Search Results - (( process activation function 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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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. …”
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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
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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7
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 -
8
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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9
Performance of Multi-Layer Perceptron Neural Networks with an Exponential Decay Activation Function in Airwaves Estimation
Published 2013“…The benchmark for the performance evaluation is by comparing the exponential decay activation function with log-sigmoid and tan-sigmoid activation functions through back propagation algorithm. …”
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Citation Index Journal -
10
Modeling the prediction of hydrogen production by co-gasification of plastic and rubber wastes using machine learning algorithms
Published 2023“…Chemical activation; Gasification; Learning algorithms; Machine learning; Multilayer neural networks; Neurons; Plastics industry; Predictive analytics; Rubber; Rubber industry; Activation functions; MLP neural networks; Model architecture; Multi layer perceptron; Neural network algorithm; Optimized performance; Process operation; Radial Basis Function(RBF); Hydrogen production…”
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Data-Driven Approach to Modeling Biohydrogen Production from Biodiesel Production Waste: Effect of Activation Functions on Model Configurations
Published 2022“…The RBFNN model with softmax as the hidden layer activation function and identity as the outer layer activation function has the least predictive performance, as indicated by an R2 of 0.403 and a RMSE of 301.55. …”
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12
Effort Estimation Model for Function Point Measurement
Published 2007“…The process starts with the planning phase activities and refined throughout the development. …”
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13
Discrimination of pathological voices using systole activated neural network
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Working Paper -
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Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…The uniqueness of this approach lies in embedding an integrated scheduling function into a partially integrated process planning function in order to exploit the strategic potentials of flexibility and reconfigurability in manufacturing systems. …”
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15
A Hybrid Active Contour and Artificial Bee Colony Algorithm for Segmenting Mixed-Meal Food Images (S/O: 13239)
Published 2020“…In addition, a modified active contour method is presented in this paper using the artificial bee colony (ABC) algorithm to optimize the weights of the external energy function in the original active contour (AC) method. …”
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Monograph -
16
Modelling of biogas production process with evolutionary artificial neural network and genetic algorithm
Published 2017“…The EANN used a modified activation function to meet the optimisation requirement. …”
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17
Real time nonlinear filtered-x lms algorithm for active noise control
Published 2012“…The NLFXLMS algorithm is a stochastic gradient algorithm that incorporates the derivative of a nonlinear plant model which is represented by the scaled error function (SEF) in the controller design. …”
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18
Performance comparison of THF-NLFXLMS and VFXLMS algorithms for Hammerstein NANC
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Conference or Workshop Item -
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Jogging activity recognition using k-NN algorithm
Published 2022“…The objective of this project are 1) to investigate human activity recognition (HAR) for jogging activity and k-Nearest Neighbors (k-NN) algorithm for jogging classifier, 2) to apply HAR AND k-NN for jogging recognition and classification and, 3) to test the functionality of the k-NN algorithm of jogging recognition and classification. …”
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Academic Exercise -
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The effect of adaptive parameters on the performance of back propagation
Published 2012“…The activation functions are adjusted by the adaptation of gain parameters together with adaptive momentum and learning rate value during the learning process. …”
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Thesis
