Search Results - (( processes equations learning algorithm ) OR ( java simulation optimization algorithm ))
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1
Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…The simulation is implemented with iFogSim and java programming language. …”
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2
Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…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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Thesis -
3
Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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Monograph -
4
OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT
Published 2023“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
Review -
5
Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…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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6
Feedforward neural network for solving particular fractional differential equations
Published 2024“…Artificial neural networks (ANNs), a machine learning tool, have exhibited promising capabilities in solving differential equations. …”
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7
Wavelet neural networks based solutions for elliptic partial differential equations with improved butterfly optimization algorithm training
Published 2020“…Although the gradient information of the commonly used gradient descent training algorithm in WNNs may direct the search to optimal weight solutions that minimize the error function, the learning process is slow due to the complex calculation of the partial derivatives. …”
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8
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…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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9
Resource management in grid computing using ant colony optimization
Published 2011“…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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Monograph -
10
Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter
Published 2019“…Cloudsim is used as Discrete Event Simulation tool and Java as coding language to evaluate LACE algorithm. …”
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11
Evaluating the performances of Dice, Jaccard, Overlap, and Cosine coefficients in automated marking of algebraic equations / Hasnah Yusof, Wan Rolini Wan Yusoff and Masita Jamal
Published 2006“…Computers enable the automation of many tasks and made great contributions in many areas where learning process takes place. Assessment plays an important role in the learning process of many courses and mathematics is no exception. …”
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Research Reports -
12
Weather prediction in Kota Kinabalu using linear regressions with multiple variables
Published 2021“…Numerical weather prediction is the process of using existing numerical data on weather conditions to forecast the weather using machine learning algorithms. …”
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Proceedings -
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Applications of machine learning to friction stir welding process optimization
Published 2020“…Machine learning (ML) is a branch of artificial intelligent which involve the study and development of algorithm for computer to learn from data. …”
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14
An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction
Published 2014“…Backpropagation (BP) learning algorithm is the well-known learning technique that trained ANN. …”
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Thesis -
15
Modeling and validation of base pressure for aerodynamic vehicles based on machine learning models
Published 2023“…The data for training and testing the algorithms was derived using the regression equation developed using the Box-Behnken Design (BBD). …”
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Predicting energy consumption pattern based on top trending videos YouTube 2021 using machine learning techniques
Published 2022“…The process of putting a machine learning pipeline into action will be explored and analysed. …”
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Final Year Project / Dissertation / Thesis -
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Application of boundary-fitted convolutional neural network to simulate non-Newtonian fluid flow behavior in eccentric annulus
Published 2022“…The simulated results and parametric analysis conclude that the proposed algorithm can decipher the non-Newtonian fluid mechanics from the governing equations. …”
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SG-PBFS : Shortest Gap-Priority Based Fair Scheduling technique for job scheduling in cloud environment
Published 2024“…To conduct this experiment, we employed the CloudSim simulator, which is implemented using the Java programming language.…”
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Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources
Published 2021“…The governing equations derived for non-Newtonian fluid models result in nonlinear differential equations. …”
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20
Predicting Petroleum Reservoir Properties from Downhole Sensor Data using an Ensemble Model of Neural Networks
Published 2013“…One of such is the difficulty in determining the most suitable learning algorithm for optimal model performance. To save the cost, effort and time involved in the use of trial-and-error and evolutionary methods, this paper presents an ensemble model of ANN that combines the diverse performances of seven "weak" learning algorithms to evolve an ensemble solution in the prediction of porosity and permeability of petroleum reservoirs. …”
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