Search Results - (( problem recommendations from algorithm ) OR ( java application optimization algorithm ))
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Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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Thesis -
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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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Conference or Workshop Item -
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Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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Conference or Workshop Item -
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Route Optimization System
Published 2005“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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Final Year Project -
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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Article -
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Ant colony optimization algorithm for load balancing in grid computing
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Monograph -
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Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT
Published 2006“…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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Thesis -
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A machine learning approach to tourism recommendations system
Published 2025“…The main problem encountered when developing a powerful recommendation system is cold start problem, data sparsity and scalability problems. …”
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Final Year Project / Dissertation / Thesis -
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Content-based recommender system for an academic social network / Vala Ali Rohani
Published 2014“…Four metrics, namely precision, recall, fallout, and F1 were employed to measure the prediction accuracy of each algorithm. Although the experiment conducted presented some threats, the results indicated that the ECSN algorithm not only improves the prediction accuracy of recommendations but also resolves the cold start problem in the existing recommender systems algorithms.…”
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Book recommender mobile application / Amir Imran Kamaludin
Published 2021“…In this project, it presented a model for a personalized collaborative filtering book recommendation system. It are takes some information from user through signup which will help to get more appropriate recommendations based on individual user item rating and thus an attempt to overcome cold start problem. …”
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Examination timetabling using genetic algorithm case study: KUiTTHO
Published 2005“…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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Thesis -
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Cuti – cuti Malaysia recommender system using Ant Colony Optimization (ACO) / Nur Maisarah Zulkifli
Published 2017“…Execution of the ACO algorithm shows that the algorithm able to produce optimum solution towards the said problem.…”
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Student Project -
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Deep reinforcement learning approaches for multi-objective problem in Recommender Systems
Published 2022“…On the other hand, the evolutionary algorithm is notorious with premature convergence issue and suffering from curse of dimensionality. …”
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Thesis -
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Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO
Published 2005“…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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Thesis -
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Multiobjective deep reinforcement learning for recommendation systems
Published 2022“…Existing multi-objective (MO) RSs employed collaborative filtering and combined with evolutionary algorithms to handle bi-objective optimization. Besides cold-start problem from collaborative filtering, it also vulnerable to highly sparse environment, while the evolutionary algorithm suffers from premature convergence and curse of dimensionality. …”
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Article -
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Multi-objective deep reinforcement learning for recommendation systems
Published 2022“…Existing multi-objective (MO) RSs employed collaborative filtering and combined with evolutionary algorithms to handle bi-objective optimization. Besides cold-start problem from collaborative filtering, it also vulnerable to highly sparse environment, while the evolutionary algorithm suffers from premature convergence and curse of dimensionality. …”
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