Search Results - (( parameter optimization method algorithm ) OR ( data classification means algorithm ))

Taylor-Bird Swarm Optimization-Based Deep Belief Network For Medical Data Classification by Mohammed, Alhassan Afnan

“…However, finding the most appropriate deep learning algorithm for a medical classification problem along with its optimal parameters becomes a difficult task. …”
Get full text
Get full text

A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…Hybridizing the Deep Neural Network (DNN) with the K-Means Clustering algorithm will increase the accuracy and reduce the data complexity of the Lorenz dataset. …”
Get full text
Get full text

Electricity load profile determination by using fuzzy C-means and probability neural network / Norhasnelly Anuar by Anuar, Norhasnelly

“…PNN is a fast training process to do the classification activities. As compared with the backpropagation method in literature review, it gives better result when classifying large data sets. …”
Get full text
Get full text

Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh by Sai , Chong Yeh

“…The training and parameters selection of the machine learning algorithms are conducted using EEG data collected from ten subjects in the laboratory. …”
Get full text
Get full text
Get full text

Hybrid clustering-GWO-NARX neural network technique in predicting stock price by Das, Debashish, Sadiq, Ali Safa, Mirjalili, Seyedali, Noraziah, Ahmad

“…Malaysian Stock Market (Bursa Malaysia), Dhaka Stock Exchange (DSE). It applies K-means clustering algorithm to determine the most promising cluster, then MGWO is used to determine the classification rate and finally the stock price is predicted by applying NARX neural network algorithm. …”
Get full text
Get full text
Get full text

Context enrichment framework for sentiment analysis in handling word ambiguity resolution by Yusof, Nor Nadiah

“…However, ambiguous words pose a challenge for sentiment analysis algorithms as they require the identification of the correct meaning and word polarity within a specific context. …”
Get full text
Get full text

Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach by Mustakim, Nurul Ain

“…The framework uses machine learning methods, including classification, clustering, feature selection, and parameter tuning, to improve accuracy and reliability. …”
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

“…Clustering is one of the means in data mining of predicting the class based on separating the data categories from similar features. …”
Get full text
Get full text
Get full text

Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

“…Methods for improving supervised and unsupervised classification of remotely sensed data were developed in this study. …”
Get full text
Get full text

Improving the tool for analyzing Malaysia’s demographic change: data standardization analysis to form geo-demographics classification profiles using k-means algorithms by Kamarul Ismail, Nasir Nayan, Siti Naielah Ibrahim

“…Clustering is one of the important methods in data exploratory in this era because it is widely applied in data mining.Clustering of data is necessary to produce geo-demographic classification where k-means algorithm is used as cluster algorithm. …”
Get full text
Get full text
Get full text

An improved data classification framework based on fractional particle swarm optimization by Sherwani, Fahad

“…Furthermore, the proposed MOFPSO algorithm is hybridized with Back-Propagation (BP), Elman Recurrent Neural Networks (RNN) and Levenberg-Marquardt (LM) Artificial Neural Networks (ANNs) to propose an enhanced data classification framework, especially for data classification applications. …”
Get full text
Get full text
Get full text
Get full text

Effective k-Means Clustering in Greedy Prepruned Tree-based Classification for Obstructive Sleep Apnea by Sim, Doreen Ying Ying, Ahmad I., Ismail, Chee Siong, Teh

“…GPrTC algorithm showed better classification accuracies than k-means clustering in almost all the assigned datasets. …”
Get full text
Get full text
Get full text

Optimization of turning parameters using genetic algorithm method by Shah Izwandi, Mohd Zawawi

“…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). …”
Get full text
Get full text

MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM by Aurangzeb, khan, Baharum, Baharudin, Khairullah, khan

“…The experimental result shows that the proposed hybrid k-mean plus MFP algorithm can generate more useful pattern from large stock data.…”
Get full text
Get full text

Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis by Asrul, Adam

“…The efficiency of the three algorithms are evaluated and compared with previous results obtained by other optimization methods on similar studies. …”
Get full text
Get full text
Get full text

Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization by Nur Iffah, Mohamed Azmi

“…Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. …”
Get full text
Get full text

Optimization of turning parameters using ant colony optimization by Mohamad Nazri, Semoin

“…The project objectives are to develop Ant Colony Optimization (ACO) algorithm for CNC turning process and to optimize turning parameters for minimized production cost per unit. …”
Get full text
Get full text

Parameter estimation in double exponential smoothing using genetic algorithm / Foo Fong Yeng, Lau Gee Choon and Zuhaimy Ismail by Foo, Fong Yeng, Lau, Gee Choon, Ismail, Zuhaimy

“…Trial and error often serves as the best method to determine the parameter. Therefore, a good optimization technique is required for identify the best parameter in minimizing the forecast errors. …”
Get full text
Get full text

Gas Identi cation by Using a Cluster-k-Nearest-Neighbor by Brahim Belhaouari, samir

“…We find 98.7% of accuracy in the classification of 6 different types of Gas by using K-means cluster algorithm and we find almost the same by using the new clustering algorithm.…”
Get full text
Get full text

Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

“…Phase 1 is mainly to evaluate the performance of clustering algorithm (K-Means and FCM). Phase 2 is to study the performance of proposed integration system which using the data clustered to be used as train data for Naïve Bayes classifier. …”
Get full text
Get full text