Search Results - (( java simulation optimization algorithm ) OR ( based prediction models 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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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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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. …”
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Opposition-Based Learning Binary Bat Algorithm as Feature Selection Approach in Taguchi's T-Method
Published 2024Subjects:Conference Paper -
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Cellular Automata-based Algorithm for Liquid Diffusion Phenomenon Modeling using imaging technique
Published 2013“…This thesis proposes a dynamical behavior prediction algorithm using Cellular Automata (CA) to model the LDP. …”
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7
An enhanced feed-forward neural networks and a rule-based algorithm for predictive modelling of students' academic performance
Published 2016“…Also, for a more efficient exploration of students‟ data collected for this research, a Rule-Based Algorithm is proposed and implemented. The predictive models emanated from the two approaches were evaluated in order to validate their effectiveness. …”
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8
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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9
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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10
Extreme learning machine for user location prediction in mobile environment
Published 2011“…Findings – WiFi’s SS contributes more in accuracy to the prediction of user location than WiFi’s SQ. Moreover, the new framework based on ELM has been compared with the k-Nearest Neighbor and the results have shown that the proposed model based on the extreme learning algorithm outperforms the k-Nearest Neighbor approach. …”
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11
Power plant energy predictions based on thermal factors using ridge and support vector regressor algorithms
Published 2021“…Initially, the Ridge algorithm-based modeling is performed in detail, and then SVR-based LR, named as SVR (LR), SVR-based radial basis function—SVR (RBF), and SVR-based polynomial regression—SVR (Poly.) algorithms, are applied. …”
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12
Optimization of Prediction Error in CO2 Laser Cutting process by Taguchi Artificial Neural Network Hybrid with Genetic algorithm
Published 2013“…In some cases, the prediction errors of Taguchi ANN model was larger than 10 even with Levenberg Marquardt training algorithm. …”
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13
An artificial immune system model as talent performance predictor / Siti ‘Aisyah Sa’dan, Hamidah Jantan and Mohd Hanapi Abdul Latif
Published 2016“…The objective of this study is to propose a prediction model based on bio-inspired algorithm for talent knowledge discovery through some experiments. …”
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Research Reports -
14
Extreme learning machine for user location prediction in mobile environment
Published 2011“…Findings – WiFi's SS contributes more in accuracy to the prediction of user location than WiFi's SQ. Moreover, the new framework based on ELM has been compared with the k-Nearest Neighbor and the results have shown that the proposed model based on the extreme learning algorithm outperforms the k-Nearest Neighbor approach. …”
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15
Neural network based model predictive control for a steel pickling process
Published 2009“…The Levenberg-Marquardt algorithm is used to train the process models. In the control (MPC) algorithm, the feedforward neural network models are used to predict the state variables over a prediction horizon within the model predictive control algorithm for searching the optimal control actions via sequential quadratic programming. …”
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16
A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…The focus of the paper is to propose a hybrid approach for the selection of the most influential input variables for the training and testing of neural network based hybrid models. The combined influence of the genetic algorithm and correlation analysis are used in this technique. …”
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Adaptive-model based self-tuning generalized predictive control of a biodiesel reactor / Ho Yong Kuen
Published 2011“…Traditionally, the Recursive Least Squares (RLS) algorithm was used in the Generalized Predictive Control (GPC) framework solely for model adaptation purposes. …”
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18
Efficient Entropy-Based Decoding Algorithms For Higher-Order Hidden Markov Model
Published 2019“…Higher-order Hidden Markov model (HHMM) has a higher prediction accuracy than the first-order Hidden Markov model (HMM). …”
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19
An improved scatter search algorithm for parameter estimation in large-scale kinetic models of biochemical systems
Published 2019“…The improved algorithm is based on hybridization of quasi opposition-based learning in enhanced scatter search (QOBLESS) method. …”
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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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