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Bee colony optimisation of the travelling salesman problem in light rail systems by Wang, Chen, Leong, Kah Huo, Abdul-Rahman, Hamzah

“…The study reported in this paper aimed to identify the most efficient algorithm and develop a mathematical model based on artificial bee colony optimisation to solve this problem in light rail transit systems. …”
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LSSVM parameters tuning with enhanced artificial bee colony by Mustaffa, Zuriani, Yusof, Yuhanis

“…The proposed model was employed in predicting financial time series data and comparison is made against the standard Artificial Bee Colony (ABC) and Cross Validation (CV) technique.The simulation results assured the accuracy of parameter selection, thus proved the validity in improving the prediction accuracy with acceptable computational time.…”
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Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics by Mohammad Jarrah, Mu'ath Ibrahim

“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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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

“…Thus, this study aims to evaluate the feasibility of homogenous transfer learning approaches to overcome data constraints in developing NIRS predictive models of stingless bee honey qualities across different months. …”
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Multi-Class Multi-Level Classification of Mental Health Disorders Based on Textual Data from Social Media by Sutranggono, Abi Nizar, Sarno, Riyanarto, Ghozali, Imam

“…The results of the experiments show that the MCML classification algorithm successfully performs detailed classification and produces promising results for each classification level. …”
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Symmetric Key Size for Different Level of Information Classification by Ibrahim, Subariah, Maarof, Mohd. Aizaini

“…Confidential information can be categorized into various levels of classification. The classification depends on the level of damage to an organization or to national security when the information is disclosed. …”
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Minimizing Classification Errors in Imbalanced Dataset Using Means of Sampling by Khan I., Ahmad A.R., Jabeur N., Mahdi M.N.

“…Classification (of information); Learning algorithms; Students; Class imbalance; Data level; Over sampling; Performance prediction; SMOTE; Spread subsampling; Student performance; Student performance prediction; Under-sampling; Machine learning…”

Performance analysis of machine learning algorithms for classification of infection severity levels on rubber leaves by Mat Lazim, Siti Saripa Rabiah, Sulaiman, Zulkefly, Mat Nawi, Nazmi, Mohd Mustafah, Anas

“…This work shows that the spectroscopic measurement combined with classification techniques are promising strategy to classify severity level of WRD based on the spectral data of the rubber leaves.…”
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Enhanced ABD-LSSVM for energy fuel price prediction by Mustaffa, Zuriani, Yusof, Yuhanis, Kamaruddin, Siti Sakira

“…This paper presents an enhanced Artificial Bee Colony (eABC)based on Lévy Probability Distribution (LPD) and conventional mutation. …”
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Optimizing Visual Surveillance Sensor Coverage Using Dynamic Programming by Altahir, A.A., Asirvadam, V.S., Hamid, N.H.B., Sebastian, P., Saad, N.B., Ibrahim, R.B., Dass, S.C.

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Automatic classification of medical x-ray images by Zare, M.R., Seng, W.C., Mueen, A.

“…These features have been exploited in different algorithms for automatic classification of medical X-ray images. …”
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Data Mining Analysis Of Chronic Kidney Disease (CKD) Level by Mohd Harizi, Muhammad Hafizam Afiq

“…The ZeroR algorithm was set as the baseline There are three levels of classification analyses: before and after handling the missing values, before and after the outliers’ treatment, and adding uncertain classes. …”
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Enhanced ABC-LSSVM For Energy Fuel Price Prediction by Mustaffa, Zuriani, Yusof, Yuhanis, Kamaruddin, Siti Sakira

“…To evaluate the effi ciency of the proposed model, crude oil prices data was employed as empirical data and a comparison against four approaches were conducted, which include standard ABC-LSSVM, Genetic Algorithm-LSSVM (GA-LSSVM), Cross Validation-LSSVM (CV-LSSVM), and conventional Back Propagation Neural Network (BPNN). …”
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Correlation Feature Selection Weighting Algorithms for Better Support Vector Classification: An Empirical Study by Sim, Doreen Ying Ying, Teh, Chee Siong, Ahmad Izuanuddin, Ismail

“…Prediction and/or classification accuracies of cfsw-SVM algorithms are significantly improved.…”
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Modified anfis architecture with less computational complexities for classification problems by Talpur, Noureen

“…The proposed ANFIS model is trained by one of the metaheuristics approach instead of standard two pass learning algorithm. …”
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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. …”

Arabic text classification using hybrid feature selection method using chi-square binary artificial bee colony algorithm by Hijazi, Musab, Zeki, Akram M., Ismail, Amelia Ritahani

“…Chi-square, a filter method that is computationally fast, simple and has the ability to deal with a large dimensional feature, is used as the first level of the feature selection process. After that, the wrapper method, Artificial Bee Colony algorithm, is used as the second level where Naive Base is used as a fitness function. …”
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Multilayer Perceptron Neural Network In Classifying Gender Using Fingerprint Global Level Features by Siti Fairuz, Abdullah, Ahmad Fadzli Nizam, Abdul Rahman, Zuraida, Abal Abas, Wira Hidayat, Mohd Saad

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Classification of Diabetes Mellitus (DM) using Machine Learning Algorithms by Sirajun Noor, Noor Azmiya

“…The objective of this study is to perform DM classification using various machine learning algorithms using Weka as a tool. …”
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Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

“…However, there is a need to explore more algorithms that can yield better classification performance. …”
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