Search Results - (( using gamification learning algorithm ) OR ( basic optimisation based algorithm ))

Open access for gamification: a systematic review of literature across disciplines by Zakaria, Noor Syamilah, Saripan, M. Iqbal, Subarimaniam, Neerushah, Ismail, Alyani

“…With the increasing need for developing effective learning methods, gamification has been widely used as a tool to improve the desire and interest in learning. …”
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Self learning module on securing IPV6 deployment / Muhamad Nazif Shahaimi Zaha by Zaha, Muhamad Nazif Shahaimi

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Enhanced convergence of Bat Algorithm based on dimensional and inertia weight factor by Ramli, Mohamad Raziff, Abal Abas, Zuraida, Desa, Mohammad Ishak, Zainal Abidin, Zaheera, Al Azzam, Malik Bader Hasan

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Gamification of Regional Tourism Engagement: Analysis and Design of a Web-Based Information System by Johannes Hamonangan, Siregar, Rufman Iman, Akbar, Augury, El Rayeb, Chaerul, Anwar, Suriati Khartini, Jali, Mohamad Imran, Bandan, Phei Chin, Lim, Abby Lian, Hendrick

“…The system integrates a structured gamification algorithm with a scalable relational database model, built using React.js and Firebase, to ensure responsive and consistent user experiences. …”
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Designing machine learning frameworks for intelligence and gamification research / Nordin Abu Bakar by Abu Bakar, Nordin

“…The knowledge will be stored, used, referred, postulated and reasoned with. Those activities define learning in its own specific domain and context. …”
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Parametric modelling of a TRMS using dynamic spread factor particle swarm optimisation by Toha, Siti Fauziah, Abd Latiff, I., Mohamad, M., Tokhi, M Osman

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Local search manoeuvres recruitment in the bees algorithm by Muhamad, Zaidi, Mahmuddin, Massudi, Nasrudin, Mohammad Faidzul, Sahran, Shahnorbanun

“…Swarm intelligence of honey bees had motivated many bioinspired based optimisation techniques. The Bees Algorithm (BA) was created specifically by mimicking the foraging behavior of foraging bees in searching for food sources.During the searching, the original BA ignores the possibilities of the recruits being lost during the flying.The BA algorithm can become closer to the nature foraging behavior of bees by taking account of this phenomenon.This paper proposes an enhanced BA which adds a neighbourhood search parameter which we called as the Local Search Manoeuvres (LSM) recruitment factor.The parameter controls the possibilities of a bee extends its neighbourhood searching area in certain direction.The aim of LSM recruitment is to decrease the number of searching iteration in solving optimization problems that have high dimensions.The experiment results on several benchmark functions show that the BA with LSM performs better compared to the one with basic recruitment.…”
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Unit commitment in power system using multi-agent evolutionary programming incorporating priority listing optimisation technique / Muhammad Nazree Che Othman by Che Othman, Muhammad Nazree

“…The search process then being refined using heuristic EP-based algorithm with multi-agent approach to produce the final solution. …”
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Handover Parameter for Self-optimisation in 6g Mobile Networks: A Survey by Ukasyah Mahamod, Ibraheem Shayea, Hafizal Mohamad, Marinah Othman, Fauzun Abdullah Asuhaimi

Instance matching framework for heterogeneous semantic web content over linked data environment by Mansir, Abubakar

“…These discovered attributes serve as input to a modified training set generation component, where training sets are generated based on the potential attributes’ clusters. Property alignment check the irregular data associated to the generated sets to optimise the matching performance. …”
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Gravitational energy harvesting system based on multistage braking technique for multilevel elevated car parking building by Al Kubaisi, Yasir Mahmood

“…Applying a methodology based on three basic aspects; Firstly, designing a (GEH) structure of a scaled-down prototype for the actual system describing the mechanism of the energy harvesting, which is inspired by the elevator structures. …”
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Abnormal event detection in video surveillance / Lim Mei Kuan by Lim, Mei Kuan

“…Therefore, by considering tracking as an optimisation problem, the proposed SwATrack algorithm searches for the optimal distribution of motion model without making prior assumptions, or prior learning of the motion model. …”
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