Search Results - (( pattern classifications using algorithm ) OR ( loading optimisation based algorithm ))
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Optimising cloud computing performance with an enhanced dynamic load balancing algorithm for superior task allocation
Published 2024“…This paper presents an Enhanced Dynamic Load Balancing (EDLB) algorithm designed to optimise task scheduling and resource allocation in cloud environments. …”
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Performance evaluation of load balancing algorithm for virtual machine in data centre in cloud computing
Published 2018“…Cloud computing has become biggest buzz in the computer era these days.It runs entire operating systems on the cloud and doeverything on cloud to store data off-site.Cloud computing is primarily based on grid computing, but it’s a new computational model.Cloud computing has emerged into a new opportunity to further enhance way of hosting data centre and provide services.The primary substance of cloud computing is to deal the computing power,storage,different sort of stages and services which assigned tothe external users on demand through the internet.Task scheduling in cloud computing is vital role optimisation and effective dynamic resource allocation for load balancing.In cloud, the issue focused is under utilisation and over utilisation of the resources to distribute workload of multiple network links for example,when cloud clients try to access and send request tothe same cloud server while the other cloud server remain idle at that moment, leads to the unbalanced of workload on cloud data centers.Thus, load balancing is to assign tasks to the individual cloud data centers of the shared system so that no single cloud data centers is overloaded or under loaded.A Hybrid approach of Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm is combined in order to get effective response time.The proposed hybrid algorithm has been experimented by using CloudSim simulator.The result shows that the hybrid load balancing algorithm improves the cloud system performance by reducing the response time compared to the Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm.…”
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…In pattern recognition system, achieving high accuracy in pattern classification is crucial. …”
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Thesis -
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Modelling of optimal placement and sizing of battery energy storage system using hybrid whale optimization algorithm and artificial immune system for total system losses reduct...
Published 2023“…Lastly, the effectiveness of WOA and WOA-AIS in attaining optimal solutions was validated with other well-known optimisation algorithms, including particle swarm optimisation (PSO) and firefly algorithm (FA). …”
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Firefly analytical hierarchy algorithm for optimal allocation and sizing of distributed generation in radial distribution network
Published 2022“…Finally, an AHP was integrated with FA to form Firefly Analytical Hierarchy Algorithm (FAHA) to automatically calculate the weight of each objective function based on the load flow outputs followed by the optimisation process. …”
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Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier
Published 2018“…There are a lot of feature extraction methods and classification methods for iris classification. Classic local binary pattern (LBP) is one of the most useful feature extraction methods. …”
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Monograph -
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Pattern Recognition for Human Diseases Classification in Spectral Analysis
Published 2022“…On the other hand, classification methods are techniques or algorithms used to group samples into a predetermined category. …”
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The Potential of a Classification-based Algorithm to Calculate Calories in Real-Time Via Pattern Recognition
Published 2016“…While the algorithm helped to classify different types of wavelengths produced from the sensor, a classification-based algorithm via Pattern Recognition Method will be used to classify and match the food components. …”
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Conference or Workshop Item -
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Songket pattern classification using backpropagation neural network / Nik Aidil Syawalni Nik Mazlan
Published 2024“…Despite to the several system limitations, the project on classifies Songket pattern using BPNN is consider successful. The outcomes of this investigation show the originality and efficacy of employing BPNNs for Songket pattern classification, resulting in good accuracy rates in the classification of Songket. …”
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Hybrid ACO and SVM algorithm for pattern classification
Published 2013“…Support Vector Machine (SVM) is a pattern classification approach originated from statistical approaches. …”
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MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM
Published 2011“…The experimental result shows that the proposed hybrid k-mean plus MFP algorithm can generate more useful pattern from large stock data.…”
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Citation Index Journal -
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Experimental study of urban growth pattern classification using moving window algorithm
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A new optimisation framework based on Monte Carlo embedded hybrid variant mean–variance mapping considering uncertainties
Published 2024“…The Monte Carlo-embedded MVMO-SH was then used to optimise PVDG in the urban RDN. Simulations were run for several scenarios in three load cases based on 288 segments: residential, commercial, and industrial urban loads. …”
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A modified fuzzy min-max neural network with a genetic-algorithm-based rule extractor for pattern classification
Published 2010“…In this paper, a two-stage pattern classification and rule extraction system is proposed. …”
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A hybrid-based modified adaptive fuzzy inference engine for pattern classification
Published 2011“…The performance of the proposed MAFIE is compared with other existing applications of pattern classification schemes using Fisher's Iris data set and shown to be very competitive.…”
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Genetic algorithm fuzzy logic for medical knowledge-based pattern classification
Published 2018“…The proposed algorithm was applied and tested in four critical illness datasets in medical knowledge pattern classification. …”
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Neural Network Training Using Hybrid Particle-move Artificial Bee Colony Algorithm for Pattern Classification
Published 2017“…In this work, we aimed to highlight the performance of the Hybrid Particle-move Artificial Bee Colony (HPABC) algorithm by applying it on the ANNT application. The performance of the HPABC algorithm was investigated on four benchmark pattern-classification datasets and the results were compared with other algorithms. …”
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Individual And Ensemble Pattern Classification Models Using Enhanced Fuzzy Min-Max Neural Networks
Published 2014“…Pattern classification is one of the major components for the design and development of a computerized pattern recognition system. …”
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Thesis -
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Pattern Classification of Human Epithelial Images
Published 2016“…This project shows an important role to diagnosis autoimmune disorder which is by a comparative analysis on the most appropriate clustering technique for the segmentation and also to develop algorithm for positivity classification. In this project, there are four stages will be used to analyze pattern classification in human epithelial (HEp-2) images. …”
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Final Year Project
