Search Results - (((matching OR machine) algorithm) OR (((means algorithm) OR (learning algorithm))))

A Recent Research on Malware Detection Using Machine Learning Algorithm: Current Challenges and Future Works by Gorment N.Z., Selamat A., Krejcar O.

“…Barium compounds; Cybersecurity; Data mining; Decision trees; Evolutionary algorithms; K-means clustering; Learning algorithms; Malware; Network security; Sodium compounds; Support vector machines; 'current; Comparatives studies; Cyber security; K-means; Machine learning algorithms; Malware attacks; Malware detection; Metaheuristic; Recent researches; Systematic literature review; Nearest neighbor search…”

Music Recommender System Using Machine Learning Content-Based Filtering Technique by Foong, Kin Hong

“…These are the popular algorithm for unsupervised learning, a machine learning method to analyse and cluster datasets. …”
Get full text
Get full text

Elucidating the effect of process parameters on the production of hydrogen-rich syngas by biomass and coal Co-gasification techniques: A multi-criteria modeling approach by Bahadar A., Kanthasamy R., Sait H.H., Zwawi M., Algarni M., Ayodele B.V., Cheng C.K., Wei L.J.

“…Biomass; Coal; Complex networks; Errors; Forecasting; Gasification; Hydrogen production; Learning algorithms; Mean square error; Neural networks; Regression analysis; Sensitivity analysis; Support vector machines; Co-gasification; Gaussian process regression; Hydrogen-rich syngas; Machine learning algorithms; Machine-learning; Neural-networks; Process parameters; Regression model; Support vectors machine; Syn gas; Synthesis gas; coal; hydrogen; synfuel; biomass; chemical reaction; detection method; hydrogen; machine learning; multicriteria analysis; algorithm; Article; artificial neural network; biomass; controlled study; gasification; Gaussian processing regression; linear regression analysis; machine learning; mean absolute error; mean square error; parameters; prediction; root mean square error; sensitivity analysis; support vector machine; temperature; Bayes theorem; biomass; Bayes Theorem; Biomass; Coal; Hydrogen; Temperature…”

Quantifying usability prioritization using K-means clustering algorithm on hybrid metric features for MAR learning by Lim K.C., Selamat A., Mohamed Zabil M.H., Selamat M.H., Alias R.A., Puteh F., Mohamed F., Krejcar O.

“…Augmented reality; Learning algorithms; Machine learning; Usability engineering; Between clusters; Mobile augmented reality; Prioritization; Prioritization techniques; Unsupervised machine learning; Usability; K-means clustering…”

Streamflow Prediction Utilizing Deep Learning and Machine Learning Algorithms for Sustainable Water Supply Management by Latif S.D., Ahmed A.N.

Subjects:

Comparative analysis of machine learning algorithms for rainfall prediction in Kuantan, Pahang, Malaysia by Seri Liyana, Ezamzuri, Sarah ‘Atifah, Saruchi, Ammar A., Al-Talib

“…The analysis shows that the SVR consistently outperforms the other machine learning algorithms, achieving the lowest Mean Absolute Error (MAE) and Mean Squared Error (MSE).…”
Get full text
Get full text
Get full text

Comparison of Electricity Load Prediction Errors Between Long Short-Term Memory Architecture and Artificial Neural Network on Smart Meter Consumer by Salleh N.S.M., Suliman A., J�rgensen B.N.

“…Brain; Errors; Forecasting; Learning algorithms; Mean square error; Memory architecture; Network architecture; Smart meters; Time series; Demand-side; Electricity load; Error values; Load predictions; Machine learning algorithms; Mean absolute error; Mean squared error; Prediction errors; Regression problem; Times series; Long short-term memory…”

Prediction of Machine Failure by Using Machine Learning Algorithm by Fakhrurazi, Nur Amalina

“…Then, the data is cluster by using K Means to produce labeled input that will be trained by using Gradient Boosting Machine, a decision tree algorithm to make prediction. …”
Get full text
Get full text

Machine learning based-model to predict catalytic performance on removal of hazardous nitrophenols and azo dyes pollutants from wastewater by Khan M.S.J., Sidek L.M., Kumar P., Alkhadher S.A.A., Basri H., Zawawi M.H., El-Shafie A., Ahmed A.N.

Subjects:

Evaluating enhanced predictive modeling of foam concrete compressive strength using artificial intelligence algorithms by Abdellatief M., Wong L.S., Din N.M., Mo K.H., Ahmed A.N., El-Shafie A.

Subjects:

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 Predicting Reservoir Water Level by Sammen S.S., Ehteram M., Sheikh Khozani Z., Sidek L.M.

Subjects:

Advanced machine learning algorithm to predict the implication of climate change on groundwater level for protecting aquifer from depletion by Ahmed Osman A.I., Latif S.D., Wee Boo K.B., Ahmed A.N., Huang Y.F., El-Shafie A.

Subjects:

Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

Subjects:

Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

“…Unlike the classical kNN algorithm which is a regression type algorithm, the proposed localisation algorithms utilise machine learning classification for both linear and kernel types. …”
Get full text
Get full text

Development of an intelligent information system for financial analysis depend on supervised machine learning algorithms by Lei, X., Mohamad, U.H., Sarlan, A., Shutaywi, M., Daradkeh, Y.I., Mohammed, H.O.

“…In the financial sector, machine learning algorithms are used to detect fraud, automate trading, and provide financial advice to investors. …”
Get full text
Get full text

Real time long range (LoRa) based indoor positioning system using Deep Gaussian Process (DGP) algorithm / Ng Tarng Jian by Ng, Tarng Jian

“…Through experimental evaluation and comparison of various machine learning algorithms, including Deep Gaussian Process (DGP) regression, the research demonstrates the effectiveness of DGPs in achieving precise single-point estimation, by keeping the mean absolute error to below 5 meters. …”
Get full text
Get full text
Get full text

Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms by Al-Rawashdeh, Mohammad, Al Nawaiseh, Moh’d, Yousef, Isam, Bisharah, Majdi, Alkhadrawi, Sajeda, Al-Bdour, Hamza

“…Bayesian Optimization optimizes machine learning algorithm hyperparameters to solve this problem. …”
Get full text
Get full text

Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

“…In this article, we present the exploration on the combination of the clustering based algorithm with an ensemble classification learning. …”
Get full text
Get full text
Get full text

Elucidating the effect of process parameters on the production of hydrogen-rich syngas by biomass and coal Co-gasification techniques: A multi-criteria modeling approach by Bahadar, A., Kanthasamy, R., Sait, H.H., Zwawi, M., Algarni, M., Ayodele, B.V., Cheng, C.K., Wei, L.J.

“…A total of 12 machine learning algorithms which comprises the regression models, SVM, GPR, and ANN were configured, trained using 124 datasets. …”
Get full text
Get full text

Predicting longitudinal dispersion coefficient using ensemble models and optimized multi-layer perceptron models by Gholami M., Ghanbari-Adivi E., Ehteram M., Singh V.P., Najah Ahmed A., Mosavi A., El-Shafie A.

Subjects: