Search Results - ((((testing algorithms) OR (learning algorithms))) OR (clustering algorithm))

Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

Subjects: “…Genetic algorithms…”
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A new variant of black hole algorithm based on multi population and levy flight for clustering problem by Haneen Abdul Wahab, Abdul Raheem

“…The obtained results were compared with the BH and previous optimization algorithms for both test functions as well as data clustering in terms of normal and high dimensional datasets. …”
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An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis by Tie, K. H., A., Senawi, Chuan, Z. L.

“…The k-means and the Gaussian mixture distribution were adopted as the clustering algorithms and each algorithm was tested on four datasets with four distinct clustering evaluation criteria: Calinski-Harabasz, Davies-Bouldin, Gap and Silhouette. …”
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Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman by Seman, Ali

“…A One-Way ANOVA test also indicated that the clustering accuracy scores of &-AMH algorithm was significantly different as compared to the other eight partitional algorithms. …”
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Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

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Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohamad Fadhil, Abas, Bayuaji, Luhur

“…To solve the issue of parameter estimation for a chaotic system, deep learning is utilized. After that, it has been suggested to improve the efficiencies in the Deep Neural Network (DNN) model by combining the DNN with an unsupervised machine learning algorithm, the K-Means clustering algorithm. …”
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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Nature inspired data mining algorithm for document clustering in information retrieval by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

“…The newly proposed clustering algorithm, known as GFA_R, is then tested on a benchmark dataset obtained from the 20Newsgroups. …”
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An enhanced version of black hole algorithm via levy flight for optimization and data lustering problems by Haneen, Abd Wahab, Noraziah, Ahmad, Alsewari, Abdulrahman A., Sinan, Q. Salih

“…The experimental outcomes obtained indicated the designed algorithm’s suitability for data clustering, displaying effectiveness and robustness.…”
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An enhanced version of black hole algorithm via levy flight for optimization and data clustering problems by Abdulwahab, Haneen A., Noraziah, Ahmad, Al-Sewari, Abdul Rahman Ahmed Mohammed, Salih, Sinan Q.

“…The experimental outcomes obtained indicated the designed algorithm's suitability for data clustering, displaying effectiveness and robustness.…”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. …”
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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

“…Based on the above components and circumstances, many studies have been performed on data clustering problems. Despite attempts to solve the data clustering issues, there are also many variants of modified algorithms in traditional information clustering that attempt to solve issues such as clustering algorithms based on condensation. …”
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Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

“…The overall performances of the three proposed frameworks have been compared with several current state-of-the-art clustering algorithms on 15 benchmark datasets from the UCI repository. …”
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Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed by Borujeni, Sattar Chavoshi

“…Among the available learning algorithms in the Neural Network Toolbox of MATLAB, three algorithms, gradient descent back propagation (TRAINGD), gradient descent with adaptive learning rule back propagation (TRAINGDA) and the Levenberg-Marquardt (TRAINLM) were studied. …”
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K-means Clustering Analysis for EEG Features of Situational Interest Detection in Classroom Learning by Othman, E.S., Faye, I., Babiker, A., Hussaan, A.M.

“…This paper proposes a method to detect situational interest in classroom learning using k-means algorithms. The developed algorithm in this paper had been tested on features from ten students who experienced mathematics learning in a classroom. …”
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Alternate methods for anomaly detection in high-energy physics via semi-supervised learning by Md. Ali, Mohd. Adli, Badrud’din, Nu’man, Abdullah, Hafidzul, Kemi, Faiz

“…In this paper, we introduce two new algorithms called EHRA and C-EHRA, which use machine learning regression and clustering to detect anomalies in samples. …”
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Density based subspace clustering: a case study on perception of the required skill by Rahmat Widia, Sembiring

“…Each dimension will be tested to investigate whether having a relationship with the data on another cluster, using proposed subspace clustering algorithms. …”
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Density subspace clustering: a case study on perception of the required skill by Sembiring, Rahmat Widia

“…Each dimension will be tested to investigate whether having a relationship with the data on another cluster, using proposed subspace clustering algorithms. …”
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Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

“…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. …”
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Support Vector Machines (SVM) in Test Extraction by Ghazali, Nadirah

“…This project's objective is to create a summarizer, or extractor, based on machine learning algorithms, which are namely SVM and K-Means. …”
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