Search Results - intelligence re ((mining algorithm) OR (learning algorithm))

Improving Patient Rehabilitation Performance In Exercise Games Using Collaborative Filtering Approach by Waidah Ismail, Ismail Ahmed Al-Qasem Al-Hadi, Crina Grosan, Rimuljo Hendradi

Artificial intelligence in sustainability reporting / Prof. Dr Corina Joseph by Joseph, Corina

“…In the speech introduction, various definitions of Artificial Intelligence (AI) were provided. One of these definitions describes AI as the utilization of automated algorithms, robotics, or machines that mimic human cognitive functions, enabling them to perform tasks such as learning, identifying, analyzing, and problem-solving (Graham et al., 2020). …”
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Usability prioritization using performance metrics and hierarchical agglomerative clustering in MAR-learning application by Cheng L.K., Selamat A., Mohamed Zabil M.H., Selamat M.H., Alias R.A., Puteh F., Mohamed F., Krejcar O.

Modular deep neural network in reducing overfitting to enhance generalization / Mohd Razif Shamsuddin by Shamsuddin, Mohd Razif

“…Machine Learning (ML) and Artificial Intelligence (AI) are a hype in this new age. …”
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Optimizing mobile robot navigation through neuro-symbolic fusion of Deep Deterministic Policy Gradient (DDPG) and fuzzy logic by Nasary, Muhammad Faqiihuddin, Mohd Ibrahim, Azhar, Al Mahmud, Suaib, Shafie, Amir Akramin, Mardzuki, Muhammad Imran

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Geospatial AI-based approach to assess the spatiotemporal suitability of onshore wind-solar farms in Iraq by Sachit, Mourtadha Sarhan Almushattat

“…In this context, global geospatial data for 13 conditioning factors were collected, and 55,619 inventory samples of wind and solar stations worldwide were prepared to train three machine learning (ML) algorithms, namely Random Forest (RF), Support Vector Machine (SVM), and Multi-Layer Perceptron (MLP). …”
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Design of intelligent control system and its application on fabricated conveyor belt grain dryer by Lutfy, Omar F.

“…Moreover, three evolutionary algorithms (EAs), in particular a real-coded genetic algorithm (GA), a particle swarm optimization (PSO), and a global-best harmony search (GHS), were separately used to train the proposed controller and to determine its scaling factors. …”
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Enhancing teaching and learning through data-driven optimization of servicing code demand and lecturer allocation using WEKA analysis by Rochin Demong, Nur Atiqah, Mohamed Razali, Murni Zarina, Kamaruddin, Juliana Noor, Shamsuddin, Sazwan, Awang, Nor Ain, Kamarudin, Norjuliatie, Wan Othman, Noor Faradilla

“…These results identifying course approval status and demand trends. These re suggest that machine learning driven approaches can effectively support academic administrations in making informed staffing decisions, balancing full time and part time lecturer assignments, and optimizing cost structures without compromising teaching quality. …”
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