Search Results - data distribution ((using algorithm) OR (((learning algorithm) OR (matching algorithm))))
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Hierarchical Bayesian estimation for stationary autoregressive models using reversible jump MCMC algorithm
Published 2018“…The performance of the algorithm is tested by using simulated data. The test results show that the algorithm can estimate the order and coefficients of the autoregressive model very well. …”
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Mapping the distribution of oil palm using Landsat 8 data by comparing machine learning and non-machine learning algorithms
Published 2019“…Hence, the mapping of oil palm distributions via machine learning algorithm was better than that via non-machine learning algorithm.…”
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The application of voltage sags pattern to locate a faulted section in distribution network
Published 2010“…This paper proposes an alternative automated fault location algorithm to locate a faulted section in distribution network using only voltage sag data monitored at the primary substation. …”
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Fault location estimation for distribution system using simulated voltage sags data
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Inference Algorithms in Latent Dirichlet Allocation for Semantic Classification
Published 2018“…However, the problem of learning or inferencing the posterior distribution of the algorithm is trivial. …”
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Inference Algorithms in Latent Dirichlet Allocation for Semantic Classification
Published 2018“…However, the problem of learning or inferencing the posterior distribution of the algorithm is trivial. …”
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Classification of diabetic patients with imbalanced class distribution by using a Cost-Sensitive forest algorithm / Ummi Asyiqin Che Muhammad and Muhammad Hasbullah Mohd Razali
Published 2023“…Although many machine learning algorithms have been developed by researchers, the class imbalanced distribution still makes it challenging for classifiers to properly learn and differentiate between the minority and majority classes. …”
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Book Section -
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Comparative performance of deep learning and machine learning algorithms on imbalanced handwritten data
Published 2018“…The experiment shows that although the algorithm is stable and suitable for multiple domains, the imbalanced data distribution still manages to affect the outcome of the conventional machine learning algorithms.…”
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Supervised deep learning algorithms for process fault detection and diagnosis under different temporal subsequence length of process data
Published 2025“…Deep learning algorithms were widely used among all the data-driven algorithms. …”
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Machine learning in botda fibre sensor for distributed temperature measurement
Published 2023“…An alternative method is proposed, utilizing machine learning algorithms. Therefore, this thesis explores the comparative analysis for BOTDA data processing using the six most suited machine learning algorithms. …”
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Technical job distribution at BSD SHARP service center using combination of naïve Bayes and K-Nearest neighbour
Published 2022“…Meanwhile, k-NN algorithm is used to classify the experimental data. …”
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Enhanced Q-Learning algorithm for potential actions selection in automated graphical user interface testing
Published 2023“…To overcome this limitation, the Q-Learning algorithm was proposed by several researchers to minimise randomness. …”
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Measuring height of high-voltage transmission poles using unmanned aerial vehicle (UAV) imagery
Published 2017“…Results were compared with well-known algorithms; including, for example, global and local stereo matching algorithms. …”
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Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm
Published 2025“…Parallel power loads anomalies are processed by a fast-density peak clustering technique that capitalizes on the hybrid strengths of Canopy and K-means algorithms all within Apache Mahout's distributed machine-learning environment. …”
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Minimizing Classification Errors in Imbalanced Dataset Using Means of Sampling
Published 2023Conference Paper -
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CONTEXT AWARE TRAFFIC SCHEDULING ALGORITHM FOR COMMUNICATION SYSTEM IN POWER DISTRIBUTION NETWORK
Published 2023text::Thesis -
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Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks
Published 2023“…The intrusion detection evaluation dataset (CICIDS2017) is used to provide more realistic detection. The CICIDS2017 dataset includes benign and up-to-date examples of typical attacks, closely matching real-world data of Packet Capture. …”
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Deep learning in distributed denial-ofservice attacks detection method for Internet of Things networks
Published 2023“…The intrusion detection evaluation dataset (CICIDS2017) is used to provide more realistic detection. The CICIDS2017 dataset includes benign and up-to-date examples of typical attacks, closely matching real-world data of Packet Capture. …”
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