Search Results - (( rendering optimization strategy algorithm ) OR ( basic optimisation based algorithm ))

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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Binary ant colony optimization algorithm in learning random satisfiability logic for discrete hopfield neural network by Gao, Yuan, Mohd Kasihmuddin, Mohd Shareduwan, Chen, Ju, Zheng, Chengfeng, Romli, Nurul Atiqah, Mansor, Mohd. Asyraf, Zamri, Nur Ezlin

“…This study introduced a novel ant colony optimization algorithm that implements the population selection strategy of the Estimation of Distribution Algorithm and a new pheromone updating formula. …”
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Development of intelligent evaluation system for product end-of-life selection strategy by Zakri, Ghazalli

“…This study integrates the travelling salesman problem with genetic algorithm (TSP-GA) for finding the optimal disassembly sequence and disassembling the EOL product. …”
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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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Success history moth flow optimization for multi-goal generation dispatching with nonlinear cost functions by Alam, Mohammad Khurshed, Mohd Herwan, Sulaiman, Sayem, Md. Shaoran, Ringku, Md Mahfuzer Akter, Imtiaz, Shahriar, Khan, Rahat

“…Comparing the SHMFO method to other optimization strategies revealed its superiority and proved its capacity to resolve the CEED issue. …”
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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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The advancement of artificial intelligence's application in hybrid solar and wind power plant optimization: a study of the literature by Mauludin, Mochamad Subchan, Khairudin, Moh., Asnawi, Rustam, Mustafa, Wan Azani, Toha, Siti Fauziah

“…Furthermore, this inquiry delves into the optimization strategies of these systems leveraging artificial intelligence methodologies. …”
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Hybrid dynamic scheduling model for flexible manufacturing system with machine availability and new job arrivals by Paslar, Shahla

“…The idea of hybridizing the newly developed biogeography based optimization algorithm (BBO) with variable neighborhood structure (VNS) is proposed in order to produce a high performance initial schedule in terms of minimum completion time, tardiness and flow time within reasonable amount of time. …”
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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

Personalized one-shot local adaptation federated learning for mortality prediction in multi-center Intensive Care Unit by Deng, Ting

“…Step 2 enables highly personalized models as students to rebalance global and local data knowledge through knowledge distillation optimizations. Step 3 automatically evolves the best-fitting parameters for the highly personalized model at each center using an adapted genetic algorithm. …”
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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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Progress in prediction of photocatalytic CO2 reduction using machine learning approach: A mini review by Ali, Md Mohshin, Hossen, Md. Arif, Azrina, Abd Aziz

“…These models can handle extensive experimental datasets, optimize operational parameters, and provide insights into CO2 reduction (CO2R) mechanisms. …”
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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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