Search Results - "machine learning methods"

Phishing attack detection using machine learning method by Jupin, John Arthur

“…The experiment is conducted for the datasets that obtained by using machine learning method. The results are obtained, showing the performance of machine learning method on each dataset.…”
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Comparative performance of machine learning methods for classification on phishing attack detection by Siti Noranisah, Wan Ahmad, Mohd Arfian, Ismail, Edi, Sutoyo, Shahreen, Kasim, Mohd Saberi, Mohamad

“…In this paper, several machine learning methods were studied and applied in detecting phishing attack. …”
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Exploring The Synergy Of Template And Machine Learning Methods To Improve Photometric Redshifts by Khalfan, Alshuaili Ishaq Yahya

“…This thesis explores the use of both template-based and machine learning methods to improve the accuracy of galaxy photometric redshift estimation. …”
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Predictive Analytics for Malaysian Federal Government Revenue using Supervised Machine Learning Methods by Noor Kamarul Anuar, Nadzira

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Review of the machine learning methods in the classification of phishing attack by Jupin, John Arthur, Sutikno, Tole, Mohd Arfian, Ismail, Mohd Saberi, Mohamad, Shahreen, Kasim, Deris, Stiawan

“…Based on the literature, the machine learning method is widely used to prevent phishing attacks. …”
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A comparison of machine learning methods for knowledge extraction model in A LoRa-Based waste bin monitoring system by Zaenal Abidin, Aa Zezen, Othman, Mohd Fairuz Iskandar, Hassan, Aslinda, Murdianingsih, Yuli, Suryadi, Usep Tatang, Siallagan, Timbo Faritchan

“…This research contributes in the form of the KEM system in the classification of scheduling for emptying waste bins with the best performance of the Machine Learning method. The research aims to compare the performance of Machine Learning methods in the form of Decision Tree, Naïve Bayes, K-Nearest Neighbor, Support Vector Machine, and Multi-Layer Perceptron, which will be recommended in the KEM system. …”
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Rainfall variation impact on identification groundwater potential area at Selangor using Random Forest (RF) machine learning method / Muhammad Hakimi Mohd Zain by Mohd Zain, Muhammad Hakimi

“…The groundwater potential map has been generated using ArcGIS Pro and RF machine learning method then illustrated the relationship between rainfall distribution and groundwater potential. …”
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Predicting the rutting parameters of nanosilica/waste denim fiber composite asphalt binders using the response surface methodology and machine learning methods by Al-Sabaeei, Abdulnaser M, Alhussian, Hitham, Abdulkadir, Said Jadid, Giustozzi, Filippo, Jakarni, Fauzan Mohd, Yusoff, Nur Izzi Md

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Predicting the rutting parameters of nanosilica/waste denim fiber composite asphalt binders using the response surface methodology and machine learning methods by Al-Sabaeei, Abdulnaser M, Alhussian, Hitham, Abdulkadir, Said Jadid, Giustozzi, Filippo, Jakarni, Fauzan Mohd, Yusoff, Nur Izzi Md

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A supervised machine-learning method for optimizing the automatic transmission system of wind turbines by Aladwani, Habeeb A. H. R., Ariffin, Mohd Khairol Anuar, Mustapha, Faizal

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A Study on Gradient Boosting Algorithms for Development of AI Monitoring and Prediction Systems by Aziz, N., Akhir, E.A.P., Aziz, I.A., Jaafar, J., Hasan, M.H., Abas, A.N.C.

“…AIM 4.0 utilizes three different ensemble machine learning methods, including Gradient Boost Machine (GBM), Light GBM, and XGBoost for prediction of machine failures. …”
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An Improved Machine Learning Method by applying Cloud Forensic Meta-Model to Enhance the Data Collection Process in Cloud Environments by Al-Mugern, Rafef, Othman, Siti Hajar, Al-Dhaqm, Arafat

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A comparative study of different machine learning methods for landslide susceptibility assessment: a case study of Uttarakhand area (India) by Pham, Binh Thai, Pradhan, Biswajeet, Bui, Dieu Tien, Prakash, Indra, Dholakia, M. B.

“…Landslide susceptibility assessment of Uttarakhand area of India has been done by applying five machine learning methods namely Support Vector Machines (SVM), Logistic Regression (LR), Fisher's Linear Discriminant Analysis (FLDA), Bayesian Network (BN), and Naïve Bayes (NB). …”
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Recent Trends in Artificial Intelligence and Machine Learning Methods Applied to Water Jet Machining by Khan, Rehan, Wieczorowski, Michał, Qureshi, Ariba, Ammar, Muhammad, Ahmed, Tauseef, Khan, Umair

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ExtraImpute: a novel machine learning method for missing data imputation by Alabadla, Mustafa, Sidi, Fatimah, Ishak, Iskandar, Ibrahim, Hamidah, Affendey, Lilly Suriani, Hamdan, Hazlina

“…Its existence usually leads to undesirable results while conducting data analysis using machine learning methods. Recently, researchers have proposed several imputation approaches to deal with missing values in real-world datasets. …”
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Examining text categorization methods for incidents analysis by Mohd Sharef, Nurfadhlina, Kasmiran, Khairul Azhar

“…Results have shown that fuzzy grammar has gotten promising results among the other benchmark machine learning methods.…”
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Oral cancer prognosis based on clinicopathologic and genomic markers using a hybrid of feature selection and machine learning methods by Chang, S.W., Abdul-Kareem, S., Merican, A.F., Zain, R.B.

“…The main aim of this research is to apply a hybrid of feature selection and machine learning methods in oral cancer prognosis based on the parameters of the correlation of clinicopathologic and genomic markers. …”
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Supervised and unsupervised machine learning for cancer classification: recent development by Aina Umairah, Mazlan, Nor Syahidatul Nadiah, Ismail, Noor Azida, Sahabudin, Mohd Saberi, Mohamad, Muhammad Akmal, Remli, Nor Bakiah, Abd. Warif

“…This review will mainly focus on the development of machine learning methods for classification of cancer diseases. …”
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Convolutional neural network model in machine learning methods and computer vision for image recognition: a review by R. M. Q. R., Jaapar, Muhamad Arifpin, Mansor

“…Furthermore, current approaches to image recognition make essential use of machine learning methods. Based on twenty five journal that have been review, this paper focusing on the development trend of convolution neural network (CNNs) model due to various learning method in image recognition since 2000s, which is mainly introduced from the aspects of capturing, verification and clustering. …”
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Data Analysis of Fly Ash Geopolymer Compressive Strength Using Machine Learning Method by Hissyam, Hazmi, Idawati, Ismail, Annisa, Jamali, Mohamad Nazim, Jambli

“…This research is to analyze compressive strength data sets of geopolymer concrete by using the machine learning method. The result comparison of compressive strength is divided into three parameters which are based on molarity, water binder ratio, and the type of activators in the ratio between sodium hydroxide (NaOH) and sodium silicate (Na2SiO3). …”
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