Search Results - (( basic optimization based algorithm ) OR ( loading optimisation _ algorithm ))

Gravitational energy harvesting system based on multistage braking technique for multilevel elevated car parking building by Al Kubaisi, Yasir Mahmood

“…The results showed that, 34.09% energy and 6.58% delay time have been improved using the proposed system and proposed optimised mass at 3.5 kg. Based on the MSBS experiment, the parameters used are being applied in developing an optimization model; both results are compared and obtained an 8.2% error. …”
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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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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). …”

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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Optimisation of PID controller for load frequency control in two-area power system using evolutionary particle swarm optimisation by Illias, Hazlee Azil, Zahari, A.F.M., Mokhlis, Hazlie

“…Hence, by implementing an optimisation method, the performance of the LFC can be optimised through optimising the PID controller parameters.…”
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Optimal power flow based on fuzzy linear programming and modified Jaya algorithms by Alzihaymee, Warid Sayel Warid

“…In the proposed novel QOJaya algorithm, an intelligence strategy, namely, quasi-oppositional based learning (QOBL) is incorporated into the basic Jaya algorithm to enhance its convergence speed and solution optimality. …”
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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems by Din, Fakhrud, Khalid, Shah, Fayaz, Muhammad, Gwak, Jeonghwan, Kamal Z., Zamli, Mashwani, Wali Khan

“…The performance of the fuzzy adaptive teaching learning-based optimization is evaluated against other metaheuristic algorithms including basic teaching learning-based optimization on 23 unconstrained global test functions. …”
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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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Design of a hybrid ANN multi-objective whale algorithm for suspended sediment load prediction by Ehteram M., Ahmed A.N., Latif S.D., Huang Y.F., Alizamir M., Kisi O., Mert C., El-Shafie A.

Optimisation of automatic generation control performance in two-area power system with pid controllers using mepso / Lu Li by Lu , Li

“…From the simulation results, it was found that with the same number of PID controllers, the performance of AGC optimised by using MEPSO-TVAC algorithm is better in terms of overshoot and fitness value than using EPSO and PSO algorithms. …”
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A hybrid algorithm based on artificial bee colony and artificial rabbits optimization for solving economic dispatch problem by Lee, Wei Wen, Hashim, Mohd Ruzaini

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Embedded Meta evolutionary-firefly algorithm-ANN for multi dg planning in distribution system / Siti Rafidah Abdul Rahim by Abdul Rahim, Siti Rafidah

“…Thus, a reliable optimisation technique is crucial to address this issue. …”
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Optimal coordinated voltage control in active distribution networks using backtracking search algorithm by Hashim T.J.T., Mohamed A.

Voting algorithms for large scale fault-tolerant systems by Karimi, Abbas

“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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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 MVMO-SH had the lowest APL index compared to genetic algorithm and particle swarm optimisation when the probabilistic power flow with PVDG was optimised under uncertainty. …”
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An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP by Bibi Aamirah Shafaa Emambocus, Muhammed Basheer Jasser, Muzaffar Hamzah, Aida Mustapha, Angela Amphawan

“…Several variants of PSO have been proposed for solving discrete optimization problems like TSP. Among them, the basic algorithm is the Swap Sequence based PSO (SSPSO), however, it does not perform well in providing high quality solutions. …”
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Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System by Ali, Mohammed Hasan, Mohamed Fadli, Zolkipli

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An algorithm for the selection of planting lining technique towards optimizing land area: an algorithm for planting lining technique selection by Md Badarudin, Ismadi, Md Sultan, Abu Bakar, Sulaiman, Md. Nasir, Mamat, Ali, Tengku Muda Mohamed, Mahmud

“…This algorithm solution generated the dataset based coordinates areas to analyze the techniques. …”
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Optimal placement and sizing of battery energy storage system considering the duck curve phenomenon by Wong L.A., Ramachandaramurthy V.K., Walker S.L., Ekanayake J.B.

Immunized-evolutionary algorithm based technique for loss control in transmission system with multi-load increment by Shaaya S.A., Musirin I., Sulaiman S.I., Mansor M.H.

“…This paper presents immunized-evolutionary algorithm based technique for loss control in transmission system with multi -load increment. …”