Search Results - (( java simulation optimization algorithm ) OR ( based learning cell 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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Energy management strategies, control systems, and artificial intelligence-based algorithms development for hydrogen fuel cell-powered vehicles: A review
Published 2025“…cost components amongst others are explained in the study. The multi-objective-based algorithm, reinforcement learning algorithm, and different hybridizations are enhancing HFCEVs cost-competing edge. ? …”
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Distributed learning based energy-efficient operations in small cell networks
Published 2023“…Also, the proposed algorithms focus on the need for cooperative learning that maintains the quality of service, adapts to the network dynamics and achieves energy efficiency in dense small-cell networks. …”
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7
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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8
Micro-Crack Detection Of Solar Cells Featuring Adaptive Anisotropic Diffusion Filter And Semi-Supervised Support Vector Learning
Published 2014“…In this thesis, a machine vision-based application for detecting micro-crack in an electro luminescence (el) image of solar cell is presented. …”
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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
Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
Published 2025thesis::doctoral thesis -
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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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Monograph -
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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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13
Q-learning based vertical handover decision algorithm in LTE-A two-tier macrocell-femtocell systems / Ammar Bathich
Published 2019“…The main objective of this work is to propose and implement an efficient handover decision procedure based on users’ profiles using Q-learning technique in a LTE-A macrocell-femtocell networks. …”
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14
Classification of acute leukemia using image processing and machine learning techniques / Hayan Tareq Abdul Wahhab
Published 2015“…In total, 601 features were extracted from each blast cell, and its nucleus: 31of these were shape-based features, while 534 were texture-based features and 36 were color-based features. …”
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Immune Multiagent System for Network Intrusion Detection using Non-linear Classification Algorithm
Published 2010“…A new non classification algorithm was developed based on the danger theory model of human immune system (HIS).The abstract model of system algorithm is inspired from HIS cell mechanism mainly, the Dendritic cell behavior and T-cell mechanisms. …”
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Citation Index Journal -
17
Prediction of device performance in SnO2 based inverted organic solar cells using machine learning framework
Published 2024“…In this project, the machine learning (ML) framework with different algorithm models and kernel functions was employed to predict the device performance of solution-processed SnO2-based organic solar cells. …”
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Classification of Diabetes Mellitus (DM) using Machine Learning Algorithms
Published 2021“…Apart from that, ensemble methods such as bagging, adaptive boosting using AdaBoostM1, hybrid classifier using combinations of Random Forest with various base classifiers and ensemble algorithm which is the Random Forest has also been studied. …”
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Final Year Project -
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Breast cancer disease classification using fuzzy-ID3 algorithm with FUZZYDBD method: automatic fuzzy database definition
Published 2021“…FID3 algorithm combined the fuzzy system and decision tree techniques with ID3 algorithm as the decision tree learning. …”
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An integrated priority-based cell attenuation model for dynamic cell sizing
Published 2012“…A new, robust integrated priority-based cell attenuation model for dynamic cell sizing is proposed and simulated using real mobile traffic data.The proposed model is an integration of two main components; the modified virtual community – parallel genetic algorithm (VC-PGA) cell priority selection module and the evolving fuzzy neural network (EFuNN) mobile traffic prediction module.The VC-PGA module controls the number of cell attenuations by ordering the priority for the attenuation of all cells based on the level of mobile level of mobile traffic within each cell.The EFuNN module predicts the traffic volume of a particular cell by extracting and inserting meaningful rules through incremental, supervised real-time learning.The EFuNN module is placed in each cell and the output, the predicted mobile traffic volume of the particular cell, is sent to local and virtual community servers in the VC-PGA module.The VC-PGA module then assigns priorities for the size attenuation of all cells within the network, based on the predicted mobile traffic levels from the EFuNN module at each cell.The performance of the proposed module was evaluated on five adjacent cells in Selangor, Malaysia. …”
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