Search Results - (( parameter optimization strategy algorithm ) OR ( parameter optimisation _ algorithm ))

A simulation based fly optimisation algorithm for swarms of mini autonomous surface vehicles application by Zainal Abidin, Zulkifli

“…The optimal simulation parameters can be used for the real application. …”
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Sensitivity analysis of GA parameters for ECED problem by Kamil K., Razali N.M.M., Teh Y.Y.

“…The effectiveness of these stochastic search techniques however is heavily dependent on the genetic operators and their parameters. The paper presents the study on sensitivity analysis of the parameters of Genetic Algorithm (GA) for the ECED problem. …”

Optimisation and control of semi-active suspension using genetic algorithm for off-road full vehicle by BenLahcene, Zohir, Faris, Waleed Fekry, Ihsan, Sany Izan, Ridhuan Siradj , Fadly Jashi Darsivan

“…In solving this problem, the genetic algorithms have consistently found near-optimal solutions within specified parameters ranges for several independent runs.…”
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Particle swarm optimization algorithm-based PI inverter controller for a grid-connected PV system by Roslan M.F., Al-Shetwi A.Q., Hannan M.A., Ker P.J., Zuhdi A.W.M.

A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, Fakhrud Din, Shah Khalid, Kamal Zuhairi Zamli, Aftab Alam

“…Although effective, these algorithms get stuck in local optima and need proper parameter tuning for solving optimisation problems. …”
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Enhancing harmony search parameters based on step and linear function for bus driver scheduling and rostering problems by Mansor, Nur Farraliza

“…Optimization is a major challenge in numerous practical world problems.According to the “No Free Lunch (NFL)” theorem,there is no existing single optimizer algorithm that is able to resolve all issues in an effective and efficient manner.It is varied and need to be solved according to the specific capabilities inherent to certain algorithms making it hard to foresee the algorithm that is best suited for each problem.As a result,the heuristic technique is adopted for this research as it has been identified as a potentially suitable algorithm.Alternative heuristic algorithms are also suggested to obtain optimal solutions with reasonable computational effort.However,the heuristic approach failed to produce a solution that nears optimum when the complexity of a problem increases;therefore a type of nature-inspired algorithm known as meta-euristics which utilises an intelligent searching mechanism over a population is considered and consequently used.The meta-heuristic approach is widely used to substitute heuristic terms and is broadly applied to address problems with regards to driver scheduling.However,this meta-heuristic technique is still unable to address the fairness issue in the scheduling and rostering problems.Hence,this research proposes a strategy to adopt an amendment of the harmony search algorithm in order to address the fairness issue which in turn will escalate the level of fairness in driver scheduling and rostering.The harmony search algorithm is classified as a meta-heuristics algorithm that is capable of solving hard and combinatorial or discrete optimisation problems.In this respect,the three main operators in harmony search,namely the Harmony Memory Consideration Rate (HMCR),Pitch Adjustment Rate (PAR) and Bandwidth (BW) play a vital role in balancing local exploitation and global exploration.These parameters influence the overall performance of the HS algorithm,and therefore it is crucial to fine-tune them. …”
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Optimisation of fed-batch fermentation process using deep reinforcement learning by Chai, Wan Ying

“…This research aimed to determine the optimal feeding strategy for fed-batch baker’s yeast fermentation process using the deep reinforcement learning algorithm in maximising the final production of yeast, while minimising the undesired ethanol formation. …”
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Optimised combinatorial control strategy for active anti-roll bar system for ground vehicle by Zulkarnain, N., Zamzuri, H., Saruchi, S. A., Hussain, A., Mokri, S. S., Jedi, A., Razali, N., Mohd Nordin, I. N. A.

“…The objective of this paper is to optimise the proposed control strategy for an active anti-roll bar system using non-dominated sorting genetic algorithm (NSGA-II) tuning method. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, ., Fakhrud, Din, Shah, Khalid, Kamal Z., Zamli, Alam, Aftab

“…Although effective, these algorithms get stuck in local optima and need proper parameter tuning for solving optimisation problems. …”
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Power generation allocation in smart grid using Dwarf Mongoose Optimization / Mohamad Irfan Shamani by Shamani, Mohamad Irfan

“…Dwarf Mongoose Optimization (DMO) is a new metaheuristic algorithm that published in 2022 by Jeffrey O. …”
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Grey wolf optimization for enhanced performance in wind power system with dual-star induction generators by Benamara K., Amimeur H., Hamoudi Y., Abdolrasol M.G.M., Cali U., Ustun T.S.

“…This study investigates strategies for enhancing the performance of dual-star induction generators in wind power systems by optimizing the full control algorithm. …”

An enhanced computational model based on social spider optimisation algorithm for EEG- based emotion recognition by Al-Qammaz, Abdullah Yousef Awwad

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A fuzzy multi-objective optimisation model of risk-based gas detector placement methodology for explosion protection in oil and gas facilities by Idris, A.M., Rusli, R., Nasif, M.S., Ramli, A.F., Lim, J.S.

“…Additionally, a sensitivity analysis was performed to determine the proposed model's response to parameter variations. © 2022 The Institution of Chemical Engineers…”
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SOC Estimation Using Deep Bidirectional Gated Recurrent Units with Tree Parzen Estimator Hyperparameter Optimization by How D.N.T., Hannan M.A., Lipu M.S.H., Ker P.J., Mansor M., Sahari K.S.M., Muttaqi K.M.

On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B., Alsewari, Abdulrahman A.

“…Although useful, strategies based on the aforementioned optimization algorithms are not without limitation. …”
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Recent Development of Grid-Connected Microgrid Scheduling Controllers for Sustainable Energy: A Bibliometric Analysis and Future Directions by Mannan M., Mansor M., Reza M.S., Roslan M.F., Ker P.J., Hannan M.A.

“…This paper seeks to identify and analyze the highly referenced published articles in the relevant area to yield an in-depth analysis of advanced controllers and optimization strategies in MG energy management systems. …”

A review: Use of evolutionary algorithm for optimisation of machining parameters by Zolpakar, N. A., Mohd Fuad, Yasak, Pathak, Sunil

“…Lately, evolutionary algorithm, statistical approaches such as genetic algorithm (GA), particle swarm optimisation (PSO), and cuckoo search algorithm (CSA) have been utilised in simultaneous optimisation of the parameters of the desired outputs and its great potential in optimising machining processes is recognisable.…”
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PSO-LFDE Algorithm on Constrained Real-Parameter Optimisation Test Functions by Nafrizuan, Mat Yahya, Nur Iffah, Mohamed Azmi

“…The proposed PSO-LFDE algorithm is compared with the PSO algorithm by Gaing on single-objective constrained real-parameter optimisation test functions. …”
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Mixed-variable ant colony optimisation algorithm for feature subset selection and tuning support vector machine parameter by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…This paper presents a hybrid classification algorithm, ACOMV-SVM which is based on ant colony and support vector machine.A new direction for ant colony optimisation is to optimise mixed (discrete and continuous) variables.The optimised variables are then feed into selecting feature subset and tuning its parameters are two main problems of SVM.Most approaches related to tuning support vector machine parameters will discretise the continuous value of the parameters which will give a negative effect on the performance. …”
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Advancements in crop water modelling: algorithmic developments and parameter optimization strategies for sustainable agriculture: a review by Sulaiman, Ahmad S. S., Wayayok, Aimrun, Aziz, Samsuzana A., Yun, Wong Mui, Leifeng, Guo

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