Search Results - (( intelligence practices scheduling algorithm ) OR ( intelligence system force algorithm ))

Intelligent Optimization of Force Tracking Parameters for MR Damper Modelling using Firefly Algorithm by Mat Hussin, Ab Talib, Hanim, Mohd Yatim, Nik Mohd Ridzuan, Shaharuddin, Muhamad Sukri, Hadi, Intan Zaurah, Mat Darus, Annisa, Jamali

“…To overcome this problem, an intelligent optimization method known as firefly algorithm (FA) was used by this study to optimize the force tracking controller (FTC) parameters as to achieve the exact damping force of MR damper system. …”
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A study of packet scheduling algorithms in long term evolution-advanced by Ul Islam Mattoo, Mohd Mueen, Mohd. Ramli, Huda Adibah

“…The simulation results obtained demonstrate the efficacy of RM2 scheduling algorithm over other scheduling algorithms in maximizing the system capacity and is more robust on the effect of the cellular channel impairments.…”
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Intelligent active force control of a robotic arm using genetic algorithm by Mailah, Musa, Wong, Min Yee, Jamaluddin, Hishamuddin

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An Intelligent Active Force Control Algorithm to Control an Upper Extremity Exoskeleton for Motor Recovery by Wan Hasbullah, Mohd Isa, Zahari, Taha, Ismail, Mohd Khairuddin, Anwar, P. P. A. Majeed, Khairul Fikri, Muhammad, Ali, Mohammed A. H., Jamaluddin, Mahmud, Zulkifli, Mohamed

“…A proportional-derivative (PD) architecture is employed in this study to investigate its efficacy performing joint-space control objectives. An intelligent AFC algorithm is also incorporated into the PD to investigate the effectiveness of this hybrid system in compensating disturbances. …”
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A fuzzy-active force based control architecture for characterizing a nonlinear MIMO system / Tengku Luqman Tengku Mohamed by Tengku Mohamed, Tengku Luqman

“…This study examines the modelling and control of a twin rotor multi-input multi-output (MIMO) system (TRMS). An intelligent Active Force Control (AFC) scheme is utilised to compensate disturbances that a conventional PID control algorithm alone is unable to due to the system’s highly nonlinear behaviour. …”
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Non-pressurized magnetorheological damper controlled using fuzzy semi active damping force estimator (fSADE) by Saiful Anuar, Abu Bakar, Hishamuddin, Jamaluddin, Roslan, Abd Rahman, Pakharuddin, Mohd Samin, Ryosuke, Masuda, Hiromu, Hashimoto, Takeshi, Inaba

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An improved fair nurse scheduling optimisation using particle swarm intelligent technique by Ramli, Mohamad Raziff

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Improving real-time multimedia scheduling in practical mobile cellular channels by Mohd. Ramli, Huda Adibah, Mohd. Isa, Farah Nadia

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Optimization and control of hydro generation scheduling using hybrid firefly algorithm and particle swarm optimization techniques by Hammid, Ali Thaeer

“…To deal with these problems, this thesis introduces three approved intelligent controllers for hydropower generation. Firstly, a hybrid algorithm namely firefly particle swarm optimization (FPSO) and series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed. …”
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Energy management scheduling for microgrids in the virtual power plant system using artificial neural networks by Abdolrasol M.G.M., Hannan M.A., Suhail Hussain S.M., Ustun T.S., Sarker M.R., Ker P.J.

Series division method based on PSO and FA to optimize Long-Term Hydro Generation Scheduling by Hammid, Ali Thaeer, M. H., Sulaiman

“…To deal with this complicated problem, Series division method (SDM) based on the practical swarm optimization and the firefly algorithm is proposed in this paper. …”
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Intelligent material handling mobile robot for industrial purpose with active force control capability by Mailah, Musa, Jamaluddin, Hishamuddin, Pitowarno, Endra, Purnomo, Didik Setyo

“…A number of disturbances in the form of vibratory and impact forces are deliberately introduced into the system to evaluate the system performances. …”
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Active force control with iterative learning control algorithm for a vehicle suspension by Rosmazi, Rosli

“…The research focuses on the application of an active force control (AFC) strategy with iterative learning control (ILC) algorithms to compensate for the various introduced road profiles or 'disturbances' in a quarter car suspension system as an improvement to ride comfort performance. …”
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Intelligent adaptive active force control of a robotic arm with embedded iterative learning algorithms by Mailah, Musa, Ong, Miaw Yong

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An Intelligent System Approach to the Dynamic Hybrid Robot Control by Md. Yeasin, Md. Mahmud Hasan

“…To derive a complete intelligent state-of-the-art hybrid control system, several experiments were conducted in the study. …”
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Development of a robust intelligent controller for a semi-active car suspension system by Abas, Hesham Ahmed Abdul Mutleba

“…Semi-active suspension systems outperformed passive and active suspension systems because it contains an intelligent actuator that can give the appropriate force to dissipate unwanted vibration using intelligent and real-time controllers. …”
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Automatic prehension using an accelerometer and force sensor by Ahmad, Siti Anom, Chappell, Paul H., Ali, Mohd Liakot

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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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Classification Algorithms and Feature Selection Techniques for a Hybrid Diabetes Detection System by Al-Hameli, Bassam Abdo, Alsewari, Abdulrahman A., Alraddadi, Abdulaziz Saleh, Aldhaqm, Arafat

“…Several combinations of Harmony search algorithm, genetic algorithm, and particle swarm optimization algorithm are examined with K-means for feature selection. …”
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Online DE optimization for Fuzzy-PID controller of semi-active suspension system featuring MR damper by Ahmed, Hesham, As’arry, Azizan, Hairuddin, Abdul Aziz, Hassan, Mohd Khair, Liu, Yunyun, Onwudinjo, Erasmus Cufe Ujunwa

“…The semi-active suspension system outperformed other suspension systems because it contains an intelligent actuator that can give the appropriate force to dissipate unwanted vibration using intelligent and real-time controllers. …”
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