Search Results - (( parametric classification based algorithm ) OR ( using factorization learning algorithm ))

Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

“…Lastly, (i) a single-based solution representation, (ii) a switchable mutation scheme, (iii) a vector-based estimation of the mutation factor, and (iv) an optional crossover strategy are proposed in the VDEO framework. …”
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Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach by Moheb Pour, Majid Reza

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Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification by Myaser, Jwan

“…The second stage involved assessing the spatial resolution effect through utilizing Landsat 8 (30 m) and Sentinel (10 m) data on LCM accuracy using SVM, K-Nearest Neighbor (K-NN), Random Forest (RF), and Neural Network (NN) algorithms. Based on the concluding overall analysis, the classification accuracy derived from Sentinel 2 imagery utilizing SVM and RF, Landsat 8 applying SVM donated higher than other methods of classification. …”
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Nearest neighbour group-based classification by Samsudin, Noor A., Bradley, Andrew P.

“…In this paper, we extend three variants of the nearest neighbour algorithm to develop a number of non-parametric group-based classification techniques. …”
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Validation on an enhanced dendrite cell algorithm using statistical analysis by Mohamad Mohsin, Mohamad Farhan, Hamdan, Abdul Razak, Abu Bakar, Azuraliza, Abd Wahab, Mohd Helmy

“…In this study, we evaluated the performance of the enhanced algorithm called dendrite cell algorithm using sensitivity, specificity, false positive rate, and accuracy and validated the result using parametric and non parametric statistical significant tests. …”
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Segmentation of masses from breast ultrasound images using parametric active contour algorithm by Jumaat, Abdul Kadir, Wan Abdul Rahman, Wan Eny Zarina, Ibrahim, Arsmah, Mahmud, Rozi

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Novel voice activity detection based on cepstrum moments by Farzan, Ali, Nourmohammadi, Ali, Mashohor, Syamsiah, Sadra, Sarvin

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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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Development of compound clustering techniques using hybrid soft-computing algorithms by Salim, Naomie, Shamsuddin, Siti Mariyam, Salleh @ Sallehuddin, Roselina, Alwee, Razana

“…Previously, there is limited work on the clustering and classification of biologically active compounds into their activity based classes using fuzzy and neural network. …”
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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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An improved teaching-learning-based optimization for extreme learning machine in floating photovoltaic power forecasting by Mohd Redzuan, Ahmad, Nor Farizan, Zakaria, Mohd Shawal, Jadin, Mohd Herwan, Sulaiman

“…This study presents an improved teaching-learning-based optimization algorithm with extreme learning machine for floating photovoltaic power forecasting. …”
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Oil palm mapping over Peninsular Malaysia using Google Earth Engine and machine learning algorithms by Shaharum, Nur Shafira Nisa, Mohd Shafri, Helmi Zulhaidi, Wan Ab. Karim Ghani, Wan Azlina, Samsatli, Sheila, Al-Habshi, Mohammed Mustafa, Yusuf, Badronnisa

“…In this study, 30 m Landsat 8 data were processed using a cloud computing platform of Google Earth Engine (GEE) in order to classify oil palm land cover using non-parametric machine learning algorithms such as Support Vector Machine (SVM), Classification and Regression Tree (CART) and Random Forest (RF) for the first time over Peninsular Malaysia. …”
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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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