Search Results - (( developing emerging svm algorithm ) OR ( java implication based algorithm ))

Prediction of COVID-19 outbreak using Support Vector Machine / Muhammad Qayyum Mohd Azman by Mohd Azman, Muhammad Qayyum

“…A prototype architecture and a user-friendly graphical interface tailored for SVM-based outbreak predictions are developed, accompanied by detailed code snippets elucidating essential steps in data loading, encoding, scaling, and SVM model training. …”
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SVM modelling of agarwood oil quality grading using radial basis function (RBF) and sequential minimal optimization (SMO) learning algorithms by Muhammad Haziq Haikal, Hisham, Nurlaila, Ismail, Nor Azah, Mohd Ali, Saiful Nizam, Tajuddin, Mohd Nasir, Taib

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Analysing machine learning models to detect disaster events using social media by Faris Azni Azlan, Mr.

“…To simulate the examining process further, a fuzzy algorithm is developed to automatically rate the severity of a disaster as described in each message in disaster environment. …”

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

“…However, current models often rely on coarse regional data and fail to account for microclimatic variations, limiting their predictive accuracy in dengue hotspots. 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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Applications of machine learning to friction stir welding process optimization by Nasir, Tauqir, Asmaela, Mohammed, Zeeshan, Qasim, Solyali, Davut

“…Machine learning (ML) is a branch of artificial intelligent which involve the study and development of algorithm for computer to learn from data. …”
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Intelligent decision support systems: transforming smart cities management by Ahmed, Zeinab E., Hassan Abdalla Hashim, Aisha, Mokhtar, Rania A., Saeed, Mamoon M.

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Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia by Lay, Usman Salihu

“…The general objective of the study was the development of optimized hybrid debris flow models using airborne laser scanning data and Machine learning algorithms in Malaysia. …”
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A Systematic Review of Metaheuristic Algorithms in Human Activity Recognition : Applications, Trends, and Challenges by John Deutero, Kisoi, Norfadzlan, Yusup, Syahrul Nizam, Junaini

“…Metaheuristic algorithms have emerged as promising techniques for optimizing human activity recognition (HAR) systems. …”
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An automated high-accuracy detection scheme for myocardial ischemia based on multi-lead long-interval ECG and Choi-Williams time-frequency analysis incorporating a multi-class SVM... by Hussein, Ahmed Faeq, Hashim, Shaiful Jahari, Rokhani, Fakhrul Zaman, Wan Adnan, Wan Azizun

“…However, an accurate interpretation of these waveforms still calls for the expertise of an experienced cardiologist. Several algorithms have been developed to overcome issues in this area. …”
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Mental stress classification based on selected electroencephalography channels using correlation coefficient of Hjorth parameters by Hag, Ala, Al-Shargie, Fares, Handayani, Dini Oktarina Dwi, Asadi, Houshyar

“…Leveraging features from the time, frequency, and time–frequency domains of these channels, and employing machine learning algorithms, notably RLDA, SVM, and KNN, our approach achieved a remarkable accuracy of 81.56% with the SVM algorithm outperforming existing methodologies. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Covid-19 Fake News Detection Model On Social Media Data Using Machine Learning Techniques by Liew, Kelvin Kai Xuan

“…Finally, to categorise the covid -19 related dataset, multiple cutting-edge machine learning algorithms were trained. Support Vector Machine (SVM), Naïve Bayes (NB), and Decision Tree (DT) are the machine learning models presented. …”
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Exploring COVID-19 vaccine sentiment: a Twitter-based analysis of text processing and machine learning approaches by Khalaf, Ban Safir, Hamdan, Hazlina, Manshor, Noridayu

“…Social media platforms, especially Twitter, have emerged as rich sources for gauging public opinion. …”
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A review on classifying and prioritizing user review-based software requirements by Salleh, Amran, Said, Mar Yah, Osman, Mohd Hafeez, Hassan, Sa’Adah

“…Investigating the potential of emerging machine learning models and algorithms to improve classification and prioritization accuracy is crucial. …”
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Sentiment analysis for airline services on Twitter using deep learning with word embedding / Mawada Mohamed Nour El Daim El Khalifa by Mawada Mohamed , Nour El Daim El Khalifa

“…Meanwhile, in recent years, Deep Learning algorithms for Sentiment Analysis has emerged as one of the most popular algorithms, which provides automatic feature extraction, rich representation capabilities, and better performance than most of the traditional learning algorithms. …”
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Internet of Things-based Home Automation with Network Mapper and MQTT Protocol by Alam T., Rokonuzzaman M., Sarker S., Abadin A.F.M.Z., Debnath T., Hossain M.I.

“…The proposed system is developed using a Raspberry Pi 3 Home Server (RHS) driven by the Support Vector Machine (SVM) algorithm. …”

Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

COVID-19 fake news detection model on social media data using machine learning techniques by Kai Xuan, Kelvin Liew, Bhuiyan, Mohaiminul Islam, Nur Shazwani, Kamarudin, Ahmad Fakhri, Ab Nasir, Muhammad Zulfahmi, Toh Abdullah@ Toh Chin Lai

“…Finally, to categorize the COVID -19 related dataset, multiple cutting-edge machine-learning algorithms were trained. Support Vector Machine (SVM), Naïve Bayes (NB), and Decision Tree (DT) are the machine learning models presented. …”
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Advances in remote sensing technology, machine learning and deep learning for marine oil spill detection, prediction and vulnerability assessment by Yekeen, S.T., Balogun, A.-L.

“…The Support Vector Machine (SVM) and Artificial Neural Network (ANN) are the most used machine learning algorithms for oil spill detection, although the restriction of ML models to feed forward image classification without support for the end-to-end trainable framework limits its accuracy. …”
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An enhanced feature selection and cancer classification for microarray data using relaxed Lasso and support vector machine by Aina Umairah, Mazlan, Noor Azida, Sahabudin, Muhammad Akmal, Remli, Nor Syahidatul Nadiah, Ismail, Adenuga, Kayode I.

“…This chapter proposed relaxed Lasso and support vector machine (rL-SVM) for selecting features and classifying cancer. …”
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