Search Results - (( model validation max algorithm ) OR ( level classification _ 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“…As the ALOS PALSAR-2 image was evaluated with dual-polarization (HH and HV), each digitized point has two distinct backscatter data with four severity levels (T0 to T3). The machine learning algorithm consistently performs well when presented with a well-balanced dataset. …”
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Thesis -
2
Modern fuzzy min max neural networks for pattern classification
Published 2019“…Among these algorithms, Fuzzy Min Max (FMM) neural network algorithm has been proven to be one of the premier neural networks for undertaking the pattern classification problems. …”
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An improvement of stochastic gradient descent approach for mean-variance portfolio optimization problem
Published 2021“…Furthermore, the applicability of SGD, Adam, AdaMax, Nadam, AMSGrad, and AdamSE algorithms in solving the mean-variance portfolio optimization problem is validated.…”
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak
Published 2019“…It involves development of Max-Min Rule-Based Classification Algorithm. The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. …”
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5
MBIST implementation and evaluation in FPGA based on low-complexity March algorithms
Published 2024“…In addition, their fault detection abilities were also validated through tests on a fault-injected memory model, which shows that the implemented March AZ1 and March AZ2 provide 80.6% and 83.3% coverage of the intended faults, respectively, which outperform any other existing 14N-complexity March algorithms.…”
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Quality of service management algorithms in WiMAX networks
Published 2015“…In addition, an analytical model for the proposed scheme is developed. Secondly, a Load-Aware Weighted Round Robin algorithm (LAWRR) packet scheduling discipline for downlink traffic in 802.16 networks is proposed to improve the poor performance of scheduling algorithm that use static weights under bursty traffic. …”
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7
Multi-Class Multi-Level Classification of Mental Health Disorders Based on Textual Data from Social Media
Published 2024“…The results of the experiments show that the MCML classification algorithm successfully performs detailed classification and produces promising results for each classification level. …”
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Symmetric Key Size for Different Level of Information Classification
Published 2006“…Confidential information can be categorized into various levels of classification. The classification depends on the level of damage to an organization or to national security when the information is disclosed. …”
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Conference or Workshop Item -
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Enhanced handover decision algorithm in heterogeneous wireless network
Published 2017“…Finally, the simulation results are validated by the analytical model.…”
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Self-calibration algorithm for a pressure sensor with a real-time approach based on an artificial neural network
Published 2018“…To verify the proposed model’s capability to build a self-calibration algorithm, the model was tested using an untrained input data set. …”
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Minimizing Classification Errors in Imbalanced Dataset Using Means of Sampling
Published 2023“…Classification (of information); Learning algorithms; Students; Class imbalance; Data level; Over sampling; Performance prediction; SMOTE; Spread subsampling; Student performance; Student performance prediction; Under-sampling; Machine learning…”
Conference Paper -
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Machine learning for mapping and forecasting poverty in North Sumatera: a datadriven approach
Published 2024“…Thus, there were three poverty clusters - low, medium, and high - that were used in the model. The best model was created using the grid search cross-validation, while the best prediction results were created using the RF algorithm, with the following parameters: n-estimator = 50, max depth = 10, min samples split = 2, and min samples leaf = 1. …”
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Performance analysis of machine learning algorithms for classification of infection severity levels on rubber leaves
Published 2023“…This work shows that the spectroscopic measurement combined with classification techniques are promising strategy to classify severity level of WRD based on the spectral data of the rubber leaves.…”
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Book Section -
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Real time self-calibration algorithm of pressure sensor for robotic hand glove system
Published 2019“…This work shows that the Proposed model exhibited a remarkable performance than traditional methods with a max MSE of 0.17325 and R value over 0.99 for the total response of training, testing and validation. …”
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Malaysian license plate recognition system using Convolutional Neural Network (CNN) on web application / Nur Farahana Mahmud
Published 2022“…Based on the results obtained, the trained CNN model was able to achieve an accuracy of 97.11% for training and 96.76% for validation, respectively. …”
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Student Project -
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Automatic classification of medical x-ray images
Published 2013“…These features have been exploited in different algorithms for automatic classification of medical X-ray images. …”
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Data Mining Analysis Of Chronic Kidney Disease (CKD) Level
Published 2022“…The ZeroR algorithm was set as the baseline There are three levels of classification analyses: before and after handling the missing values, before and after the outliers’ treatment, and adding uncertain classes. …”
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Monograph -
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Correlation Feature Selection Weighting Algorithms for Better Support Vector Classification: An Empirical Study
Published 2020“…Prediction and/or classification accuracies of cfsw-SVM algorithms are significantly improved.…”
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Arabic text classification using hybrid feature selection method using chi-square binary artificial bee colony algorithm
Published 2021“…Chi-square, a filter method that is computationally fast, simple and has the ability to deal with a large dimensional feature, is used as the first level of the feature selection process. After that, the wrapper method, Artificial Bee Colony algorithm, is used as the second level where Naive Base is used as a fitness function. …”
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