Search Results - (( evolution optimization clustering algorithm ) OR ( course optimization method algorithm ))

An adaptive HMM based approach for improving e-Learning methods by Deeb B., Hassan Z., Beseiso M.

“…This adaptive algorithm can thus be applied to any e-learning platform for optimal content delivery to its users in real-time. © 2014 IEEE.…”

Enhancing clustering algorithm with initial centroids in tool wear region recognition by Kasim, Nur Adilla, Nuawi, Mohd Zaki, Abdul Ghani, Jaharah, Ngatiman, Nor Azazi, Che Haron, Che Hassan, Muhammad Rizal

“…Autonomous manufacturing allows the system to distinguish between a mild, normal and total failure in tool condition. K-means clustering has become the most applied algorithm in discovering classes in an unsupervised scenario. …”
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A novel clustering based genetic algorithm for route optimization by Aibinu, Abiodun Musa, Salau, Habeeb Bello, Najeeb, Athaur Rahman, Nwohu, Mark Ndubuka, Akachukwu, Chichebe

“…It was also observed that the introduction of clustering based selection algorithm guaranteed the selection of cluster with the optimal solution in every generation. …”
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Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm by Vincent Chung, Hamzarul Alif Hamzah, Norah Tuah, Kit, Guan Lim, Min, Keng Tan, Kenneth Tze Kin Teo

“…Genetic-based evolutionary algorithms such as Genetic Algorithm (GA) and Differential Evolution (DE) have been popularly used to optimize cluster head selection in WSN to improve energy efficiency for the extension of network lifetime. …”
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Broadening selection competitive constraint handling algorithm for faster convergence by Shaikh, T.A., Hussain, S.S., Tanweer, M.R., Hashmani, M.A.

“…In this study, the BSCCH algorithm has been coupled with Differential Evolution algorithm as a proof of concept because it is found to be an efficient algorithm in the literature for constrained optimization problems. …”
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Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

“…Nature-inspired optimization-based clustering techniques are powerful, robust and more sophisticated than the conventional clustering methods due to their stochastic and heuristic characteristics. …”
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Seed disperser ant algorithm for optimization / Chang Wen Liang by Chang , Wen Liang

“…The optimal results obtained for constrained engineering problems as well as data clustering are very promising in terms of quality of solutions and convergence speed of the algorithm.…”
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Descriptive analysis of patient diet trends at Pantai Hospital Ayer Keroh by Muhidin, Nurain Fatiha

“…Identifying the clustering results enables targeted meal planning based on patient group characteristics and helps optimize resources by understanding dietary demand within each cluster. …”
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Dealing with Routing Hole Problem in Multi-hop Hierarchical Routing Protocol in Wireless Sensor Network by Sama, Najm Us

“…Further evolution of the ELEC routing protocol is presented to evaluate the impact of incremental cluster iv heads on the performance of WSN. …”
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A harmony search algorithm for university course timetabli by Al-Betar, Mohammed Azmi, Khader, Ahamad Tajudin

“…The major thrust of this algorithm lies in its ability to integrate the key components of population-based methods and local search-based methods in a simple optimization model. …”
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Meta-Heuristic Algorithms for Learning Path Recommender at MOOC by Son, N.T., Jaafar, J., Aziz, I.A., Anh, B.N.

“…We have developed Metaheuristic algorithms includes the Genetic Algorithm (GA) and Ant Colony Optimization Algorithm (ACO), to solve the proposed model. …”
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Adapting And Hybridising Harmony Search With Metaheuristic Components For University Course Timetabling by Al-Betar, Mohammed Azmi

“…Harmony Search Algorithm (HSA) is a recent metaheuristic population-based method. …”
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Harmony great deluge for solving curriculum based course timetabling problem by Wahid, Juliana, Mohd Hussin, Naimah

“…University course timetabling which has been determined as non deterministic polynomial problem that accept widely as problem that are intractable.An efficient algorithm does not exist that is guaranteed to find an optimal solution for such problems.The design of good algorithm to find new methods and techniques to solve such problem is a very active area of research.This paper presents the adaption of the hybridizing between harmony search with great deluge algorithm for solving curriculum-based course timetabling problems.The algorithm can be adapted to the problem.Results were not comparatively better than those previously known as best solution.Proper modification in terms of the approach in this algorithm would make the algorithm perform better on curriculum-based course timetabling.…”
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Hybridizing harmony search with local search based metaheuristic for solving curriculum based university course timetabling / Juliana Wahid by Wahid, Juliana

“…The real data of UUM CAS timetable was analyzed and processed using the proposed algorithms. The result shows that the quality cost of UUM CAS course timetabling produced by the proposed algorithms is better compared to the course timetable produced by the ready-made software package. …”
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Evaluate the performance of university timetabling problem with various artificial intelligence techniques by Hooi, Charmaine Wai Yee

“…Over time, numerous algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Simulated Annealing (SA), and other approaches have been introduced to address the challenges of optimizing class schedules. …”
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Web based personalized university timetable for UiTM students using genetic algorithm / Mohd Radhi Fauzan Jamli and Ahmad Firdaus Ahmad Fadzil by Jamli, Mohd Radhi Fauzan, Ahmad Fadzil, Ahmad Firdaus

“…The proposed approach utilizes genetic algorithms to dynamically produce optimized timetables based on individual student needs, with real-time data scraping from 'iCRESS' ensuring the system stays up to date with the latest course information for accurate timetable generation. …”
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Investigating a round robin strategy over multi algorithms in optimising the quality of university course timetables by Abdullah S., Shaker K., Shaker H.

“…The performance of the approach is tested with over two sets of benchmark datasets, that is, enrolment-based course timetabling and curriculum-based course timetabling (UD1) in comparison with a set of state-of-the-art methods from the literature. …”

Enhancing hyperparameters of LSTM network models through genetic algorithm for virtual learning environment prediction by Ismanto, Edi, Ab Ghani, Hadhrami, Md Saleh, Nurul Izrin

“…Genetic algorithms for hyperparameter optimization significantly contributed, with the GA + LSTM + ADAGRAD model achieving 88% and 87% accuracy in the 7th and 9th models for BBB course data. …”
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Graph theory approach for managing lecturers’ schedule using graph colouring method / Siti Nor Ba Basri, Nur Su’aidah Khozaid and Farhana Hazwani Ismail by Basri, Siti Nor Ba, Khozaid, Nur Su’aidah, Ismail, Farhana Hazwani

“…In this study, the scheduling problem is represented as a graph where vertices represent time slots and edges represent conflicts or dependencies between courses and lecturers. Different colours are allocated to each vertex using graph colouring techniques such as the vertices algorithm or the edges algorithm, ensuring that clashing courses and lecturers are assigned different time slots. …”
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Hybridizing harmony search with local search based metaheuristic for solving curriculum based university course timetabling / Juliana Wahid by Wahid, Juliana

“…Thus, this thesis proposed hybrid algorithms between HSA and local search based methods (simulated annealing (SA) and/or great deluge (GD)) to enhance the HSA performance for solving curriculum-based course timetabling (CBCTT) problem which is the variant of UCTP. …”
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