing a robust technique for estimating the slope parameter in LFRM. In particular, the focus is on the non-parametric estimation of the slope parameter and the robustness of this technique is compared with the maximum likelihood estimation and the Al-Nasser and Ebrahem (2005) method. …”
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11
Enhancing time series prediction with Hybrid AFSA-TCN: A unified approach to temporal data and optimization
Published 2025“…Time series data, with its sequential dependencies presents a unique challenge for traditional machine learning methods such as Random Forest (RF), Support Vector Machines (SVM), and Decision Trees (DT), which often struggle to capture temporal patterns effectively. …”
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12
Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram
Published 2021“…The supervised machine learning algorithm, SVM and Decision Tree are used for the estimation of the mangrove age into young and mature. …”
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13
Outlier detection in circular regression model using minimum spanning tree method
Published 2019“…The existence of outliers in a circular regression model can lead to many errors, for example in inferences and parameter estimations. Therefore, this study aims to develop new algorithms that can detect outliers by using the minimum spanning tree method. …”
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14
UAV multispectral image for tree crown delineation of mangifera indica using object based image analysis [OBIA] / Nik Syaza Sahiera Nik Nazmy
Published 2022“…In this study, conventional method was used to derive the parameter and positioned of tree, functioned as reference. …”
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15
Interaction effect of process parameters and Pd-electrocatalyst in formic acid electro-oxidation for fuel cell applications: Implementing supervised machine learning algorithms
Published 2023“…Carbon nanotubes; Electrocatalysts; Electrooxidation; Forestry; Formic acid; Gaussian distribution; Learning algorithms; Palladium; Parameter estimation; Regression analysis; Support vector machines; Formic acid electrooxidation; Fuel cell application; Gaussian kernel functions; Gaussian process regression; Interaction effect; Machine learning algorithms; Performance; Process parameters; Regression trees; Support vector machine regressions; Sensitivity analysis…”
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Differential Search Optimized Random Forest Regression Algorithm for State of Charge Estimation in Electric Vehicle Batteries
Published 2023Conference Paper -
17
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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18
Determination of tree stem volume : A case study of Cinnamomum
Published 2013“…Hence, this research is designed such that the idea of determining the best models and solving their parameters that give the best estimates are conceptualized. …”
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19
Multiple equations model selection algorithm with iterative estimation method
Published 2016“…This estimation method is equivalent to maximum likelihood estimation at convergence. …”
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Electric vehicle battery state of charge estimation using metaheuristic-optimized CatBoost algorithms
Published 2025“…Three distinct metaheuristic algorithms were investigated: Barnacles Mating Optimizer (BMO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Whale Optimization Algorithm (WOA), each integrated with CatBoost to optimize critical parameters including learning rate, tree depth, regularization, and bagging temperature. …”
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