Search Results - (( data replication method algorithm ) OR ( using factorization learning algorithm ))

A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification by Talpur, N., Abdulkadir, S.J., Hasan, M.H., Alhussian, H., Alwadain, A.

“…Additionally, the Wilcoxon rank test was used to perform the significance analysis between the proposed SCSOKNN method and six other algorithms for a p-value less than 5.00E-02. …”
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A Novel Path Prediction Strategy for Tracking Intelligent Travelers by Motlagh, Omid Reza Esmaeili

“…The FCM nodes are a novel selection of kinematical factors. Genetic algorithm (GA) is then used to train the FCM to be able to replicate the decisional behaviors of the intelligent traveler. …”
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Assessment of suitable hospital location using GIS and machine learning by Almansi, Khaled Y. M.

“…First, the conditioning factors were optimized and ranked to identify and select the most correlated factors to predict the suitability of a hospital site by applying the correlation feature selection (CFS) algorithm and the greedy-stepwise search method. …”
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Dynamic replication algorithm in data grid: Survey by K. Madi, Mohammed, Hassan, Suhaidi

“…For improving the performance of file accesses and to ease the sharing amongst distributed collaboration, such a system needs replication services. Data replication is a common method used to improve the performance of data access in distributed systems. …”
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Enhanced replication strategy with balanced quorum technique and data center selection method in cloud environment by Mohd Ali, Fazlina

“…In order to mitigate the issues, ‘cloud data replication’ is commonly implemented for better data performance and promising business continuity. …”
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Development of a hybrid machine learning model for rockfall source and hazard assessment using laser scanning data and GIS by Fanos, Ali Mutar

“…This indicates that the model can be generalized and replicated in different regions and the proposed method can be applied in various landslides studies. …”
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Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system by Beg, Abul Hashem

“…The motivation of implementation is to make sure the data replication is easy to maintain and cost effective. …”
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Exploration of machine learning forecasting methods in M4 competition / Muhammad Halim Hamdan and Shuzlina Abdul-Rahman by Hamdan, Muhammad Halim, Abdul-Rahman, Shuzlina

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Managing fragmented database in distributed database environment / Ainul Azila Che Fauzi ... [et al.] by Che Fauzi, Ainul Azila, Wan Abdul Rahman, Wan Fariza, Fauzi, Auni, Weigelt, Florian

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Enhancement processing time and accuracy training via significant parameters in the batch BP algorithm by Fatma Susilawati, Mohamad, Mumtazimah, Mohamad, Sarhan, AlDuais

“…We created the dynamic learning rate and dynamic momentum factor for increasing the efficiency of the algorithm. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

“…The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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Prediction models of heritage building based on machine learning / Nur Shahirah Ja'afar by Ja'afar, Nur Shahirah

“…These algorithms were developed by using prewar shophouses dataset from 2004 until 2018 based on factors of heritage properties. …”
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Learning Algorithm effect on Multilayer Feed Forward Artificial Neural Network performance in image coding by Mahmoud, Omer, Anwar, Farhat, Salami, Momoh Jimoh Emiyoka

“…One of the essential factors that affect the performance of Artificial Neural Networks is the learning algorithm. …”
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Optimization of chest X-ray exposure factors using machine learning algorithm by Hamd, Zuhal Y., Alrebdi, H.I., Osman, Eyas G., Awwad, Areej, Alnawwaf, Layan, Nashri, Nawal, Alfnekh, Rema, Khandaker, Mayeen Uddin *

“…In this study, the chest X-ray exposure factors for 178 patients with different body mass index (BMI) values have been analyzed using the Python Machine Learning algorithm. …”
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A bayesian network approach to identify factors affecting learning of Additional Mathematics by Ong, Hong Choon, Kumarenthiran A/L Chandrasekaran

“…Constraint-based algorithms and score-based algorithms are used to generate the networks into several categories to compare and identify the strong relationships among the factors that affect the students’ learning of the subject. …”
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Three-term backpropagation algorithm for classification problem by Saman, Fadhlina Izzah

“…This algorithm utilizes two term parameters which are Learning Rate, α and Momentum Factor,β. …”
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Rockfall source identification using a hybrid Gaussian mixture-ensemble machine learning model and LiDAR data by Fanos, Ali Mutar, Pradhan, Biswajeet, Mansor, Shattri, Md Yusoff, Zainuddin, Abdullah, Ahmad Fikri, Jung, Hyung Sup

“…In addition, this technique has achieved excellent accuracies (ROC = 95%) over other methods used. Moreover, the proposed model has achieved the optimal prediction accuracies (92%) on the basis of testing data, thereby indicating that the model can be generalised and replicated in different regions, and the proposed method can be applied to various landslide studies.…”
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Reverse migration prediction model based on machine learning / Azreen Anuar by Anuar, Azreen

“…A significant way to minimize the errors is by using a machine learning approach that can predict reverse migration intelligently depending on the tested dataset. …”
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A comparative study of deep learning algorithms in univariate and multivariate forecasting of the Malaysian stock market by Mohd. Ridzuan Ab. Khalil, Azuraliza Abu Bakar

“…This study aims to develop a univariate and multivariate stock market forecasting model using three deep learning algorithms and compare the performance of those models. …”
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