Search Results - (( intelligence based group algorithm ) OR ( intelligence a learning algorithm ))

User song preferences using preference learning in artificial intelligence by Goh, Beng Jun

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Virtual power plant and microgrids controller for energy management based on optimization techniques by Abdolrasol M.G.M., Mohamed A., Hannan M.A.

Clustering autism spectrum disorder student’s system based on intelligence, skills and behavior using agglomerative clustering algortihm / Daarin Nadia Nordin by Nordin, Daarin Nadia

“…Thus, this project proposes a solution to the problems by utilizing the machine learning approach which is the Agglomerative clustering algorithm. …”
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Assessing the potential of laboratory instructional tool through Synthesia AI: a case study on student learning outcome / Jacqueline Joseph by Joseph, Jacqueline

“…The course was divided into two groups, an experimental group and a control group. …”
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Machine learning of tax avoidance detection based on hybrid metaheuristics algorithms by Masrom, S., Rahman, R.A., Mohamad, M., Rahman, A.S.A., Baharun, N.

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Machine learning of tax avoidance detection based on hybrid metaheuristics algorithms by Masrom, S., Rahman, R.A., Mohamad, M., Rahman, A.S.A., Baharun, N.

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Extreme learning machine for user location prediction in mobile environment by Mantoro, Teddy, Olowolayemo, Akeem, Olatunji, Sunday O., Ayu, Media A., Abu Osman, Md. Tap

“…Purpose – Prediction accuracies are usually affected by the techniques and devices used as well as the algorithms applied. This work aims to attempt to further devise a better positioning accuracy based on location fingerprinting taking advantage of two important mobile fingerprints, namely signal strength (SS) and signal quality (SQ) and subsequently building a model based on extreme learning machine (ELM), a new learning algorithm for single-hidden-layer neural networks. …”
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Extreme learning machine for user location prediction in mobile environment by Mantoro, Teddy, Olowolayemo, Akeem, Olatunji, Sunday O., Ayu, Media Anugerah, Md. Tap, Abu Osman

“…Purpose – Prediction accuracies are usually affected by the techniques and devices used as well as the algorithms applied. This work aims to attempt to further devise a better positioning accuracy based on location fingerprinting taking advantage of two important mobile fingerprints, namely signal strength (SS) and signal quality (SQ) and subsequently building a model based on extreme learning machine (ELM), a new learning algorithm for single-hidden-layer neural networks. …”
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Automated cone cut error detection of bitewing images using convolutional neural network by Mohamed Misbahou Mkouboi, Mohamed Moubarak, Olowolayemo, Akeem, Ghazali, Ahmad Badruddin

“…Introduction: Cone cut error is one of the technical errors that can hinder the important information from a bitewing radiograph. Meanwhile, deep learning is a specialized artificial intelligence method where an algorithm can be trained to automatically detect, classify and give output based on the trained dataset. …”
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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. …”
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Analytical Study Of Machine Learning Models For Stock Trading In Malaysian Market by Hazirah Halul

Operating a reservoir system based on the shark machine learning algorithm by Allawi M.F., Jaafar O., Mohamad Hamzah F., Ehteram M., Hossain M.S., El-Shafie A.

An optimized multi-layer ensemble framework for sentiment analysis by Lai, Po Hung, Alfred Rayner

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A Reinforced Active Learning Algorithm for Semantic Segmentation in Complex Imaging by Usmani, U.A., Watada, J., Jaafar, J., Aziz, I.A., Roy, A.

“…This biases the model performance to the most represented ones. We propose a new reinforced active learning strategy based on a deep reinforcement learning algorithm. …”
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Comprehensive review of drones collision avoidance schemes: challenges and open issues by Rezaee, Mohammad Reza, Abdul Hamid, Nor Asilah Wati, Hussin, Masnida, Ahmad Zukarnain, Zuriati

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Boosting and bagging classification for computer science journal by Wibawa, Aji Prasetya, Putri, Nastiti Susetyo Fanany, Al Rasyid, Harits, Nafalski, Andrew, Hashim, Ummi Rabaah

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Fuzzy subtractive clustering (FSC) with exponential membership function for heart failure disease clustering by Annisa Eka Haryati, ., Sugiyarto, Surono, Tommy Tanu, Wijaya, Goh, Khang Wen, Aris, Thobirin

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Modelling of clinical risk groups (CRGs) classification using FAM by Mohd. Asi, Salina, Saad, Puteh

“…FAM is a fast learning algorithm and used less epoch training [4]. …”
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A flowchart-based multi-agent system for assisting novice programmers with problem solving activities by Hooshyar D., Ahmad R.B., Raj R.G., Nizam M.H.N.M., Yousefi M., Horng S.-J., Rugelj J.

“…In order to address this problem, FMAS, a flowchart-based multi-agent system is developed to familiarize students who have no prior knowledge of programming, with the initial stages in learning programming. …”

Nomadic people optimizer (NPO) for large-scale optimization problems by Mohamd Salih, Sinan Qahtan

“…Good performances were also achieved with the NPO with respect to noise and limited information problems. A Wilcoxon Signed-Rank Test was performed to measure the pair-wise statistical performances of the algorithms and from the results, NPO recorded a better statistical performance compared to the other benchmarking algorithms. …”
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