57 results for “supervised learning”

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Research ArticleOpen accessPhrase in the titleComparative Performance of Supervised Learning Algorithms for Flood Prediction in Kemaman, TerengganuNur Najihah Shaaban, Norlida Hassan, Aida Mustapha, Salama A. MostafaFlood is one of the most destructive phenomena all over the world. Because the flooding uncertainties and the urgency to prepare for disaster management, three specific technique approaches are compared in this study to predict the flood occurrence based on historical rainfall data. The study involved the rainfall data in Kemaman, Terengganu between 2017 and 2018 extracted from the official … …Journal of Computer Science, Vol. 17, Issue 5 · 7 May 2021 · 6,887 accessesView PDF Cite

Research ArticleOpen accessPhrase in the titleUnfair Reviews Detection on Amazon Reviews using Sentiment Analysis with Supervised Learning TechniquesElshrif Ibrahim Elmurngi, Abdelouahed GherbiReputation and trust are significantly important and play a pivotal role in enabling multiple parties to establish relationships that achieve mutual benefit especially in an E-Commerce (EC) environment. There are several factors negatively affecting the sight of customers and sellers in terms of reputation. For instance, lack of credibility in providing feedback reviews, by which users might create phantom feedback … …Journal of Computer Science, Vol. 14, Issue 5 · 14 May 2018 · 9,882 accessesView PDF Cite

Research ArticleOpen accessPhrase in the titlePredicting Microbe-Drug Association based on Similarity and Semi-Supervised LearningLingzhi Zhu, Jun Wang, Guixiang Li et al.Increasing clinic evidences have showed that microbial communities play important roles in human health and disease. Predicting hidden microbe-drug associations can be helpful in understanding the microbe-drug association mechanisms in clinical treatment, drug discovery, combinations and repositioning. Some computational methods were proposed to predict the associations of microbes and drugs. However, the prediction performance of these methods needs to be … …American Journal of Biochemistry and Biotechnology, Vol. 17, Issue 1 · 9 Mar 2021 · 7,535 accessesView PDF Cite

Research ArticleOpen accessEvery word in the titleSelf-Supervised Contrastive Learning for Steering Angle Prediction in Autonomous Driving SimulationsMaxson Phang, Suryadiputra LiawatimenaPredicting steering angles is a crucial task in autonomous driving, with end-to-end deep learning being a widely used approach. However, such models often suffer from overfitting to learned trajectories, limiting their generalization to new data. To address this, self-supervised contrastive learning is explored as an alternative, allowing models to learn meaningful representations without labeled data. The primary objective is to … …Journal of Computer Science, Vol. 21, Issue 9 · 20 Oct 2025 · 2,581 accessesView PDF Cite

Research ArticleOpen accessEvery word in the titleSupervised Machine Learning Model-Based Approach for Performance Prediction of StudentsAbdul Razaque, Abrar M. AlajlanPredicting students’ performance is one of the crucial issue for learning contexts, since it helps to develop alternative recommendation systems for academically weak students. Thus, several methods and practices have been applied for educational improvement. However, most of the existing methods do not determine the performance of the students. In this study, we have studied the execution of six machine … …Journal of Computer Science, Vol. 16, Issue 8 · 28 Aug 2020 · 7,082 accessesView PDF Cite

Research ArticleOpen accessEvery word in the titleA Combined Approach to Improve Supervised E-Learning using Multi-Sensor Student Engagement AnalysisAbdulkareem Al-AlwaniE-learning provides an important means of education which can reach masses irrespective of their locations all over the world. The E-learning systems and platforms have evolved over the years, but E-learning methodologies are still lagging in matching the benefits of teacher-student interaction in a classroom. The absence of human supervision is always a concern as a student cannot be monitored … …American Journal of Applied Sciences, Vol. 13, Issue 12 · 12 Dec 2016 · 7,473 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsMachine Learning Oceanographic Data for Prediction of the Potential of Marine ResourcesDenny Arbahri, Oky Dwi Nurhayati, Imam MuditaMarine data and information are very important for human survival, therefore this data and information is attractive to investors because of the potential economic value. This data and information has been difficult to obtain, the solution to overcome this is by analyzing oceanographic data for 2009-2019 collected from the marine database belonging to the Agency for the Study and Application … …Journal of Computer Science, Vol. 20, Issue 2 · 8 Jan 2024 · 5,970 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsCombining Q-Learning and Multi-Layer Perceptron Models on Wireless Channel Quality PredictionAndrea L. Piroddi, Maurizio TorregianiOne of the most complex challenges that wireless communication systems will face in the coming years is the management of the radio resource. In the next years, the growth of mobile devices, forecast (CISCO, 2020), will lead to the coexistence of about 8.8 billion mobile devices with a growing trend for the following years. This scenario makes the reuse of … …American Journal of Engineering and Applied Sciences, Vol. 14, Issue 1 · 10 Mar 2021 · 6,761 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsArtificial Neural Networks Based Red Palm Weevil (Rynchophorus Ferrugineous, Olivier) Recognition SystemSaleh Mufleh Al-Saqer, Ghulam Mubashar HassanProblem statement: The most dangerous insect for the existence of palm trees in entire world is Red Palm Weevil (scientifically named as Rynchophorus Ferrugineous, Oliveir). The proposed research is conducted to develop an identification system for Automated Wireless Red Palm Weevil Detection and exterminated. The core idea of the proposed research is to develop software that can utilize image processing … …American Journal of Agricultural and Biological Sciences, Vol. 6, Issue 3 · 4 Aug 2011 · 9,187 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsKnowledge Representation of Ion-Sensitive Field-Effect Transistor Voltage Response for Potassium Ion Concentration Detection in Mixed Potassium/Ammonium Ion SolutionsWan Fazlida Hanim Abdullah, Mohd Alaudin Mohd Ali, Md Shabiul Islam, Masuri OthmanProblem statement: The Ion-Sensitive Field-Effect Transistor (ISFET) is a metal-oxide field-effect transistor-based sensor that reacts to ionic activity at the electrolye/membrane/gate interface. The ionic sensor faces issue of selectivity from interfering ions that contribute to the sensor electrical response in mixed solutions. Approach: We present the training data collection of ISFET voltage response for the purpose of post-processing stage neural … …American Journal of Applied Sciences, Vol. 7, Issue 1 · 31 Jan 2010 · 7,816 accessesView PDF Cite