Search Results - (( parameter optimization modified algorithm ) OR ( loading optimisation based algorithm ))

An enhanced support vector regression -African Buffalo optimisation algorithm for electricity time series forecasting by Maijama'a, Inusa Sani

“…The study presents a series of hybrid algorithms that leverage ABO to optimize SVR hyperparameters. …”
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Optimization of modified Bouc–Wen model for magnetorheological damper using modified cuckoo search algorithm by Rosmazi, Rosli, Zamri, Mohamed

“…This article presents a new modified cuckoo search algorithm with dynamic discovery probability and step-size factor for optimizing the Bouc–Wen Model in magnetorheological damper application. …”
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Optimising cloud computing performance with an enhanced dynamic load balancing algorithm for superior task allocation by Zhanuzak, Raiymbek, Ala'anzy, Mohammed Alaa, Othman, Mohamed, Algarni, Abdulmohsen

“…This paper presents an Enhanced Dynamic Load Balancing (EDLB) algorithm designed to optimise task scheduling and resource allocation in cloud environments. …”
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Performance evaluation of load balancing algorithm for virtual machine in data centre in cloud computing by Parmesivan, Yuganes, Hasan, Sazlinah, Muhammed, Abdullah

“…Cloud computing has become biggest buzz in the computer era these days.It runs entire operating systems on the cloud and doeverything on cloud to store data off-site.Cloud computing is primarily based on grid computing, but it’s a new computational model.Cloud computing has emerged into a new opportunity to further enhance way of hosting data centre and provide services.The primary substance of cloud computing is to deal the computing power,storage,different sort of stages and services which assigned tothe external users on demand through the internet.Task scheduling in cloud computing is vital role optimisation and effective dynamic resource allocation for load balancing.In cloud, the issue focused is under utilisation and over utilisation of the resources to distribute workload of multiple network links for example,when cloud clients try to access and send request tothe same cloud server while the other cloud server remain idle at that moment, leads to the unbalanced of workload on cloud data centers.Thus, load balancing is to assign tasks to the individual cloud data centers of the shared system so that no single cloud data centers is overloaded or under loaded.A Hybrid approach of Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm is combined in order to get effective response time.The proposed hybrid algorithm has been experimented by using CloudSim simulator.The result shows that the hybrid load balancing algorithm improves the cloud system performance by reducing the response time compared to the Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm.…”
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Modified Harmony Search by Najihah, Mohamed, Ahmad Lutfi, Amri Ramli, Ahmad, Abd Majid, Abd Rahni, Mt Piah

“…A metaheuristic algorithm, called Harmony Search is quite highly applied in optimizing parameters in many areas. …”
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Modelling of optimal placement and sizing of battery energy storage system using hybrid whale optimization algorithm and artificial immune system for total system losses reduct... by Wong Ling Ai

“…Lastly, the effectiveness of WOA and WOA-AIS in attaining optimal solutions was validated with other well-known optimisation algorithms, including particle swarm optimisation (PSO) and firefly algorithm (FA). …”

Hybrid Harmony Search Algorithm with Grey Wolf Optimizer and Modified Opposition-based Learning by Alomoush, Alaa A., Alsewari, Abdulrahman A., Alamri, Hammoudeh S., Aloufi, Khalid, Kamal Z., Zamli

“…Many variants have been developed to cope with this problem and improve algorithm performance. In this paper, a hybrid algorithm of HS with grey wolf optimizer (GWO) has been developed to solve the problem of HS parameter selection. …”
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Firefly analytical hierarchy algorithm for optimal allocation and sizing of distributed generation in radial distribution network by Bujal, Noor Ropidah

“…Finally, an AHP was integrated with FA to form Firefly Analytical Hierarchy Algorithm (FAHA) to automatically calculate the weight of each objective function based on the load flow outputs followed by the optimisation process. …”
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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer by Most. Julakha, Jahan Jui

“…his thesis implements a novel nature-inspired metaheuristic optimization algorithm, namely the modified Multi-Verse Optimizer (mMVO) algorithm, to identify the continuous-time model of Hammerstein system. …”
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Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study by Li Yu Yab, Li Yu Yab, Wahid, Noorhaniza, A Hamid, Rahayu

“…—Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study by Li Yu Yab, Li Yu Yab, Wahid, Noorhaniza, A Hamid, Rahayu

“…Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
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Application of conjugate gradient approach for nonlinear optimal control problem with model-reality differences by Leong, Wah June, Sie, Long Kek, Teo, Kok Lay, Sim, Sy Yi

“…Specifically, the modified model-based optimal control problem is resulted. …”
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Application of conjugate gradient approach for nonlinear optimal control problem with model-reality difference by Sie, Long Kek, Wah, June Leong, Sy, Yi Sim, Kok, Lay Teo

“…Specifically, the modified model-based optimal control problem is resulted. …”
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Modified multi-verse optimizer for nonlinear system identification of a double pendulum overhead crane by Julakha, Jahan Jui, Mohd Ashraf, Ahmad, Muhammad Ikram, Mohd Rashid

“…In the HMVOSCA algorithm, the new position updating mechanism of the traditional MVO method is modified based on the sine function and cosine function which is taken from the Sine Cosine Algorithm (SCA). …”
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Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems by Kek, Sie Long

“…The main idea is the integration of optimal control and parameter estimation. In this work, a simplified model-based optimal control model with adjustable parameters is constructed. …”
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Optimal power flow based on fuzzy linear programming and modified Jaya algorithms by Alzihaymee, Warid Sayel Warid

“…A set of modified and novel optimization algorithms are proposed in this thesis to deal with different single and multi-objective OPF problems. …”
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A Modified Particle Swarm Optimization for Efficient Maximum Power Point Tracking Under Partial Shading Condition by Koh J.S., Tan R.H.G., Lim W.H., Tan N.M.L.

“…Therefore, a modified PSO hybridized with adaptive local search (MPSO-HALS) is designed as a robust, real-time MPPT algorithm. …”

CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

“…In the hybrid scheme, the initial parameters of the modified BP neural network are optimized by using the global search ability of genetic algorithm, improved by cat chaotic mapping to enrich its optimization capability. …”
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A Modified Symbiotic Organism Search Algorithm with Lévy Flight for Software Module Clustering Problem by Nurul Asyikin, Zainal, Kamal Z., Zamli, Fakhrud, Din

“…To date, there are much increasing trends on adopting parameter free meta-heuristic algorithms for solving general optimization problems. …”
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A new optimisation framework based on Monte Carlo embedded hybrid variant mean–variance mapping considering uncertainties by Norhafidzah, Mohd Saad, Muhamad Zahim, Sujod, Mohd Ikhwan, Muhammad Ridzuan, Mohammad Fadhil, Abas, Mohd Shawal, Jadin, Mohd Fadzil, Abdul Kadir

“…The Monte Carlo-embedded MVMO-SH was then used to optimise PVDG in the urban RDN. Simulations were run for several scenarios in three load cases based on 288 segments: residential, commercial, and industrial urban loads. …”
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