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

“…This research proposes an enhancement of the ant colony optimization algorithm that caters for dynamic scheduling and load balancing in the grid computing system. …”
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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

“…This research proposes an Enhanced Ant Colony Optimization (EACO) algorithm that caters dynamic scheduling and load balancing in the grid computing system. …”
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Resource management in grid computing using ant colony optimization by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

“…Managing resources in grid computing system is complicated due to the distributed and heterogeneous nature of the resources.Stagnation in grid computing system may occur when all jobs require or are assigned to the same resources which lead to the resources having high workload or the time taken to process a job is high.This research proposes an Enhanced Ant Colony Optimization (EACO) algorithm that caters dynamic scheduling and load balancing in the grid computing system.The algorithm consists of three new mechanisms that organize the work of an ant colony i.e. initial pheromone value mechanism, resource selection mechanism and pheromone update mechanism.The resource allocation problem is modeled as a graph that can be used by the ant to deliver its pheromone.This graph consists of four types of vertices which are job, requirement, resource and capacity that are used in constructing the grid resource management element.The proposed EACO algorithm takes into consideration the capacity of resources and the characteristics of jobs in determining the best resource to process a job.EACO selects the resources based on the pheromone value on each resource which is recorded in a matrix form.The initial pheromone value of each resource for each job is calculated based on the estimated transmission time and execution time of a given job. …”
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Improved bacterial foraging optimization algorithm with machine learning-driven short-term electricity load forecasting: a case study in peninsular Malaysia by Zaini, Farah Anishah, Sulaima, Mohamad Fani, Wan Abdul Razak, Intan Azmira, Othman, Mohammad Lutfi, Mokhlis, Hazlie

“…Thus, these parameters of LSSVM need to be chosen appropriately using intelligent optimization algorithms. This study proposes a new hybrid model based on the LSSVM optimized by the improved bacterial foraging optimization algorithm (IBFOA) for forecasting the short-term daily electricity load in Peninsular Malaysia. …”
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Improved bacterial foraging optimization algorithm with machine learning driven short term electricity load forecasting: A case study in Peninsular Malaysia by Sulaima, Mohamad Fani, Zaini, Farah Anishah, Wan Abdul Razak, Intan Azmira, Othman, Mohammad Lutfi, Mokhlis, Hazlie

“…Thus, these parameters of LSSVM need to be chosen appropriately using intelligent optimization algorithms. This study proposes a new hybrid model based on the LSSVM optimized by the improved bacterial foraging optimization algorithm (IBFOA) for forecasting the short‑term daily electricity load in Peninsular Malaysia. …”
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Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River by Katipo?lu O.M., Kartal V., Pande C.B.

“…4.457, and KGE = 0.737) compared to other models. Furthermore, the utilization of FA and ABC optimization techniques facilitated the optimization of the ANN model parameters. …”

Comparison Between the Bees Algorithm and Genetic Algorithm Model in Manpower Allocation on Cell Loading Problem by AlMahasneh, Hossam Sayel

“…Results show that there are different factors of GA that it is not exist in the Bees Algorithm. Both of the proposed algorithm finds optimal or near optimal solutions for the MACL especially in large problems.…”
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Modeling and optimization of cold extrusion process by using response surface methodology and metaheuristic approaches by Ong, Pauline, Vui, Desmond Daniel Sheng Chin, Choon, Sin Ho, Chuan, Huat Ng

“…The established extrusion force model was then taken as the fitness function. Subsequently, the analytical approach and metaheuristic algorithms, specifically the particle swarm optimization, cuckoo search algorithm (CSA) and flower pollination algorithm, were applied to optimize the extrusion process parameters. …”
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Optimal design of EV aggregator for real-time peak load shaving and valley filling by Solanke T.U., Khatua P.K., Ramachandaramurthy V.K., Yong J.Y., Kanesan J., Tariq M., Kasinathan P.

“…Battery management systems; Dynamic loads; Energy management systems; Genetic algorithms; Landforms; Optimal systems; Power electronics; Deterministic optimization; Fluctuating loads; Grid-connected; Matlab Simulink models; Optimal design; Optimization algorithms; Real-time application; State of charge; Electric power transmission networks…”

Load-Balancing Models for Scheduling Divisible Load on Large Scale Data Grids by Abduh Kaid, Monir Abdullah

“…The closed form solutions are derived for the optimal load allocation. Although the IDLT model is proposed for single source, it has been applied in the case of multiple sources. …”
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Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

“…The solution set (i.e. optimized weight/bias matrix of ANN) provided by the optimized and improved genetic algorithm and modified BP based model is extracted and used in the design and development of a prototype device of the proposed model. …”
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Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH by Norhafidzah, Mohd Saad

“…The load flow patterns will significantly have affected when uncertain PV generation – load models are considered into the power flow algorithm. …”
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One day ahead daily peak hour load forecasting by using invasive weed optimization learning algorithm based Artificial Neural Network by Rahim, Muhammad Fitri

“…In this project, an Artificial Neural Network (ANN) trained by the Invasive Weed Optimization (IWO) learning algorithm is proposed for short term load forecasting (STLF) model. …”
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Optimum battery depth of discharge for off-grid solar PV/battery system by Hlal M.I., Ramachandaramurthy V.K., Sarhan A., Pouryekta A., Subramaniam U.

“…Electric load loss; Genetic algorithms; Multiobjective optimization; Optimization; Secondary batteries; Battery systems; Cost of energies; Depth of discharges; Multi-objective optimization models; Non dominated sorting genetic algorithm (NSGA II); NSGA-II; Off-grid system; Solar PV systems; Loss of load probability…”

A novel peak load shaving algorithm for isolated microgrid using hybrid PV-BESS system by Rana, M.M., Romlie, M.F., Abdullah, M.F., Uddin, M., Sarkar, M.R.

“…The proposed algorithm has been tested with the designed IMG model. …”
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Optimization of neural network architecture using genetic algorithm for load forecasting by Islam, B.U., Baharudin, Z., Raza, M.Q., Nallagownden, P.

“…In this paper, a computational intelligent technique genetic algorithm (GA) is implemented for the optimization of artificial neural network (ANN) architecture. …”
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Provider independent cryptographic tools by Ibrahim, Subariah, Salleh, Mazleena, Abdul Aziz, Shah Rizan

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AUTOMATED MODEL GENERATION OF FSM AND NUSMV MODEL FROM RSA JAVA SOURCE CODE FOR MODEL CHECKING by SALLEH AL-HUMAIKANI, MOHAMMED ABDULQAWI

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Particle swarm optimization technique for optimal economic load dispatch / Muhammad Hilmi Nordin by Nordin, Muhammad Hilmi

“…PSO is an algorithm that is modeled on swarm intelligence that finds a solution to an optimization problem in a search space, or model, and predicts social behavior in the presence of objectives. …”
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