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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

“…Then canonical Polyadic decomposition-based attribute reduction is applied to the offload-able task to reduce the data size. Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Dhany, Saputra

“…The results also show that in Java, A Arraylist is the most suitable choice for storing Object and Arraylnt list is the most suitablec choice for storing integer data. …”
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Non-invasive pathological voice classifications using linear and non-linear classifiers by Hariharan, Muthusamy

“…In this research work, three databases such as MEEI voice disorders database, MAPACI Speech Pathology database, and dataset-III (collected at Hospital Tuanku Fauziah, Kangar, Perlis) are used to test the independence of the algorithms to the databases and the proposed feature extraction algorithms are also tested in noisy condition at 30dB signal-to-noise ratio. …”
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Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

“…The results also show that in Java, A Arraylist is the most suitable choice for storing Object and Arraylnt list is the most suitablec choice for storing integer data. …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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Reducing of Inconsistent Data using Fuzzy Multi Attribute Decision Making for Accessing Data from Database by Yusof, Mohd Kamir, Abdul Rahman, Mohd Nordin, Azlan, Atiqah

“…Sample data was selected for experiments purposes. The result indicates fuzzy multi attribute decision making is a suitable technique in reducing inconsistent data from database. …”
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Pairwise test suite generator tool based on harmony search algorithm (HS-PTSGT) by Lai, Yi Xiang

“…This thesis is about the research on developing a pairwise test suite generator tool based on Harmony Search Algorithm (HS-PTSGT) to generate optimum test suite. …”
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

“…In order to make the normal people can cluster their data easily, this project aims is to develop a web-based clustering tool that can be used by all peoples. …”
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Forensic language of property theft genre based on mathematical formulae and machine learning algorithms / Hana' Abd Razak by Abd Razak, Hana'

“…Here, 19116 colour pixel-based images that comprised of both normal and anomalous behaviours acted as inputs to four samplings of CNN. …”
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A new algorithm for normal and large-scale optimization problems: Nomadic People Optimizer by Alsewari, Abdul Rahman Ahmed, Sinan, Q. Salih

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Time normalization of LPC feature using warping method by Sudirman, Rubita, Salleh, Sh. Hussain, Khalid, Puspa Inayat, Ahmad, Abd. Hamid

“…By doing frame fixing (time normalization), the test set and the training set is adjusted to the same number of frames. …”
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Multi-sources model and control algorithm of an energy management system by Hannan, MA, Azidin, FA, Mohamed, Azah

“…The results show that the designed vehicle’s speed and load power closely match those of the ECE-47 test driving cycle under normal and heavy load conditions. …”
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Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer by Iqbal Basheer, Muhammmad Yunus

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Pengkelasan Sel Kanser Pangkal Rahim Kepada Sel Normal Dan Tidak Normal Menggunakan Analisis Pembezalayan Dan Rangkaian Neural by Saidin, Mohammad Norrish

“…The optimum value of epoch and hidden nodes for each learning algorithm are determined based on the highest accuracy obtained during training phases. …”
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DTWFF-pitch feature and faster neural network convergence for speech recognition by Sudirman, Rubita, Salleh, Sh. Hussain, Salleh, Shaharuddin

“…By doing time normalization, the test set and the training set are adjusted to the same number of frames. …”
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Early detection and mitigation of DDoS attacks in software defined networks by Al-Saadi, Mustafa Yahya Zakariya

“…To find the proper detection threshold a series of tests on different scenarios of normal and attack traffic were conducted. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. 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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An improved recommender system based on normalization of matrix factorization and collaborative filtering algorithms by Zahid, Aafaq

“…It is concluded that the resultant hybrid techniques can perform well if the variables provided to normalization by neighborhood model (MF and CF) do not have big differences in order for the hybrid normalization model to outperform every algorithm in comparison.…”
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