Search Results - (( pattern ((means algorithm) OR (based algorithm)) ) OR ( based learning algorithm ))

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

“…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
Get full text
Get full text

Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

“…In this article, we present the exploration on the combination of the clustering based algorithm with an ensemble classification learning. …”
Get full text
Get full text
Get full text

Social media mining: a genetic based multiobjective clustering approach to topic modelling by Alfred, Rayner, Loo, Yew Jie, Obit, Joe Henry, Lim, Yuto, Haviluddin, Haviluddin, Azman, Azreen

“…This paper investigates the effects of using a multiobjective genetic algorithm (MOGA) based clustering technique to cluster texts for topic extraction which is designed based on the structure and purity of the clusters in order to determine the optimal initial centroids and the number of clusters, k. …”
Get full text
Get full text

Social media mining: a genetic based multiobjective clustering approach to topic modelling by Rayner Alfred, Loo Yew Jie, Joe Henry Obit, Yuto Lim, Haviluddin Haviluddin, Azreen Azman

“…This paper investigates the effects of using a multiobjective genetic algorithm (MOGA) based clustering technique to cluster texts for topic extraction which is designed based on the structure and purity of the clusters in order to determine the optimal initial centroids and the number of clusters, k. …”
Get full text
Get full text
Get full text
Get full text

Music Recommender System Using Machine Learning Content-Based Filtering Technique by Foong, Kin Hong

“…These are the popular algorithm for unsupervised learning, a machine learning method to analyse and cluster datasets. …”
Get full text
Get full text

Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms by Al-Rawashdeh, Mohammad, Al Nawaiseh, Moh’d, Yousef, Isam, Bisharah, Majdi, Alkhadrawi, Sajeda, Al-Bdour, Hamza

“…Bayesian Optimization optimizes machine learning algorithm hyperparameters to solve this problem. …”
Get full text
Get full text

Characterization of water quality conditions in the Klang River Basin, Malaysia using self organizing map and K-means algorithm by Mohd Sharif, Sharifah, Mohd Kusin, Faradiella, Asha’ari, Zulfa Hanan, Aris, Ahmad Zaharin

“…The self organizing map (SOM) combined with the K-means algorithm arranged the data based on the relationships of 25 variables. …”
Get full text
Get full text
Get full text

River flow prediction based on improved machine learning method: Cuckoo Search-Artificial Neural Network by Zanial W.N.C.W., Malek M.B.A., Reba M.N.M., Zaini N., Ahmed A.N., Sherif M., Elshafie A.

Subjects:

Development of an intelligent system using Kernel-based learning methods for predicting oil-palm yield. by Md. Sap, Mohd. Noor, Awan, A. Majid

“…In this paper we present a robust weighted kernel k-means algorithm incorporating spatial constraints for clustering climate data. …”
Get full text
Get full text

Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman by Seman, Ali

“…For the overall performances which were based on the six data sets, the &-AMH algorithm recorded the highest mean accuracy scores of 0.93 as compared to the other algorithms: the ^-Population (0.91), the &-Modes-RVF (0.81), the New Fuzzy &-Modes (0.80), A:-Modes (0.76), &-Modes-HI (0.76), £-Modes- HII (0.75), Fuzzy £-Modes (0.74) and £-Modes-UAVM (0.70). …”
Get full text
Get full text

Simple quantum circuit for pattern recognition based on nearest mean classifier by Mahmoud Ahmed, Gharib Subhi, Messikh Azeddine, Azeddine

“…Classification is one subcategory under machine learning. In this paper we propose a simple quantum circuit based on the nearest mean classifier to classified handwriting characters. …”
Get full text
Get full text

Embedded car plate image recognition system by Moo Wui Hung

Get full text

A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition by Babiker, Elsadig Ahmed Mohamed

“…A vector quantization model that incorporate rough sets attribute reduction and rules generation with a modified version of the K-means clustering algorithm was developed, implemented and tested as a part of a speech recognition framework, in which the Learning Vector Quantization (LVQ) neural network model was used in the pattern matching stage. …”
Get full text
Get full text

Evaluation of deep learning algorithm for inflow forecasting: a case study of Durian Tunggal Reservoir, Peninsular Malaysia by Latif S.D., Ahmed A.N., Sathiamurthy E., Huang Y.F., El-Shafie A.

Cabbage disease detection system using k-NN algorithm by Mohamad Ainuddin Sahimat

“…It is a method of extracting second-order statistical texture features to detect diseases more efficiently. Finally, the KNN algorithm will be used to classify the disease based on sample nature and a cabbage disease data set. …”
Get full text
Get full text
Get full text

A pattern based approach for the derivation of base forms of verbs from participles and tenses for flexible NLP by Raj, R.G., Abdul-Kareem, S.

“…As such we present an algorithm to derive the base verb from any participle or tense.…”
Get full text
Get full text
Get full text

Self learning neuro-fuzzy modeling using hybrid genetic probabilistic approach for engine air/fuel ratio prediction by Al-Himyari, Bayadir Abbas

“…The model was compared to other learning algorithms for NFS such as Fuzzy c-means (FCM) and grid partition algorithm. …”
Get full text
Get full text
Get full text

Characterization of oil palm fruitlets using artificial neural network by Olukayode, Ojo Adedayo

“…To further validate the generalization accuracy of the LSB_ANN, its performance was compared with that of a Multi-ANFIS network as well as those of three different ANN training algorithms: Levenberg Marquardt (LM) algorithm, Resilient Backpropagation (RP) algorithm and Gradient Descent with Adaptive learning rate (GDA). …”
Get full text
Get full text

The enhanced BPNN-NAR and BPNN-NARMA models for Malaysian aggregate cost indices with outlying data by Ahmad Kamaruddin, Saadi, Md Ghani, Nor Azura, Mohamed Ramli, Norazan

“…In theory, the most common training algorithm for Backpropagation algorithms leans on reducing ordinary least squares estimator (OLS) or more specifically, the mean squared error (MSE). …”
Get full text
Get full text
Get full text
Get full text

A framework of modified adaptive neuro-fuzzy inference engine by Hossen, Md. Jakir

“…This thesis proposes a framework of modified adaptive neuro-fuzzy inference engine (MANFIE) for a diversity of practical applications in order to resolve the benchmark problems of a large number of inputs datasets. A modified apriori algorithm was employed to reduce the number of clusters effectively on the basis of common data in the clusters of every input to obtain a minimal set of decision rules based on datasets. …”
Get full text
Get full text