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A Review of Unsupervised Machine Learning Frameworks for Anomaly Detection in Industrial Applications by Usmani, U.A., Happonen, A., Watada, J.

“…Unsupervised learning, also known as unsupervised machine learning, analyzes and clusters unlabeled data utlizing machine learning techniques. …”
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Waste management using machine learning and deep learning algorithms by Sami, Khan Nasik, Amin, Zian Md Afique, Hassan, Raini

“…For our research we did the comparisons between three Machine Learning algorithms, namely Support Vector Machine (SVM), Random Forest, and Decision Tree, and one Deep Learning algorithm called Convolutional Neural Network (CNN), to find the optimal algorithm that best fits for the waste classification solution. …”
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Application of machine learning algorithms to predict the thyroid disease risk: an experimental comparative study by Islam, Saima Sharleen, Haque, Md Samiul, Miah, M. Saef Ullah, Sarwar, Talha, Nugraha, Ramdhan

“…For this reason, this study compares eleven machine learning algorithms to determine which one produces the best accuracy for predicting thyroid risk accurately. …”
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Thematic textual hadith classification: an experiment in rapidminer using support vector machine (SVM) and naïve bayes algorithm by Yusof, Norzihani, Rosidi, Siti Aishah Rosidi, Ibrahim, Nuzulha Khilwani Ibrahim, Ahmed Ali, Ahmed El-Mogtaba Bannga

“…We put on the Hadith dataset onto one of machine learning tools which is text classification. …”
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Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS by Jaafar, Jafreezal

“…Moreover, the extreme learning machine does not have any design parameters such as learning rate, covariance matrix, etc…”
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A Comparative Analysis of Machine Learning and Deep Learning Algorithms for Image Classification by Madanan M., Gunasekaran S.S., Mahmoud M.A.

Neural Network Multi Layer Perceptron Modeling For Surface Quality Prediction in Laser Machining by Sivarao, Subramonian

“…The researchers conducted the prediction of laser machining quality, namely surface roughness with seven significant parameters to obtain singleton output using machine learning techniques based on Quick Back Propagation Algorithm. …”
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Machine learning using robust AI techniques / Prof. Madya Dr. Nordin Abu Bakar by Abu Bakar, Nordin (Prof. Madya Dr.)

“…How does a person make a right decision ? maybe he learns from past experience or new information he receives. …”
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Optimal variational mode decomposition and integrated extreme learning machine for network traffic prediction by Jinmei Shi, Yu-Beng Leau, Kun Li, Huandong Chen

“…Also, it does not easily fall into local optima. The evolutionary algorithm can be used to optimize the number of its hidden layer nodes. …”
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Extreme learning machine model for state-of-charge estimation of lithium-ion battery using gravitational search algorithm by Hossain Lipu M.S., Hannan M.A., Hussain A., Saad M.H., Ayob A., Uddin M.N.

Feature selection and prediction of heart disease using machine learning approaches by Molla, M. M.Imran, Islam, Md Sakirul, Shafi, A. S.M., Alam, Mohammad Khurshed, Islam, Md Tarequl, Jui, Julakha Jahan

“…In this paper, it is capable of recognizing and classifying the heart disease patient from healthy people by using three standard machine learning algorithms: Random Forest (RF), Support Vector Machine (SVM) and K-Nearest Neighbor (KNN). …”
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The influence of sentiments in digital currency prediction using hybrid sentiment-based Support Vector Machine with Whale Optimization Algorithm (SVMWOA) by Hitam, Nor Azizah, Ismail, Amelia Ritahani, Samsudin, Ruhaidah, Ameerbakhsh, Omair

“…This creates a chaos in the price of index so does the sentiment of the investor. This study proposes a machine learning model that applies a combination of sentiment-based support vector machine that is optimized by the whale optimization algorithm for predicting the daily price of a digital currency. …”
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Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

“…Moreover, the extreme learning machine does not have any design parameters such as learning rate, covariance matrix, etc. …”
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Differential Search Optimized Random Forest Regression Algorithm for State of Charge Estimation in Electric Vehicle Batteries by Hossain Lipu M.S., Hannan M.A., Hussain A., Ansari S., Ayob A., Saad M.H.M., Muttaqi K.M.

Investigation of Meta-heuristics Algorithms in ANN Streamflow Forecasting by Wei Y., Hashim H., Chong K.L., Huang Y.F., Ahmed A.N., El-Shafie A.

Intrusion detection on the in-vehicle network using machine learning by Sharmin, Shaila, Mansor, Hafizah

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Real-Time State of Charge Estimation of Lithium-Ion Batteries Using Optimized Random Forest Regression Algorithm by Hossain Lipu M.S., Hannan M.A., Hussain A., Ansari S., Rahman S.A., Saad M.H.M., Muttaqi K.M.

“…This paper presents an improved machine learning approach for the accurate and robust state of charge (SOC) in electric vehicle (EV) batteries using differential search optimized random forest regression (RFR) algorithm. …”

Bitcoin price prediction using machine learning by Tang, Jian Yang

“…This study proposes three types of machine learning algorithms (LSTM, GRU, and Prophet) with two types of architectural configurations (Sequence-to-Sequence and Sequence-to-One) to predict Bitcoin’s closing price based on 1 year of Bitcoin historical data, (2, April 2022 to 2, April 2023). …”
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Machine learning classification model for identifying internet addiction among university students by Tan, Hui Theng, Mun, Hou Kit, Handayani, Dini Oktarina Dwi

“…In this study, three machine learning models are developed and compared. …”
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Machine learning models for predicting the compressive strength of concrete with shredded pet bottles and m sand as fine aggregate by Nadimalla, Altamashuddinkhan, Masjuki, Siti Aliyyah, Gubbi, Abdullah, Khan, Anjum, Mokashi, Imran

“…Machine learning is a critical subset of AI that deliberates the development of self-trained algorithms that use previous databases and analysis for result predictions. …”
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