Search Results - (( data collaborative learning algorithm ) OR ( java adaptation optimization algorithm ))

Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

Deep reinforcement learning approaches for multi-objective problem in Recommender Systems by Ee, Yeo Keat

“…Besides that, the experiment shows that agent which learning sequential data has earned lower precision by 17.57% and novelty by 4.68% compared to the agent that without learning sequential data, however, it achieved better diversity by 2.66%. …”
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A machine learning approach to tourism recommendations system by Chia, An

“…Scalability problems arise when the system struggles to handle large volumes of data or a growing number of users and items. To overcome this problem, this project implements machine learning algorithms with collaborative filtering, content-based filtering and hybrid filtering approaches. …”
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Data Analysis and Machine Learning Algorithms Evaluation for Bioliq AI-based Predictive Tool by Samuel Simbine, Augusto

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Temporal integration based factorization to improve prediction accuracy of collaborative filtering by Al-Qasem, Al-Hadi Ismail Ahmed

“…The rating matrix typically contains a high percentage of unknown rating scores which is called the data sparsity problem. The data sparsity problem has been solved by several approaches such as Bayesian probabilistic, machine learning, genetic algorithm, particle swarm optimization and matrix factorization. …”
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A collaborative filtering approach using machine learning and business intelligence: a critical review by Muhamad Ibrahim, Najhan, Abiduzzaman, S M, Abdul Raziff, Abdul Rafiez, Shah, Asadullah

“…Specifically, we discovered that combining deep learning techniques with reinforcement learning algorithms enhanced recommendation reliability by 35% while improving user engagement measures by 25%. …”
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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 (AI) in the art and design industry / Fahmi Samsudin by Samsudin, Fahmi

“…It encompasses different types, such as rule-based AI using if-then statements for decision-making, machine learning which employs algorithms to analyze and learn from data, and deep learning utilizing artificial neural networks to learn from extensive datasets. …”
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Improved rsync algorithm to minimize communication cost using multi-agent systems for synchronization in multi-learning management systems by Mwinyi, Amir Kombo

“…This model enhances the interoperability and collaboration of HLIs in terms of synchronization and sharing of learning contents. …”
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A Denoising Generative Adversarial Network Based On Enhanced Feature Mapping Of Data Augmentation For Image Synthesis by Chen, Li

“…Specifically, the generator's ability is enhanced by adding data with noise as an extra input. This requires the generator to learn how to generate images from partially damaged data, leading to better representations learned from the data. …”
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A COLLABORATIVE FRAMEWORK FOR ANDROID MALWARE IDENTIFICATION USING DYNAMIC ANALYSIS by Thayaaleni, Rajandran

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Contextualising Computational Thinking: A Case Study in Remote Rural Sarawak Borneo by Nur Hasheena, Anuar, Fitri Suraya, Mohamad, Jacey Lynn, Minoi

“…The study used observational field notes, comprehension checks, and participants’ learning products as primary data sources. Findings showed that indigenous children’s learning characteristics were primarily ‘learning-by-making’, collaborative, highly motivated, playful, curious, and imaginative while they attempted to learn Computational thinking. …”
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Distributed learning based energy-efficient operations in small cell networks by Mughees, Amna

“…Simulation results demonstrate improved performance in power consumption, load, sum rate, utility, learning rate, convergence, and energy efficiency for small base stations (SBSs) and user equipment (UEs) compared to four benchmarked algorithms, including WMMSE, game theory, Q-learning, and DRL. …”
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Reimagining English language learning: a systematic review of AI integration in classroom practice (2019–2024) by Ibrahim Brian, Muhammad Shyazzwan

“…Grounded in constructivist and socio-cultural theories, these technologies promote collaboration, creativity, and learner autonomy through adaptive learning pathways and real-time feedback. …”
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Early autism spectrum disorder detection using machine learning / Muhammad Shahmi Shahron Nizan by Shahron Nizan, Muhammad Shahmi

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Integrating of web 2.0 technologies for interactive courseware : data structure and algorithm as case study by Mohd Nurhafeezi, Nordin

“…The intention of the developed courseware is not to replace conventional class, but the develop courseware main objective is to assist students of FCSIT for better understanding towards Data Structure and Algorithms Course (TMC1433) through interactive delivering information.…”
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Smart agriculture: precision farming through sensor-based crop monitoring and control system by Mohamad Hakhrani, Asyful Azhim, Abdul Hamid, Syamsul Bahrin

“…Notably, prevalent smart agriculture systems predominantly emphasize either IoT components for data monitoring and control or machine learning components for data analysis. …”
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Estimating Forest Aboveground Biomass Density Using Remote Sensing and Machine Learning : A RSME Approach by Yaniza Shaira, Zakaria, Mohd Fadzil, Akhir, Aidy, M Muslim, Nur Afiqah, Ariffin, Azizul, Ahmad

“…This study employs remote sensing datasets and collaborative efforts with ArcGIS to model AGB density across the Terengganu region. …”
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Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions by Saraswati, Galuh Wilujeng

“…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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A machine learning approach to movie recommendation system by Saw, Zi Jin

“…This project presents a machine learning-based movie recommendation system aimed at providing accurate and personalized movie suggestions while addressing common industry challenges such as biased recommendations, data sparsity, and the cold start problem. …”
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