Search Results - (( using function method algorithm ) OR ( based interactive ((svm algorithm) OR (bat algorithm)) ))

A study on component-based technology for development of complex bioinformatics software by Ali Shah, Zuraini, Deris, Safaai, Othman, Muhamad Razib, Zakaria, Zalmiyah, Saad, Puteh, Hassan, Rohayanti, Muda, Mohd. Hilmi, Kasim, Shahreen, Roslan, Rosfuzah

“…The second layer uses discriminative SVM algorithm with a state-of-the-art string kernel based on PSI-BLAST profiles that is used to leverage the unlabeled data. …”
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Solving large-scale problems using multi-swarm particle swarm approach by Salih, Sinan Q., Alsewari, Abdulrahman A.

“…The results showed that the proposed PSO algorithm outperformed the other algorithms in terms of the optimal solutions and the convergence.…”
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An Interaction Strategy for Testing Software Product Lines using the Bat-inspired Algorithm by Alsariera, Yazan A., Mazlina, Abdul Majid, Kamal Z., Zamli

“…In line with the recent emergence of Search based Software Engineering (SBSE), this article presents a novel strategy for SPLs tests reduction using Bat-inspired algorithm (BA), called SPLBA. …”
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TBat: A Novel Strategy for Minimization of T-Way Interaction Test Suite Based on the Particle Swarm Optimization and the Bat Algorithm by Kamal Z., Zamli, Alsariera, Yazan A.

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A Bat-inspired Strategy for T-Way Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A.

“…As part of the strategy implementation, researchers have started to turn into meta-heuristic algorithms in line with the emergence of the new field called Search based Software Engineering. …”
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Taguchi?s T-method with Normalization-Based Binary Bat Algorithm by Marlan Z.M., Jamaludin K.R., Harudin N.

“…Therefore, a variable selection technique using a swarm-based Binary Bat algorithm is proposed. Specifically, a normalization-based Binary Bat algorithm is used, where discretization of continuous solution into binary form is performed using a normalization equation. …”

The performance of Taguchi�s T-method with binary bat algorithm based on great value priority binarization for prediction by Marlan Z.M., Ramlie F., Jamaludin K.R., Harudin N.

“…This paper proposes an optimization algorithm based on the Binary Bat algorithm methodology for replacing the conventional orthogonal array approach. …”

SPLBA: an interaction strategy for testing software product lines using the bat-inspired algorithm by Kamal Z., Zamli, Yazan A., Alsariera, Mazlina, Abdul Majid

“…In line with the recent emergence of Search based Software Engineering (SBSE), this article presents a novel strategy for SPLs tests reduction using Bat-inspired algorithm (BA), called SPLBA. …”
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Benchmarking of Bat-inspired Interaction Testing Strategy by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B.

“…Complementing existing sampling strategies (i.e. in terms of dealing with interaction faults). To be specific, the interaction testing technique (refers to as t-way strategy) is based on interaction strength and is capable of dramatically reducing the number of test suite while ensuring practical coverage. …”
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A bat-inspired testing strategy for generating constraints pairwise test suite by Alsariera, Yazan A., Ahmed, Hussam Alddin Shihab, Alamri, Hammoudeh S., Mazlina, Abdul Majid, Kamal Z., Zamli

“…Complementing existing interaction based sampling strategies, pairwise testing has been extensively exploited resulting into many prototypes strategy implementations. …”
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A bat-inspired t-way strategy for mixed-strength test suite generation by Ahmad, Yazan Sadeq Al Sariera

“…Owing to its effectiveness for bug finding, many researchers are turning to the sampling strategies based on input interaction, called t-way testing, where t indicates the interaction strength. …”
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Taguchi's T-method with nearest integer-based binary bat algorithm for prediction by Marlan Z.M., Jamaludin K.R., Ramlie F., Harudin N.

“…This, however, resulted in a sub-optimal prediction accuracy due to its fixed and limited feature combination offered for evaluation and lack of higher-order feature interaction. In this paper, a swarm-based binary bat optimization algorithm with a nearest integer discretization approach is integrated with the Taguchi�s T-method. …”

Detection of eye movements based on EEG signals and the SAX algorithm by Shanmuga, P. M. M., Lau, Sian Lun *, Jou, Chichang.

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Improving multi-resident activity recognition in smart home using multi label classification with adaptive profiling by Mohamed, Raihani

“…On top of that, data association and algorithm modification inherit drawbacks on recognizing the residents and interactions of multi-resident complex activities. …”
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Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

“…The CNN algorithm produces better results with an accuracy of 97.07%, compared with the SVM algorithm. …”
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Implementation of welch pre-processing in SVM algorithm for improved accuracy on EEG data by Hariyady Hariyady, Ag Asri Ag Ibrahim, Jason Teo, Muhammad Balya Firjaun Barlaman, Muhammad Aulanas Bitaqwa, Azhana Ahmad, Fouziah Md Yassin, Carolyn Salimun, Ng, Giap Weng

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Multilanguage speech-based gender classification using time-frequency features and SVM classifier by Wani, Taiba, Gunawan, Teddy Surya, Mansor, Hasmah, Ahmad Qadri, Syed Asif, Sophian, Ali, Ambikairajah, Eliathamby, Ihsanto, Eko

“…The classification is done based on features derived from the frequency and time domain processing using the Support Vector Machines (SVM) algorithm. …”
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Gesture recognition system for Nigerian tribal greeting postures using support vector machine / Segun Aina …[et al.] by Aina, Segun, V. Sholesi, Kofoworola, R. Lawal, Aderonke, D. Okegbile, Samuel, I. Oluwaranti, Adeniran

“…This research used a moment-based feature extraction algorithm to extract shape features that were passed as input to SVM. …”
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A combinatory algorithm of univariate and multivariate gene selection by Mahmoodian, Sayed Hamid, Marhaban, Mohammad Hamiruce, Abdul Rahim, Raha, Rosli, Rozita, Saripan, M. Iqbal

“…Gene selection is usually based on univariate or multivariate methods. Univariate methods for gene selection cannot address interactions among multiple genes, a situation which demands the multivariate methods [1], [2]. …”
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Fine-scale predictive modeling of Aedes mosquito abundance and dengue risk indicators using machine learning algorithms with microclimatic variables by Che Dom, Nazri, Mohd Hardy Abdullah, Nur Athen, Dapari, Rahmat, Salleh, Siti Aekbal

“…This study developed fine-scale predictive models using machine learning algorithms; Artificial Neural Networks (ANN), Random Forest (RF), and Support Vector Machines (SVM) to estimate mosquito abundance and dengue risk at the species level based on daily microclimatic data (temperature, relative humidity, and rainfall) collected over 26 weeks in Kuala Selangor, Malaysia. …”
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