Search Results - (( java application based algorithm ) OR ( dynamic simulation optimisation algorithm ))

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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PID-based control of a single-link flexible manipulator in vertical motion with genetic optimisation by Md Zain, Badrul Aisham, Tokhi, M. Osman, Toha, Siti Fauziah

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Optimisation of fed-batch fermentation process using deep reinforcement learning by Chai, Wan Ying

“…The kinetic and dynamic behaviour of the fed-batch baker’s yeast fermentation was simulated and modelled using MATLAB, with no experimental work carried out. …”
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Optimization of multi-agent traffic network system with Q-Learning-Tune fitness function by Tan, Min Keng

“…This study aims to explore the potential of implementing multi-agent-based Genetic Algorithm (GA) with interactive metamodel to acquire regular optimisation on dynamic characteristic of traffic flow. …”
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Parametric modelling of a TRMS using dynamic spread factor particle swarm optimisation by Toha, Siti Fauziah, Abd Latiff, I., Mohamad, M., Tokhi, M Osman

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Dynamic Probability Selection for Flower Pollination Algorithm based on Metropolis-hastings Criteria by Zamli, Kamal Zuhairi, Din, Fakhrud, Nasser, Abdullah, Ramli, Nazirah, Mohamed, Noraini

“…This paper proposed flower pollination algorithm metropolis-hastings (FPA-MH) based on the adoption of Metropolis-Hastings criteria adopted from the Simulated Annealing (SA) algorithm to enable dynamic selection of the pa probability. …”
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Dynamic modelling of a single link flexible manipulator in vertical motion using swarm and genetic optimisation by Md. Zain, B. A., Tokhi, M. Osman, Toha, Siti Fauziah

“…In this research, particle swann optimisation (PSO) and genetic algorithm (GA) are used to model a single-link flexible manipulator. …”
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Gooseneck barnacle optimization algorithm: A novel nature inspired optimization theory and application by Ahmed, Marzia, Mohd Herwan, Sulaiman, Ahmad Johari, Mohamad, Rahman, Mostafijur

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Modelling and optimisation of blood glucose control for type 1 diabetes using multi-parametric programming and model-based predictive control (mp-MPC) / Associate Professor Dr Ayub... by Md. Som, Ayub

“…Three simulation works are carried out using three different algorithms so as to refine the performance of the controller. …”
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Metaheuristic algorithms applied in ANN salinity modelling by Khudhair, Zahraa S., Zubaidi, Salah L., Dulaimi, Anmar, Al-Bugharbee, Hussein, Muhsen, Yousif Raad, Putra Jaya, Ramadhansyah, Mohammed Ridha, Hussein, Raza, Syed Fawad, Ethaib, Saleem

“…The CPSOCGSA performance was evaluated by various single-based ones, including multi-verse optimiser (MVO), marine predator's optimisation algorithm (MPA), particle swarm optimiser (PSO), and the slim mould algorithm (SMA). …”
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Completion time driven hyper-heuristic approach for optimisation of scientific workflow scheduling in cloud environment / Ehab Nabiel Mohammad by Ehab Nabiel , Mohammad

“…The second stage (i.e. approach development stage) is the development of the proposed CTDHH approach, which includes two main parts, the cost optimisation model of SWFS and the dynamic hyper-heuristic algorithm. …”
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The fusion of particle swarm optimization (PSO) and interior point method (IPM) as cooperative movement control algorithm in Swarm Robotics / Dada Emmanuel Gbenga by Dada Emmanuel, Gbenga

“…Also, many of these PSO algorithms employed hybrid methods that integrate other optimisation algorithms with the standard PSO. …”
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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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Dynamic Task Offloading Algorithm for optimising IoT network quality of service in the Mobile-Fog-Cloud System by Nwogbaga, Nweso Emmanuel

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Distributed learning based energy-efficient operations in small cell networks by Mughees, Amna

“…Also, the proposed algorithms focus on the need for cooperative learning that maintains the quality of service, adapts to the network dynamics and achieves energy efficiency in dense small-cell networks. …”
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RSA Encryption & Decryption using JAVA by Ramli, Marliyana

“…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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A multi-depot dynamic vehicle routing problem with stochastic road capacity: an MDP model and dynamic policy for post-decision state rollout algorithm in reinforcement learning by Anuar, Wadi Khalid, Lee, Lai Soon, Seow, Hsin-Vonn, Pickl, Stefan

“…An Approximate Dynamic Programming (ADP) solution method is adopted where the Post-Decision State Rollout Algorithm (PDS-RA) is applied as the lookahead approach. …”
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Optimising ventilation for thermal comfort and infection control in vehicles: A review on CFD applications and techniques by Tan, Kai Ying, Wong, Sien Jie, Tan, Huiyi, Kek, Hong Yee, Mohd Hafiz Dzafan, Othman, Wong, Syie Luing, Mohamad Nur Hidayat, Mat, Fong, Yi Ka, Wong, Keng Yinn

“…This review focuses on the application of Computational Fluid Dynamics (CFD) in optimising vehicle ventilation systems. …”
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Efficient task scheduling strategies using symbiotic organisms search algorithm for cloud computing environment by Sa'ad, Suleiman

“…The SOS and its variants Discrete Symbiotic Organisms Search (DSOS) algorithm have been used to solve different optimisation problems including tasks scheduling in cloud computing environment where results obtained are promising in comparison with stateof- the-art metaheuristic algorithms. …”
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Methane plume localization with enhanced self-best reduction and Gaussian improved particle swarm optimization (GiPSO) by Liew, Jia Hun

“…To investigate this, our research will investigate the adaptation of the Gaussian gas plume in the simulation. Adapting the Gaussian gas plume model in the simulation provides the experiment with a realistic optimization problem for GiPSO to optimize in the simulation, where we can test the engagement of dynamically challenging optimization problems such as gas plume dispersions. …”
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