Search Results - (( simulation optimization system algorithm ) OR ( using solution machine algorithm ))

Damping power system oscillation using elitist differential search algorithm in multi machine power system by Niamul Islam N., Hannan M.A., Mohamed A., Hussain S.

“…In this paper, damping power system oscillations is presented using the Elitist differential search algorithm (Elitist-DSA) in a multi-machine system. …”

An Experiment of Ant Algorithms : Case Study of Kota Kinabalu Central Town by Nor Rafidah, Mohamad

“…The objectives of this study are to explore and evaluate the Ant System (AS) algorithm and Ant Colony System (ACS) algorithm in finding shortest paths. …”
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Antibody Remainder Method Based Artificial Immune System for Mathematical Function Optimization by Yap, David F. W., Koh, S. P., Tiong, S. K.

“…Artificial immune system (AIS) is one of the natureinspired algorithm for solving optimization problem. …”
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Optimal design of power system stabilizer for multimachine power system using farmland fertility algorithm by Sabo, Aliyu, Abdul Wahab, Noor Izzri, Othman, Mohammad Lutfi, Mohd Jaffar, Mai Zurwatul Ahlam, Beiranvand, Hamzeh

“…Optimal design of interconnected multimachine power system with power system stabilizers (PSSs) enduring critical conditions is a challenging assignment due to several nonlinear dynamic device and components associated to the system. …”
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An enhanced discrete symbiotic organism search algorithm for optimal task scheduling in the cloud by Sa’ad, Suleiman, Muhammed, Abdullah, Abdullahi, Mohammed, Abdullah, Azizol, Ayob, Fahrul Hakim

“…Typically, a certain number of tasks are scheduled to use diverse resources (virtual machines) to minimise the makespan and achieve the optimum utilisation of the system by reducing the response time within the cloud environment. …”
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Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources by Kumar, A., Ridha, S., Narahari, M., Ilyas, S.U.

“…However, machine and deep learning methods have higher accuracy but rely heavily on the quality and amount of training data, and the solution may become inconclusive if data is sparse. …”
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Inter-cell and intra-cell facility layout models under different demand environments in cellular manufacturing systems by Ariafar, Shahram

“…Comparison of the results with an adapted algorithm from the literature, in terms of the quality of solutions (material handling cost) shows that the proposed algorithm produces better solutions with a maximum of 0.08% error compared to 0.12% error in the benchmarked algorithm. …”
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Inverse kinematic solution in handling 3R manipulator via real-time genetic algorithm by Albert F.Y.C., Koh S.P., Tiong S.K., Chen C.P., Yap F.W.

“…The system would adopt the advantage of Genetic Algorithm to optimize its performance in terms of motion control and accuracy. …”

HSO: A hybrid swarm optimization algorithm for reducing energy consumption in the cloudlets by Hasan, Raed Abdulkareem, Mostafa, A. Mohammed, Salih, Zeyad Hussein, M. A., Ameedeen, Tapus, Nicolae, Mohammed, Muamer N.

“…With the proposed model, the performance of the Hybrid swarm algorithm was significantly increased, as observed by optimizing the number of tasks through simulation, (power consumption was reduced by 42%). …”
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Effect of adopting different dispatching rules on the mean flow time in a two machine batch-shop problem by Abdelraheem Elhaj, Hazir Farouk

“…Ali Allahverdi, 1998 obtained the optimal solutions for minimizing mean flow time in a two-machine flow shop with Sequence-independent set up times by using three heuristic algorithms. …”
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A new machine learning-based hybrid intrusion detection system and intelligent routing algorithm for MPLS network by Mohammad Azmi Ridwan, Dr.

“…Machine Learning (ML) is seen as a promising application that offers autonomous learning and provides optimized solutions to complex problems. …”

Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

“…Meta-heuristic algorithms have widely used in HPAs due to their global optimization ability. …”
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Privacy optimization and intrusion detection in modbus/tcp network-based scada in water distribution systems by Franco, Daniel Jose Da Graca Peceguina

“…Another problematic aspect is related to the intrusion detection solutions that are based on machine learning cluster algorithms to learn systems’ specifications and extract general state-based rules for attacks identification. …”
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Parallel CFD Simulations of Multiphase Systems: Jet into a Cylindrical Bath and Rotary Drum on a Rectangular Bath. by Hasan, Nurul

“…For commercial CFD packages, in many cases the solution algorithms are black boxes, even though parallel computing helps in many cases to overcome the limitations, as shown here. …”
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Cooperative multi agents for intelligent intrusion detection and prevention systems / Shahaboddin Shamshirband by Shamshirband, Shahaboddin

“…Owing to the distributed nature of modern attacks (e.g. denial-of-service), it is extremely challenging to detect such malicious behaviour using traditional intrusion detection systems. In this thesis, we investigate the possibility of adapting an intelligent system to an Intrusion Detection System (IDS) by proposing a cooperative and intelligent detection and prevention system using machine learning approaches, and aim to facilitate the detection and prevention process in a distributed environment. …”
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A Kalman Filter Approach to PCB Drill Path Optimization Problem by Abdul Aziz, Nor Hidayati, Zuwairie, Ibrahim, Ab. Aziz, Nor Azlina, Saifudin, Razali, Abas, Khairul Hamimah, Mohamad, Mohd Saberi

“…This paper presents a Kalman Filter approach in solving printed circuit board (PCB) routing problem by using the Simulated Kalman Filter (SKF) algorithm. …”
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Development of optimized damage prediction method for health monitoring of ultra high performance fiber-reinforced concrete communication tower by Gatea, Sarah Jabbar

“…Therefore, this study aims to develop a new health monitoring system for communication towers based on AdaBoost, Bagging, and RUSBoost algorithms as hybrid algorithm, which can predict the damage by using noisy, random, unstable, and skewed frequency data with high accuracy. …”
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EDITORIAL: INTEGRATION OF HYDROLOGICAL MODELS AND MACHINE LEARNING TECHNIQUES FOR WATER RESOURCES MANAGEMENT by Ren Jie, Chin, Sai Hin, Lai

“…Hydrology and water resources management ensure the sustainable use, conservation, and allocation of water in natural and engineered systems. …”
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks by Ukasyah bin Mahamod

Capacity Planning For Mixed-Load Tester Under Demand And Testing Time Uncertainty by Asih, Hayati Mukti

“…Currently,the company’s issue is low tester utilization of about 71%,well below the target of 96%.The objective of this research is to improve tester utilization while achieving the production target under uncertain demand and testing time and also to determine the break-even point on the testers required.A novel approach of integrating a mathematical model,robust optimization model,genetic algorithm,simulation model and cost–volume –profit analysis was developed.Firstly,a mathematical model of mixed-load tester was formulated.Next,a set of discrete scenarios was proposed to address uncertain demand and testing time.A robust optimization and genetic algorithm model was developed to optimize the number of testers under the described uncertainties.Next,these scenarios were simulated using the Pro Model simulation software to validate the proposed models and to evaluate throughput and tester utilization.Finally,the cost–volume–profit analysis was performed for scenarios that require additional testers at various levels of uncertainties.The results showed that the proposed solution improved tester utilization by 25% compared to the current system.This research has contribution by developing novel hybrid methodology and able to provide useful insights to assist company’s managers to plan and allocate resources according to variations in customers’ demands and testing time.…”
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