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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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Article -
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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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
Electricity load profile determination by using fuzzy C-means and probability neural network / Norhasnelly Anuar
Published 2015“…Next PNN is used to classify load profile according to its group. Results obtained show that FCM algorithm can be used as the clustering method to obtained TLPs and PNN is proven to be reliable to allocate the measured load profiles accurately according to their type of consumers.…”
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5
Intuitive content management system via manipulation and duplication with if-else rules classification
Published 2018“…As a result, ICMS can transform dynamic websites into static websites with faster load speed using manipulation method mixed with data mining classification prediction and Boyer-Moore Horspool algorithm which can be classified, edited, adjustable and searched more precisely. …”
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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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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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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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Assessment of cognitive load using multimedia learning and resting states with deep learning perspective
Published 2019“…The brain waves were extracted using discrete wavelet transform (DWT) for each segment and fed these segments to proposed model for classification and assessment of cognitive load. The results shows that alpha brain wave produced consistent behavior using for all cognition tasks based on pre-trained CNN models for classification and cognitive load assessment. …”
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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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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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12
Daily maximum load forecasting of consecutive national holidays using OSELM-based multi-agents system with weighted average strategy
Published 2023Subjects:Article -
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Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition
Published 2018“…Electromyography (EMG) signal is a biomedical signal which measures physical activity of human muscle.It has been acknowledged to be widely used in rehabilitation or recovery application system assisting physiotherapist to monitor a patient’s physical strength,function,motion and overall well-being by addressing the underlying physical issues.In application system associated with rehabilitation,a signal processing and classification techniques are implemented to classify EMG signal obtained.For real time application in the rehabilitation, the classification is crucial issue.The success of the signal classification depends on the selection of the features that represent a raw EMG signal in the signal processing.Therefore,a robust and resilient denoising method and spectral estimation technique have been acknowledged as necessary to distinguish and detect the EMG pattern.The present study was undertaken to determine the characteristic of EMG features using denoising method and spectral estimation technique for assessing the EMG pattern based on a supervised classification algorithm.In the study,the combination of time-frequency domain (TFD) and time domain (TD) were identified as the preferred denoising method and spectral estimation techniques.In the first part of study, the recorded EMG signal filtered the contaminated noise by using wavelet transform (WT) approach which implemented discrete wavelet transform (DWT) method of the wavelet-denoising signal. …”
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Development of electromyography-controlled 3D printed robot hand and supervised machine learning for signal classification
Published 2019“…However, the current research state is unsatisfactory, especially in terms of structural design, robot system and the robot control method. In this research, an EMG controlled 3D printed robot hand prototype with improved features and advance hand posture classification method based on EMG signal pattern were proposed. …”
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15
Fault classification in smart distribution network using support vector machine
Published 2023“…In this paper, a machine-learning algorithm known as Support Vector Machine (SVM) for fault type classification in distribution system has been developed. …”
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Driver behaviour classification: a research using OBD-II data and machine learning
Published 2024“…However, implementing the ensemble method AB has improved the accuracy to 99.48%.…”
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Teleworking monitoring system using NILM and K-NN algorithms: a strategy for sustainable smart cities
Published 2024“…Together with an event classification method known as K-Nearest Neighbor (k-NN) algorithm, the teleworking event and duration can be identified.The results were presented using classification metrics that consist of confusion matrix andaccuracy score. …”
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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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Distribution network fault section estimation using analytical database approach
Published 2004“…The databases contain voltage sag magnitude and phase shin information for all nodes on the distribution network under different fault types and load conditions. When a fault occurs, the method only needs to measure the fault generated voltage sag waveform at the network primary substation. …”
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