Search Results - (( simulation optimization capacity algorithm ) OR ( java application learning algorithm ))

The performance of block codes in digital communication system: article / Nor Afzan Azmi by Azmi, Nor Afzan

“…This proposed algorithm was developed and simulated to evaluate the performance of handover procedure in order to minimize an unnecessary handover, enhance the system capacity and improve the user's QoS level in the femtocell networks. …”
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Handover procedure between macrocell and femtocell in Long Term Evolution (LTE) network: article / Nurul Afzan Zakaria by Zakaria, Nurul Afzan

“…This proposed algorithm was developed and simulated to evaluate the performance of handover procedure in order to minimize an unnecessary handover, enhance the system capacity and improve the user's QoS level in the femtocell networks. …”
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Handover procedure between macrocell and femtocell in long term evolution (LTE) network / Nurul Afzan Zakaria by Zakaria, Nurul Afzan

“…This proposed algorithm was developed and simulated to evaluate the performance of handover procedure in order to minimize an unnecessary handover, enhance the system capacity and improve the user's QoS level in the femtocell networks. …”
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Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

“…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation by Khan, Abdullah

“…This thesis proposes and simulates the three novel optimization algorithms to handle DG allocation, different single-objective, and multi-objective OPF problems. …”
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Optimizing dam and reservoir operations using machine learning by Mohammad Abdullah Adib Almubaidin

Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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Enhancing reservoir operations with charged system search (CSS) algorithm: Accounting for sediment accumulation and multiple scenarios by Almubaidin M.A.A., Ahmed A.N., Malek M.A., Mahmoud M.A., Sherif M., El-Shafie A.

“…Optimization methods vary depending on objectives, reservoir type, and algorithms used. …”

Performance analysis of resource allocation downlink for MIMO-OFDMA system using Greedy algorithm. / Azrinawati Samaon by Samaon, Azrinawati

“…Simulation results show that the proposed algorithm can improve the capacity of the network compared with the waterfdling when using signal-to-noise ratio (SNR) with value 6dB. …”
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Performance analysis of resource allocation downlink for MIMO-OFDMA system using greedy algorithm / Azrinawati Samaon by Samaon, Azrinawati

“…Simulation results show that the proposed algorithm can improve the capacity of the network compared with the water-filling when using signal-to-noise ratio (SNR) with value 6dB. …”
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Multi-Objective Optimal Energy Management of Nanogrid Using Improved Pelican Optimization Algorithm by Jamal S., Pasupuleti J., Rahmat N.A., Tan N.M.L.

“…The simulation reveals that the suggested IPOA algorithm exhibited the most economical performance and the lowest CO2 emissions. …”

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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Optimal sizing and location of distributed generation for loss minimization using firefly algorithm by Bin Kamarudin M.N., Hashim T.J.T., Musa A.

“…This paper presents the simulation of an application of firefly algorithm (FA) for optimally locating the most suitable placement and capacity of distributed generation (DG) in IEEE 33-bus radial distribution network. …”

Resource allocation technique for powerline network using a modified shuffled frog-leaping algorithm by Altrad, Abdallah Mahmoud Mousa

“…The resources allocated are constantly optimized and the capacity obtained is constantly higher as compared to Root-finding, Linear, and Hybrid evolutionary algorithms. …”
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Simulation of a smart antenna system by Rosli, Nur Alina Zureen

“…When deployed optimally, Smart Antennas can increase the capacity of a network by more than 100% or reduce the required number of base stations to less than 50%. …”
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A novel design of a snake robot with an optimized battery distribution for extended operational time by Badran, Marwan Atef, Khan, Md. Raisuddin, Toha, Siti Fauziah

“…Furthermore, we propose a multi-objective optimization algorithm for optimal battery distribution that minimizes energy consumption while maximizing power supply capacity. …”
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Enhancing reservoir operations with charged system search (CSS) algorithm: Accounting for sediment accumulation and multiple scenarios by Almubaidin, Mohammad Abdullah Abid, Ali, Najah Ahmed *, Marlinda, Abdul Malek, Moamin, A. Mahmoud, Sherif, Mohsen, El-Shafie, Ahmed

“…Optimization methods vary depending on objectives, reservoir type, and algorithms used. …”
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Long-term optimal planning for renewable based distributed generators and battery energy storage systems toward enhancement of green energy penetration by ALAhmad A.K., Verayiah R., Shareef H.

“…The backward reduction method (BRM) is then applied to streamline the number of generated scenarios, reducing computational efforts. To solve the optimization planning model, a hybrid optimization algorithm is proposed, combining the non-dominating sorting genetic algorithm (NSGAII) and multi-objective particle swarm optimization (MOPSO). …”

Ant colony optimization algorithm for dynamic scheduling of jobs in computational grid by Ku-Mahamud, Ku Ruhana, Ramli, Razamin, Yusof, Yuhanis, Mohamed Din, Aniza, Mahmuddin, Massudi

“…Job scheduling problem is classified as an NP-hard problem.Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms.Among different optimization algorithms for job scheduling, ant colony system algorithm is a popular meta-heuristic algorithm which has the ability to solve different types of NP-hard problems.However, ant colony system algorithm has a deficiency in its heuristic function which affects the algorithm behavior in terms of finding the shortest connection between edges.This research focuses on a new heuristic function where information about recent ants’ discoveries has been considered.The new heuristic function has been integrated into the classical ant colony system algorithm.Furthermore, the enhanced algorithm has been implemented to solve the travelling salesman problem as well as in scheduling of jobs in computational grid.A simulator with dynamic environment feature to mimic real life application has been development to validate the proposed enhanced ant colony system algorithm. …”
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