Search Results - (( data evaluation method algorithm ) OR ( variable extraction utilizing algorithm ))
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1
Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients
Published 2017“…The proposed method is based on a hybrid method integrating random walkers algorithm with integrated priors and particle swarm optimized spatial fuzzy c-means (FCM) algorithm with level set method and AdaBoost classifier. …”
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2
High-Resolution Downscaling with Interpretable Relevant Vector Machine: Rainfall Prediction for Case Study in Selangor
Published 2024“…The Principal Component Analysis (PCA) technique was employed to choose relevant environmental variables as input for the machine learning model, and various imputation methods were utilized to manage missing data, such as mean imputation and the KNN algorithm. …”
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3
Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease
Published 2021“…In an imbalanced dataset, one of the two classes contains fewer total samples than the other class. The sampling-based method, also known as the data level method, is used to deal with this problem. …”
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4
Oil palm female inflorescences anthesis stages identification using selected emissivities through thermal imaging and Machine Learning
Published 2022“…This research studies different Machine Learning (ML) classification and ensemble techniques for the assessment of the four pollination stages consist of pre-anthesis I, pre-anthesis II, pre-anthesis III, and anthesis using thermal imaging. Different ML algorithms such as Random Forest (RF), k Nearest Neighbor (kNN), Support Vector Machine (SVM), Artificial Neural Network (ANN) as well as an ensemble method are used on data extracted from thermal images collected during infield oil palms pollination stages monitoring. …”
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5
Development of an effective clustering algorithm for older fallers
Published 2022“…The purpose of this study was, therefore, to develop a clustering-based algorithm to determine falls risk. Data from the Malaysian Elders Longitudinal Research (MELoR), comprising 1411 subjects aged ≥55 years, were utilized. …”
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6
Augmentation of basic-line-search and quick-simplex-method algorithms to enhance linear programming computational performance
Published 2021“…Through the application of LP, the industries able to foresee and consider particular constraints such as restrictions or variability in requirements prior to the actual resources utilization. …”
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An Enhanced Hybrid Method Using AES Algorithm And Arabic Text Steganography
Published 2024thesis::master thesis -
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Case Slicing Technique for Feature Selection
Published 2004“…Since the 1960s, many algorithms for data classification have been proposed. …”
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9
Adaptive grid-meshed-buffer clustering algorithm for outlier detection in evolving data stream
Published 2023“…Existing clustering algorithms for outlier detection encounter significant challenges due to insufficient data pre-processing methods and the absence of a suitable data summarization framework for effective data stream clustering. …”
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10
Evaluation of multiple In Situ and remote sensing system for early detection of Ganoderma boninense infected oil palm
Published 2018“…This study concluded that remote sensing approach combined with data mining approaches such as ANN algorithms have great potential in monitoring vast plantation areas in a rapid and inexpensive manner.…”
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11
Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…The proposed algorithm is used as a pre-processing method for data followed by Gustafson-Kessel (GK) algorithm to classify credit scoring data. …”
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12
Hybrid performance measures and mixed evaluation method for data classification problems
Published 2012“…In fact, no previous studies employ mixed evaluation method in evaluating and comparing the performance measures. …”
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13
Performance evaluation of different data aggregation algorithms for different types of sensors in WSN based cluster
Published 2018“…In this project three different data aggregation algorithms coding schemes based relative difference (CS-RD), an adaptive method of data aggregation that exploits the spatial correlation between the sensor nodes (ADAM) and coding schemes based the factor of precision (CS-FP) are evaluated. …”
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14
Evaluating power efficient algorithms for efficiency and carbon emissions in cloud data centers: a review
Published 2015“…Higher power demand in data centers and changes in computing technology together to maximize data center performance has led to deploying multitude methods to estimate power intensity. …”
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15
Evaluation of Lightning Current Using Inverse Procedure Algorithm.
Published 2013“…In order to validate the proposed method, a set of measured electromagnetic fields are applied on proposed algorithm and the evaluated currents are compared to the corresponding measured current as well as the results are discussed accordingly. …”
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16
Shunt active power filter using hybrid fuzzy-proportional and crisp-integral control algorithms for total harmonic distortion improvement
Published 2016“…Utilization of soft-computing algorithms in the operation of Shunt Active Power Filters (SAPFs) becomes a latest trend. …”
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17
Data depublication using : Hashing algorithm / Naimah Nayan
Published 2019“…The recommendation for future work is to evaluate various type of data and different type of hashing algorithm.…”
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18
Parameter extraction of single, double, and three diodes photovoltaic model based on guaranteed convergence arithmetic optimization algorithm and modified third order Newton Raphso...
Published 2022“…Extraction of the photovoltaic (PV) model parameters is critical for forecasting these systems’ energy output. …”
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19
Neural Networks Ensemble: Evaluation of Aggregation Algorithms for Forecasting
Published 2013“…The results of the aggregation algorithms of NNs ensemble are also compared with the Simple Averaging method. …”
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20
Missing Value Imputation for PM10 Concentration in Sabah using Nearest Neighbour Method(NNM) and Expectation-Maximization (EM) Algorithm
Published 2020“…To fill in missing data, Nearest Neighbour Method(NNM) and Expectation Maximization(EM) algorithm are the two most widely used methods. …”
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