Search Results - (( _ distribution bees algorithm ) OR ( user evaluation ((based algorithm) OR (swarm algorithm)) ))

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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A particle swarm optimization and min-max­-based workflow scheduling algorithm with QoS satisfaction for service-­oriented grids by Ambursa, Faruku Umar, Latip, Rohaya, Abdullah, Azizol, K. Subramaniam, Shamala

“…The algorithm selects the best scheduling solutions based on the proposed constraint-handling strategy. …”
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PID TUNING OF DC MOTOR USING SWARM ITELLIGENCE ALGORITHM by Hasdi Aimon, Arhimny

“…In this project, Particle Swarm Optimization (PSO) as one of Swarm Intelligence Algorithm based has proposed to be integrated with PID (Proportional, Integral, Derivative) Controller in order to achieve optimal tuning method. …”
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On spectral efficiency maximization in a partial joint processing system using a multi-start particle swarm optimization algorithm by Faisal, Ali Raed, Hashim, Fazirulhisyam, Ismail, Mahamod, Noordin, Nor Kamariah

“…Therefore stochastic multi-start particle swarm optimization algorithm (MSPSOA) is proposed in this paper to achieve backhaul reduction and address the issue of lack of diversity, which is related to the basic particle swarm optimization algorithm (BPSOA). …”
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Particle Swarm Optimization for Bluetooth Scatternet Formation by Kamel , Nidal

“…Ab stra ct In this paper, we present and evaluate the performance of a new particle swarm optimization (PSO) based scatternet formation protocol for single hop Bluetooth networks. …”
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Performance evaluation of PID controller optimisation for wheel mobile robot using Bat based optimisation algorithm by ,, Dwi Pebrianti, Ann Ayop azmi, Nurnajmi Qasrina, Bayuaji, Luhur, Suarin, Nur Aisyah Syafinaz, ,, Muhammad Syafrullah

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An improved marine predators algorithm tuned data-driven multiple-node hormone regulation neuroendocrine-PID controller for multi-input–multi-output gantry crane system by Mohd Zaidi, Mohd Tumari, Mohd Ashraf, Ahmad, Mohd Helmi, Suid, Mohd Riduwan, Ghazali, M Osman, Tokhi

“…Comparative findings alongside other existing metaheuristic-based algorithms confirmed excellence of the proposed method through its superior performance against the conventional MPA, particle swarm optimization (PSO), grey wolf optimizer (GWO), moth-flame optimization (MFO), multi-verse optimizer (MVO), sine-cosine algorithm (SCA), salp-swarm algorithm (SSA), slime mould algorithm (SMA), flow direction algorithm (FDA), and the formally published adaptive safe experimentation dynamics (ASED)-based methods.…”
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Space allocation for examination scheduling using Genetic Algorithm / Alya Kauthar Azman by Azman, Alya Kauthar

“…The research adopts a Genetic Algorithm-based approach, where examination scheduling details such as date, time, course code, program code, student group, student numbers, and available spaces are encoded as chromosomes. …”
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Low-level hybridization scripting language with dynamic parameterization in PSO-GA / Suraya Masrom by Masrom, Suraya

“…In the scripting language evaluation, nine LLHs and three single PSO algorithms have been successfully created using the scripting languages. …”
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The Effect of Rainfall on the UAV Placement for 5G Spectrum in Malaysia by Shalaby A.M., Othman N.S.

“…The problem of finding the UAV 3D placement is formulated with the objective to minimize the total path loss between the UAV and all users. The problem is solved by invoking two algorithms, namely Particle Swarm Optimization (PSO) and Gradient Descent (GD) algorithms. …”

Internet utility evaluation of a multi-start particle swarm optimization beamformer in a partial joint processing cellular network by Faisal, Ali Raed, Hashim, Fazirulhisyam, Ismail, Mahamod, Noordin, Nor Kamariah

“…Unlike linear techniques such as zero-forcing (ZF), achieving an equivalent backhaul reduction and presenting a totally free ICI system based on limited feedback channel state information can be done by designing and implementing a multi-start particle swarm optimization algorithm (MSPSOA) as a beamforming (BF) mechanism. …”
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Performance Comparison of Nature-inspired Optimization Algorithms Applied to MVDR Technique for Canceling Multiple Access Interference Signals by Suhail Najm, Shahab, Ayib Rosdi, Zainun, Nurul Hazlina, Noordin, Izzeldin, I. Mohd

“…Findings: In comparison to conventional MVDR, the proposed algorithms have indicated that MVDRGSA providesfavorable agreement of synthesizing a maximum gain toward the desired real user angle while introducing deep null-forming in the undesired user directions. …”
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Temporal integration based factorization to improve prediction accuracy of collaborative filtering by Al-Qasem, Al-Hadi Ismail Ahmed

“…A recommender system provides users with personalized suggestions for items based on the user’s behaviour history. …”
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Efficient beamforming and spectral efficiency maximization in a joint transmission LTE-A system by Faisal, Ali Raed

“…Moreover, addressing the lack-of-diversity issue in Basic Particle Swarm Optimization Algorithm (BPSOA) is a primary concern of this work. …”
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Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam by Asrul, Adam

“…In the preliminary study, the algorithm is evaluated on the four different peak models of the three EEG signals using the artificial neural network (ANN) with particle swarm optimization (PSO) as learning algorithm. …”
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Sub-route reversal repair mechanism and differential evolution for urban transit network design problem by Tarajo, Buba Ahmed

“…From the literature of UTNDP, the most widely used metaheuristic is the genetic algorithm, at the expense of other population-based metaheuristics. …”
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Multi-objective algorithms for effective resource management in Edge-Fog-Cloud computing by Saif, Faten Ameen Mohammed

“…Simulations were conducted to evaluate the proposed algorithms compared to the PSO algorithm, Cloud-Fog Cooperation Scheduling algorithm, and Task offloading algorithm. …”
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Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients by Moghbel, Mehrdad

“…The proposed method is based on a hybrid method integrating random walkers algorithm with integrated priors and particle swarm optimized spatial fuzzy c-means (FCM) algorithm with level set method and AdaBoost classifier. …”
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Offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm: article / Deezex Noor Ainizaa Abdullah by Abdullah, Deezex Noor Ainizaa

“…This paper present offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm. …”
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Offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm / Deezex Noor Ainizaa Abdullah by Abdullah, Deezex Noor Ainizaa

“…This paper present offline study on loss optimization in distribution networks using Artificial Bee Colony (ABC) algorithm. …”
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