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Combination of perturb and observe with online sequential extreme learning machine for photovoltaic system maximum power point tracking by Dira, Yasir Sabah

“…From different MPPT techniques previously proposed, the online sequential extreme learning machine algorithm and conventional perturb and observe are combined together as a proposed MPPT algorithm. …”
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Correlation model in the adoption of E-payment services: A machine learning approach by Tan, Xi En

“…Then, by using Correlation Based Feature selection algorithm, we select the best subset of features out of the highly correlated features to do predictive modelling. …”
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A Comparative Performance Analysis of Malware Detection Algorithms Based on Various Texture Features and Classifiers by Ahmed I.T., Hammad B.T., Jamil N.

Malay sentiment analysis based on combined classification approaches and Senti-lexicon algorithm by Al-Saffar, Ahmed Ali Mohammed, Suryanti, Awang, Tao, Hai, Nazlia, Omar, Al-Saiagh, Wafaa, Al-bared, Mohammed

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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis by Norman, Masayu

“…The accuracy of each algorithm was evaluated using LibSVM, Bayes network, and Adaboost classifier. …”
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High-Resolution Downscaling with Interpretable Relevant Vector Machine: Rainfall Prediction for Case Study in Selangor by Abdul Rashid, Raghdah Rasyidah, Shaharudin, Shazlyn Milleana, Sulaiman, Nurul Ainina Filza, Zainuddin, Nurul Hila, Mahdin, Hairulnizam, Mohd Najib, Summayah Aimi, Hidayat, Rahmat

“…While machine learning eliminates the requirement for manual feature selection when extracting significant information from predictor fields, considering multiple pivotal factors is essential. …”
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Blind Source Separation Using Two-Dimensional Nonnegative Matrix Factorization In Biomedical Field by Toh, Cheng Chuan

“…Theoretically,β and α is parameters that used to vary the NMF2D algorithm in order to yield high SDR value. …”
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A comparative study of supervised machine learning approaches for slope failure production by Deris A.M., Solemon B., Omar R.C.

“…This study employs an "artificial neural network" (ANN) to predict the slope failures based on historical circular slope cases. Using the feed-forward back-propagation algorithm with a multilayer perceptron network, ANN is a powerful ML method capable of predicting the complex model of slope cases. …”

Machine Learning-Based Stress Level Detection from EEG Signals by Nirabi, Ali, Abd Rhman, Faridah, Habaebi, Mohamed Hadi, Sidek, Khairul Azami, Yusoff, Siti Hajar

“…This paper presented a system to detect the stress level from the EEG signals using machine learning algorithms. The proposed method, at first, removed physiological noises from the EEG signal applying a band-pass FIR filter. …”
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Improving named entity recognition accuracy of gene and protein in biomedical text by Tohidi, Hossein

“…The strength of our proposed approach for recognizing biomedical named entity is based on a Statistical Character-Based Syntax Similarity (SCSS) algorithm which measured similarity between all extracted candidates and the well-known biomedical named entities from a corpus. …”
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Recommendation System Model For Decision Making in the E-Commerce Application by Mohammed Mahmudur Rahman

Stock market turning points rule-based prediction / Lersak Photong … [et al.] by Photong, Lersak, Sukprasert, Anupong, Boonlua, Sutana, Ampant, Pravi

“…From news classification and news sentiment, a rule-based algorithm was used to predict the stock market turning points. …”
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Digital economy tax compliance model in Malaysia using machine learning approach by Raja Azhan Syah Raja Wahab, Azuraliza Abu Bakar

“…In predictive modeling, single and ensemble approaches are employed to find the best model and important factors contributing to the incompliance of tax payment among the digital economic retailers. Based on the validation of training data with the presence of seven single classifier algorithms, three performance improvements have been established through ensemble classification, namely wrapper, boosting, and voting methods, and two techniques involving grid search and evolution parameters. …”
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Development of a hybrid machine learning model for rockfall source and hazard assessment using laser scanning data and GIS by Fanos, Ali Mutar

“…The proposed BANN model achieved the best training accuracies of (95%) and best prediction accuracies of (92%) based on testing data compared to other employed methods. …”
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Sound quality classification of wood used for Sarawak traditional musical instrument- Sape / Wong Tee Hao by Wong , Tee Hao

“…To address dataset imbalances, Synthetic Minority Oversampling Technique was used, enhancing dataset quality before training 40 machine learning classification algorithms. …”
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Prediction of rice biomass using machine learning algorithms by Radhwane, Derraz

“…Unmanned aerial vehicles (UAVs) may address these issues. Machine learning algorithms (MLs) can predict rice biomass from UAV-based vegetation indices (VIs). …”
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Biometric identification and recognition for iris using failure rejection rate (FRR) / Musab A. M. Ali by M. Ali, Musab A.

“…The subsequent step is using the DAUB3 wavelet transform for feature extraction along with the application of an additional step for biometric template security that is the Non-invertible transform (cancelable biometrics method) and finally utilizing the Support Vector Machine (Non-linear Quadratic kernel) for matching/classification. …”
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A review of machine vision pose measurement by Xiaoxiao, Wang, Beng, Ng Seng, O. K. Rahmat, Rahmita Wirza, Sulaima, Puteri Suhaiza

“…Discusses the factors that affect the accuracy and reliability of machine vision pose measurement algorithms. …”
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A review of machine vision pose measurement by Xiaoxiao, Wang, Beng, Ng Seng, O. K. Rahmat, Rahmita Wirza, Sulaima, Puteri Suhaiza

“…Discusses the factors that affect the accuracy and reliability of machine vision pose measurement algorithms. …”
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A block-based multi-scale background extraction algorithm by Davarpanah, Seyed Hashem, Khalid, Fatimah, Golchin, Maryam

“…Approach: In this study, to extract an adaptive background, a combination of blocking and multi-scale methods is presented. …”
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