Search Results - ((((new algorithm) OR (learning algorithm))) OR (means algorithm))

Max-D clustering K-means algorithm for Autogeneration of Centroids and Distance of Data Points Cluster by Wan Maseri, Wan Mohd, Beg, Abul Hashem, Tutut, Herawan, K., F.Rabbi

“…K-Means is one of the unsupervised learning and partitioning clustering algorithms. …”
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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 first research objective is to develop a new deep learning algorithm by a hybrid of DNN and K-Means Clustering algorithms for estimating the Lorenz chaotic system. …”
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MaxD K-Means: A clustering algorithm for auto-generation of centroids and distance of data points in clusters by Wan Maseri, Wan Mohd, Beg, Abul Hashem, Herawan, Tutut, Fazley Rabbi, Khandakar

“…K-Means is one of the unsupervised learning and partitioning clustering algorithms. …”
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Quantifying usability prioritization using K-means clustering algorithm on hybrid metric features for MAR learning by Lim K.C., Selamat A., Mohamed Zabil M.H., Selamat M.H., Alias R.A., Puteh F., Mohamed F., Krejcar O.

“…Augmented reality; Learning algorithms; Machine learning; Usability engineering; Between clusters; Mobile augmented reality; Prioritization; Prioritization techniques; Unsupervised machine learning; Usability; K-means clustering…”

Coordinate-Descent Adaptation over Hamiltonian Multi-Agent Networks by Azam Khalili, Vahid Vahidpour, Amir Rastegarnia, Ali Farzamnia, Teo, Kenneth Tze Kin, Saeid Sanei

“…The incremental least-mean-square (ILMS) algorithm is a useful method to perform distributed adaptation and learning in Hamiltonian networks. …”
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The new efficient and accurate attribute-oriented clustering algorithms for categorical data by Qin, Hongwu

“…This work firstly reveals the significance of attributes in categorical data clustering, and then investigates the limitations of algorithms MMR and G-ANMI respectively, and correspondingly proposes a new attribute-oriented hierarchical divisive clustering algorithm termed Mean Gain Ratio (MGR) and an improved genetic clustering algorithm termed Improved G-ANMI (IG-ANMI) for categorical data. …”
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm by Manoharan P., Ravichandran S., Kavitha S., Tengku Hashim T.J., Alsoud A.R., Sin T.C.

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An improved self organizing map using jaccard new measure for textual bugs data clustering by Ahmed, Attika

“…For the purpose of clustering, a variety of clustering algorithms available. One of the commonly used algorithm for bug clustering is K-means, which is considered a simplest unsupervised learning algorithm for clustering, yet it tends to produce smaller number of cluster. …”
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An improved self organizing map using jaccard new measure for textual bugs data clustering by Ahmed, Attika

“…For the purpose of clustering, a variety of clustering algorithms available. One of the commonly used algorithm for bug clustering is K-means, which is considered a simplest unsupervised learning algorithm for clustering, yet it tends to produce smaller number of cluster. …”
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A modified generalized RBF model with EM-based learning algorithm for medical applications by Ma, Li Ya, Abdul Rahman, Abdul Wahab, Quek, Chai

“…Moreover, GRBF trained by the new algorithm has an apparent statistical meaning. …”
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Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman by Seman, Ali

“…The idea was incorporated into a new algorithm called, k-Approximate Modal Haplotypes (&-AMH) algorithm. …”
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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

“…Data clustering is one of the most popular branches in machine learning and data analysis. Partitioning-based type of clustering algorithms, such as K-means, is prone to the problem of producing a set of clusters that is far from perfect due to its probabilistic nature. …”
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Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

“…Unlike the classical kNN algorithm which is a regression type algorithm, the proposed localisation algorithms utilise machine learning classification for both linear and kernel types. …”
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Detection and Monitoring of Power Line Corridor from Satellite Imagery Using RetinaNet and K-Mean Clustering by Haroun F.M.E., Deros S.N.M., Din N.M.

“…Antennas; Deep learning; Electric power transmission; K-means clustering; Satellite imagery; Unmanned aerial vehicles (UAV); Vegetation; Airborne photography; Current monitoring; Electrical transmission; Identification algorithms; K-mean clustering; K-mean clustering algorithm; Monitoring system; Power interruptions; Monitoring…”

An efficient fuzzy C-least median clustering algorithm by Mallik, Moksud Alam, Zulkurnain, Nurul Fariza, Nizamuddin, Mohammed Khaja, Aboosalih, K C

“…In this paper we are discussing our new procedure for clustering called Fuzzy C-least median of squares algorithm which is an improvement to Fuzzy C-means (FCM) algorithm. …”
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Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Predicting Reservoir Water Level by Sammen S.S., Ehteram M., Sheikh Khozani Z., Sidek L.M.

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Adaptive learning for lemmatization in morphology analysis by Ting, Mary, Abdul Kadir, Rabiah, Tengku Sembok, Tengku Mohd, Ahmad, Fatimah, Azman, Azreen

“…Even with technology advancement, yet none of the available lemmatization algorithms able to produce 100 % accurate result. The base words produced by the current algorithm might be unusable as it alters the overall meaning it tried to represent, which will directly affect the outcome of NLP systems. …”
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The effect of adaptive parameters on the performance of back propagation by Abdul Hamid, Norhamreeza

“…The results show that the proposed algorithm extensively improves the learning process of conventional Back Propagation algorithm.…”
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Dynamic Bayesian Networks and Variable Length Genetic Algorithm for Dialogue Act Recognition by Ali Yahya, Anwar

Subjects: “…Machine learning.…”
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A New Unsupervised Validation Index Model Suitable for Energy-Efficient Clustering Techniques in VANET by Abdulrazzak H.N., Hock G.C., Mohamed Radzi N.A., Tan N.M.L.

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