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i-Saturate: The New Discovery of Stopping Criterion in Genetic Algorithm by Foo, Fong Yeng, Suhaimi, Azrina, Soo, Kum Yoke

“…It was concluded that the i-Saturate model has demonstrated better searching ability than the comparative model and it intelligently stops searching without human intervention.…”
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A comparison of decision tree, logistic regression, artificial neural network and random forest algorithms to predict suicidal ideation among young adults in Malaysia by Chan, Sin Yin, Ch’ng, Chee Keong

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Determining malaria risk factors in Abuja, Nigeria using various statistical approaches by Segun, Oguntade Emmanuel

“…The optimal model based on the parsimony principles was obtained from the hill climbing algorithm with score metrics. …”
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VISUALIZATION OF GENETIC ALGORITHM BASED ON 2-D GRAPH TO ACCELERATE THE SEARCHING WITH HUMAN INTERVENTIONS. by FAROOQ, HUMERA

“…It is noted that active user intervention increases the acceleration of Genetic Algorithm towards an optimal solution. …”
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Predictive Modelling of Stroke Occurrence among Patients using Machine Learning by Sures, Narayasamy, Thilagamalar, Maniam

“…Advanced machine learning algorithms, including logistic regression, decision trees, random forests, and support vector machines, were utilized to analyses the dataset and develop a predictive model. …”
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Evaluation of the Effect of Ideological and Political Education on Psychological Crisis Intervention for University Students Based on Data Mining Algorithm by Hexia Yao, Mohd. Dahlan Hj. A. Malek

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Fine-scale predictive modeling of Aedes mosquito abundance and dengue risk indicators using machine learning algorithms with microclimatic variables by Che Dom, Nazri, Mohd Hardy Abdullah, Nur Athen, Dapari, Rahmat, Salleh, Siti Aekbal

“…This study developed fine-scale predictive models using machine learning algorithms; Artificial Neural Networks (ANN), Random Forest (RF), and Support Vector Machines (SVM) to estimate mosquito abundance and dengue risk at the species level based on daily microclimatic data (temperature, relative humidity, and rainfall) collected over 26 weeks in Kuala Selangor, Malaysia. …”
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Prediction of UiTM student academic performance using Naive Bayes algorithm / Muhammad Irfan Zahin Jailani by Jailani, Muhammad Irfan Zahin

“…With the help of customized interventions and early identification of at-risk pupils, the proposed approach seeks to increase graduation rates and overall achievement.The main objectives of this study include studying the Naive Bayes algorithm in student academic performance prediction, designing and developing a student academic performance prediction model utilizing Naive Bayes, and evaluating the accuracy of the prediction prototype using the developed model. …”
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Reliability fuzzy clustering algorithm for wellness of elderly people by N. J., Mohd Jamal, Ku Muhammad Naim, Ku Khalif, Mohd Sham, Mohamad

“…Fuzzy clustering is one of the unsupervised machine learning techniques based knowledge of data analysis that automated or semi-automated analytical model building. By gleaning insights from the data, the fuzzy clustering can learn from data, identify patterns and make decisions with minimal human intervention. …”
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Facility location models development to maximize total service area by Mahmud, Ahmad Rodzi, Indriasari, Vini

“…This paper present and discuss the new developed model to maximize total service area of a fixed number of facilities. …”
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Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr... by Sammen S.S., Ehteram M., Sheikh Khozani Z., Sidek L.M.

“…This paper�s novelty includes introducing a new method for selecting inputs and developing a new model for predicting water levels. …”

Comparison of hidden Markov Model and Naïve Bayes algorithms among events in smart home environment by Babakura, Abba, Sulaiman, Md Nasir, Mustapha, Norwati, Kasmiran, Khairul A.

“…In this paper, we propose Hidden Markov Model (HMM) and Naïve Bayes (NB) to test the accuracy and response time of the home data and to compare between the two algorithms. …”
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Meta-requirement mapping model by Muhamad Idaham, Umar Ong, M. A., Ameedeen

“…Looking forward, an algorithm will be developed for realizing the associations that was define in the propose model.…”
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Sentiment analysis regarding marital issues using Naive Bayes algorithm / Farah Nabila Mohd Razali by Mohd Razali, Farah Nabila

“…These insights can assist policymakers, mental health professionals, and marriage counselors in developing targeted interventions to support healthier relationships and strengthen societal well-being.…”
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Autonomous Positioning Of Unmanned Aerial Vehicle (UAV) For Power Lines Insulator Detection by Sze Sin, Voon, Kho, Lee Chin, Ngu, Sze Song, Annie, Joseph, Kuryati, Kipli

“…The proposed model leverages machine learning algorithms for autonomous detection of insulators. …”
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Transparent insights into alzheimer’s progression: a time-aware approach with explainable by Abraham Varghese, Ben George, Vinu Sherimon, Prashanth Gouda

“…This approach not only enhances transparency but also builds trust in the model’s outcomes. The ADNI dataset, comprising 2980 observations, was employed for developing a prediction model using various machine learning classifiers. …”
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Malaysian license plate recognition system using Convolutional Neural Network (CNN) on web application / Nur Farahana Mahmud by Mahmud, Nur Farahana

“…Nowadays, there are numerous license plate recognition systems that have been developed and analysed effectively by previous researchers using different machine learning algorithms. …”
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Machine learning-based risk prediction model for medication administration errors in neonatal intensive care units: a prospective direct observational study by Henry Basil, Josephine, Lim, Wern Han, Syed Ahmad, Sharifah M., Menon Premakumar, Chandini, Mohd Tahir, Nurul Ain, Mhd Ali, Adliah, Seman, Zamtira, Ishak, Shareena, Mohamed Shah, Noraida

“…AdaBoost was identified as the best-performing algorithm. Utilising the model's predictions, healthcare providers can potentially reduce MAE occurrence through timely interventions.…”
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An optimized attack tree model for security test case planning and generation by Omotunde, Habeeb, Ibrahim, Rosziati, Ahmed, Maryam

“…This paper presents an attack tree modeling algorithm for deriving a minimal set of effective attack vectors required to test a web application for SQL injection vulnerabilities. …”
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Deep learning in public health: Comparative predictive models for COVID-19 case forecasting by Muhammad Usman Tariq, Muhammad Usman Tariq, Ismail, Shuhaida

“…The findings indicate that the selected deep learning algorithms were proficient in forecasting COVID-19 cases, although their efficacy varied across different models. …”
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