Search Results - sampling-((bees algorithm) OR (bat algorithm))

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. …”

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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Optimisation of Surface Roughness in 3D Printing Using the Bees Algorithm by Kamaruddin, Shafie, Ridzuan, Arman Hilmi, Sukindar, Nor Aiman

“…The result also shows that the Bees Algorithm found a better combination of parameters compared to other algorithms. …”
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A Bat-inspired Strategy for T-Way Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A.

“…Complementing in the aforementioned respect, this paper discusses the adoption of Bat Algorithm as the basis of t-way strategy. Our experience has been promising as our strategy has managed to outperform many existing work, where the results of the experiment shows that BTS is superior in term of the solution quality.…”
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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. …”

Artificial Bee Colony Algorithm for Pairwise Test Generation by Alazzawi, Ammar K., Homaid, Ameen A. Ba, Alomoush, Alaa A., Alsewari, Abdulrahman A.

“…PABC progresses as a means to achieve the effective use of the artificial bee colony algorithm for pairwise testing reduction.…”
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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.

“…Complementing existing sampling strategies (i.e. in terms of dealing with interaction faults). …”
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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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Transfer learning in near infrared spectroscopy for stingless bee honey quality prediction across different months by Suarin, Nur Aisyah Syafinaz, Chia, Kim Seng, Mohamad Fuzi, Siti Fatimah Zaharah

“…Since it is unrealistic to have a NIRS dataset that can represent unforeseen future changes, an algorithm that can adapt existing data for new samples is worth to be investigated. …”
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A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets by Mohd Razali, Muhamad Hasbullah, Saian, Rizauddin, Yap, Bee Wah, Ku-Mahamud, Ku Ruhana

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ZigBee environment for indoor localization by Chieh K.S., Keong N.Y., Burhan M.F., Balasubramaniam N., Din N.M.

Artificial Bee Colony With Differential Evolution Algorithm For Feature Extraction And Selection Of Mass Spectrometry Data by Mohamed Yusoff, Syarifah Adilah

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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

“…In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”

RLMD-PA: A Reinforcement Learning-Based Myocarditis Diagnosis Combined with a Population-Based Algorithm for Pretraining Weights by Seyed Vahid Moravvej, Roohallah Alizadehsani, Sadia Khanam, Zahra Sobhaninia, Afshin Shoeibi, Fahime Khozeimeh, Zahra Alizadeh Sani, Ru-San Tan, Abbas Khosravi, Saeid Nahavandi, Nahrizul Adib Kadri, N. Arunkumar, U.Rajendra Acharya, Muhammad Mokhzaini Azizan

Datasets on spatial and temporal distribution of heavy metals concentration in recent sediment at merang river system, Terengganu, Malaysia by Zaini, Nur Marni, Lee, Hui Wen, Mohamed, Khairul Nizam, Sabuti, Asnor Azrin, Suratman, Suhaimi, Ong, Meng Chuan

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Comparative studies of the tribological characteristics of conventional SAE 40 and blended SAE 40 lubricants by Samuel, Joseph, Kaisan, Muhammad Usman, Sanusi, Yinka Sofihullahi, Aliyu, Abdulkabir, Experience, Akhigbe Efeosa

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