Search Results - sampling-((bayes algorithm) OR (((bat algorithm) OR (based algorithm))))

Bat Algorithm Based Hybrid Filter-Wrapper Approach by Taha A.M., Chen S.-D., Mustapha A.

“…This paper presents a new hybrid of Bat Algorithm (BA) based on Mutual Information (MI) and Naive Bayes called BAMI. …”

A Bat-inspired Strategy for Pairwise Testing by Alsariera, Yazan A., Mazlina, Abdul Majid, Kamal Z., Zamli

“…Complementing the existing work, we propose a novel design and implementation of Bat-inspired algorithm (BA) for pairwise strategy, called Bat-inspired pairwise testing strategy (BPTS). …”
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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

“…This paper proposes an enhancement design and implementation of BTS strategy for constraints pairwise test generation based on the bat-inspired algorithm (BA). The benchmarking results of BTS show that it outperforms the generated test suite of the existing tools and strategies even in the presence of constraints.…”
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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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FEATURES EXTRACTION OF FINGERPRINTS BASED ON HYBRID PARTICLE SWARM OPTIMIZATION AND BAT ALGORITHMS by Ahmed A.L., Hassoon N., Hak L.A.L., Edan M., Abed H., Abd S.

“…Both PSO and BA algorithms are swarmbased algorithms that mimics the swarm behaviour of particles and bats in nature. …”

Benchmarking of Bat-inspired Interaction Testing Strategy by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B.

“…Recently, there are growing interests for adopting optimization algorithms as the basis of the newly developed strategies contributing to the new and upcoming search based software testing (SBST) area of research. …”
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Identification model for hearing loss symptoms using machine learning techniques by Nasiru Garba Noma

“…In order to find, the correlation that exist between the hearing thresholds and symptoms of hearing loss, FP-Growth and association rule algorithms were first used to experiment with a small sample and large sample datasets. …”
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Mobile app of mood prediction based on menstrual cycle using machine learning algorithm / Nur Hazirah Amir by Amir, Nur Hazirah

“…It implemented Supervised Learning algorithm with Bayes’ Theorem model for the calculation of mood prediction using Python programming language. …”
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A bat-inspired t-way strategy for mixed-strength test suite generation by Ahmad, Yazan Sadeq Al Sariera

“…BTS is the first t-way strategy that adopts the Bat-inspired algorithm as its core implementation and adopts the Hamming distance as the final selection criteria to enhance the exploration of new solution. …”
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Prediction of employee promotion using hybrid sampling method with machine learning architecture / Shahidan Shafie, Soek Peng Ooi and Khai Wah Khaw by Shafie, Shahidan, Soek, Peng Ooi, Khai, Wah Khaw

“…The first 5, 8, and 12 features are selected based on the RFI-ECT to train the machine learning algorithms. …”
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Natural extensions: Bat algorithm with memory by Taha A.M., Chen S.-D., Mustapha A.

“…Bat Algorithm (BA) has recently started to attract a lot of attention as a powerful search method in various machine learning tasks including feature selection. …”

Color Image Segmentation Based on Bayesian Theorem for Mobile Robot Navigation by Rahimizadeh, Hamid

“…The experimental results show the proposed algorithm is simple and robust, for real time application on vision based mobile robot for navigation, in spite of presence of other shapes and colors in the environment …”
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Mid-infrared spectroscopy for early detection of basal stem rot disease in oil palm by Liaghat, Shohreh, Mansor, Shattri, Ehsani, Reza, Mohd Shafri, Helmi Zulhaidi, Meon, Sariah, Sankaran, Sindhuja

“…The algorithms were tested to classify the leaf samples into four levels of disease severity. …”
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RFE-based feature selection to improve classification accuracy for morphometric analysis of craniodental characters of house rats by Aneesha Balachandran Pillay, Dharini Pathmanathan, Arpah Abu, Hasmahzaiti Omar

“…We also performed a comparative study based on three machine learning algorithms such as Naïve Bayes, Random Forest, and Artificial Neural Network by using all features and the RFE-selected features to classify the R. rattus sample based on the age groups. …”
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Ganoderma boninense classification based on near-infrared spectral data using machine learning techniques by Mas Ira Syafila, Mohd Hilmi Tan, Mohd Faizal, Jamlos, Ahmad Fairuz, Omar, Kamarulzaman, Kamarudin, Mohd Aminudin, Jamlos

“…It is found the spectra of healthy samples are scattered on the negative sides of PC-1 while infected samples tend to be on a positive side with large loading coefficients marked significant discriminatory effect on healthy and infected samples at the wavelength of 1310 and 1452 nm. …”
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Early detection of basal stem rot disease (Ganoderma) in oil palms based on hyperspectral reflectance data using pattern recognition algorithms by Liaghat, Shohreh, Ehsani, Reza, Mansor, Shattri, Mohd Shafri, Helmi Zulhaidi, Meon, Sariah, Sankaran, Sindhuja, Azam, Siti H. M. N.

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Sentiment analysis for online fashion clothing review using Support Vector Machine (SVM) algorithm / Muhammad Hakam Musawi Mohd Hamdi by Mohd Hamdi, Muhammad Hakam Musawi

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A Stacked Ensemble Deep Learning Approach For Imbalanced Multi-class Water Quality Index Prediction by Wen Yee Wong, Khairunnisa Hasikin, Anis Salwa Mohd Khairuddin, Sarah Abdul Razak, Hanee Farzana Hizaddin, Mohd Istajib Mokhtar, Muhammad Mokhzaini Azizan

Classification of polymorphic virus based on integrated features by A Hamid, Isredza Rahmi, Subramaniam, Sharmila, Sutoyo, Edi, Abdullah, Zubaile

“…We spilt the dataset based on 60% for training and 40% for testing. The performance metric of accuracy value, receiver operating characteristic and mean absolute error are compared between two algorithms in the experiment of static, dynamic and integrated features. …”
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Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms by Choong, Chun Sern

“…The received signal strength of the maximum, median, and mean of all statistical features has been shown to be significant specifically for the 10Hz sample size. Different machine learning classifiers were tested based on the significant features, namely the Artificial Neural Network, Decision Tree, Random Forest, Naive Bayes Support Vector Machine, and k-Nearest Neighbors. …”
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