Search Results - (( based evaluation method algorithm ) OR ( variable extraction utilizing algorithm ))
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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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Development of sorting system for oil palm in vitro shoots using machine vision approach
Published 2014“…By using k-means algorithm the extracted features have been evaluated. …”
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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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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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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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Standardizing and weighting the evaluation criteria of many-objective optimization competition algorithms based on fuzzy delphi and fuzzy-weighted zero-inconsistency methods
Published 2021“…Thus, this research aims to standardize and weigh the evaluation criteria of MaOO competitive algorithms base on fuzzy Delphi and new fuzzy-weighted zero-inconsistency (FWZIC) methods. …”
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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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Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…However, the complexity of the kmedoid based algorithms in general is more than the complexity of the k-means based algorithms. …”
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Case Slicing Technique for Feature Selection
Published 2004“…This technique with k = 10 has been used in this thesis to evaluate the proposed approach. CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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Sudoku Generator based on hybrid algorithm / Faridah Abdul Rahman
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Hybrid subjective evaluation method using weighted subsethood - based (WSBA) rule generation algorithm
Published 2013“…The use of fuzzy rules, which were extracted directly from input data through Weighted Subsethood-based (WSBA) Rule Generation Algorithm.WSBA rule generation use the subsethood values to generate the weights which finally produced the fuzzy general rules.The rules generated through the data provided knowledge in developed fuzzy rule The fuzzy rules embedded in the framework of subjective evaluation method showed advantages in generalizing the evaluation of the performance achievement, where the evaluation process can be conducted consistently in producing good evaluation results with the use of the membership set score.The results from the numerical examples are comparable to other fuzzy evaluation methods, even with the use of small rule size.…”
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A Systematic Literature Review of Machine Learning Methods for Short-term Electricity Forecasting
Published 2023Conference Paper -
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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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Multi-base number representation in application to scalar multiplication and pairing computation
Published 2011“…Multi-bases number representation is used to construct new versions of Miller’s algorithm. …”
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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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Evaluation of Lightning Current Using Inverse Procedure Algorithm.
Published 2013“…In this study an inverse procedure algorithm is proposed in the time domain to evaluate lightning return stroke current based on measured electromagnetic fields at an observation point. …”
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Modified Contrast Limited Adaptive Histogram Equalization for high dynamic range images
Published 2012“…The algorithm was written by using MATLAB software. The local tone mapping method is based on the modified contrast limited adaptive histogram equalization (CLAHE) method. …”
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Evaluation of dynamic programming among the existing stereo matching algorithms
Published 2015“…The dynamic programming algorithm used on this research is the current method as its disparity estimates at a particular pixel and all the other pixels unlike the old methods which with scanline based of dynamic programming. …”
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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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