Search Results - (( java simulation optimization algorithm ) OR ( parameter designing learning algorithm ))

Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

“…The simulation is implemented with iFogSim and java programming language. …”
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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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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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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”

Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

“…The first objective is to study the effects of varying the architecture designs and parameter values of the backpropagation neural network (BPNN) learning algorithm. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Resource management in grid computing using ant colony optimization by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

“…Resources with high pheromone value are selected to process the submitted jobs.Global pheromone update is performed after completion 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 other ant based algorithm, in terms of resource utilization.Experimental results show that EACO produced better grid resource management solution.…”
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Artificial bee colony optimization of interval type-2 fuzzy extreme learning system for chaotic data by Hassan, S., Jaafar, J., Khanesar, M.A., Khosravi, A.

“…This paper propose a novel hybrid learning algorithm for the design of IT2FLS. The proposed hybrid learning algorithm utilizes the combination of extreme learning machine (ELM) and artificial bee colony optimization (ABC) to tune the parameters of the consequent and antecedent parts of the IT2FLS, respectively. …”
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Design of efficient blue phosphorescent bottom emitting light emitting diodes by machine learning approach / Muhammad Asyraf Janai by Muhammad Asyraf , Janai

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Neural Network Multi Layer Perceptron Modeling For Surface Quality Prediction in Laser Machining by Sivarao, Subramonian

“…The input variables are the design parameters which have been selected after a critical parametric investigation of 14 process parameters available on the machine. …”
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Optimal parameters of an ELM-based interval type 2 fuzzy logic system: a hybrid learning algorithm by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

“…This paper proposes optimal parameters for an extreme learning machine-based interval type 2 fuzzy logic system to learn its best configuration. …”
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Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter by Azhar, Nur Huwaina

“…Cloudsim is used as Discrete Event Simulation tool and Java as coding language to evaluate LACE algorithm. …”
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm by Manoharan P., Ravichandran S., Kavitha S., Tengku Hashim T.J., Alsoud A.R., Sin T.C.

“…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. …”

Machine Learning Based Optimal Design of On-Road Charging Lane for Smart Cities Applications by Shanmugam Y., Narayanamoorthi R., Ramachandaramurthy V.K., Bernat P., Shrestha N., Son J., Williamson S.S.

“…The algorithm not only aids in estimating the infrastructure cost of the charging lane but also predicts optimal design parameters using trained data. …”

Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

“…Moreover, the extreme learning machine does not have any design parameters such as learning rate, covariance matrix, etc. …”
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A multi-objective genetic type-2 fuzzy extreme learning system for the identification of nonlinear dynamic systems by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

“…This paper propose a novel hybrid learning algorithm for the design of IT2FLS. The proposed algorithm benefits from the combination of extreme learning machine (ELM) and non-dominated sorting genetic algorithm (NSGAII) to tune the parameters of the consequent and antecedent parts of the IT2FLS, respectively. …”
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Design and implemtation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayyawi by Jabbar Hayyawi, Mustafa

“…Design and development an adaptive learning algorithm controller ALAC of position the actuators is presented in real time parallel manipulator based on artificial neural network ANN……”
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Analytical Study Of Machine Learning Models For Stock Trading In Malaysian Market by Hazirah Halul

“…By setting the ML algorithms and their parameter along with using Walk-Forward Analysis (WFA) method, the algorithm design of trading signal was evaluated based on two groups of evaluation indicators, namely directional and performance. …”

Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

“…These findings underscored the MSEDA suitability as a data-driven tool for controller design parameter optimization. Furthermore, the low computational burden of MSEDA rendered it a strong alternative to heuristic multi-agent algorithms, which frequently encounter high computational costs with large controller design parameters.…”
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