Search Results - (( java implementation modified algorithm ) OR ( using composition learning algorithm ))
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Direct approach for mining association rules from structured XML data
Published 2012“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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Thesis -
2
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. The objectives of this work are: i) to provide a comprehensive review of the cloud and scheduling process; ii) to classify the scheduling strategies and scientific workflows; iii) to implement our proposed algorithm with various scheduling algorithms (i.e., Min-Min, Round-Robin, Max-Min, and Modified Max-Min) for performance comparison, within different cloudlet sizes (i.e., small, medium, large, and heavy) in three scientific workflows (i.e., Montage, Epigenomics, and SIPHT); and iv) to investigate the performance of the implemented algorithms by using CloudSim. …”
Review -
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Prevention And Detection Mechanism For Security In Passive Rfid System
Published 2013“…The proposed protocol is designed with lightweight cryptographic algorithm, including XOR, Hamming distance, rotation and a modified linear congruential generator (MLCG). …”
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Automatic generation of content security policy to mitigate cross site scripting
Published 2016“…It can be extended to support generating CSP for contents that are modified by JavaScript after loading. Current approach inspects the static contents of URLs.…”
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Conference or Workshop Item -
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Improving the performance of damage repair in thin-walled structures with analytical data and machine learning algorithms
Published 2024“…On the other hand, machine learning (ML) has made it possible to employ a variety of approaches for mechanical and aerospace problems and such significant approach is the repair mechanism and hence ML algorithms used to enhance in the present work. …”
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State-of-the-art ensemble learning and unsupervised learning in fatigue crack recognition of glass fiber reinforced polyester composite (GFRP) using acoustic emission
Published 2023“…This study evaluates the damage progression on glass fiber reinforced polyester composite specimens using different approaches of machine learning. …”
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Potential of soft computing approach for evaluating the factors affecting the capacity of steel–concrete composite beam
Published 2018“…In comparison to the other widely used conventional learning algorithms, the ELM has a much faster learning ability.…”
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A comparative study of deep learning algorithms in univariate and multivariate forecasting of the Malaysian stock market
Published 2023“…This study aims to develop a univariate and multivariate stock market forecasting model using three deep learning algorithms and compare the performance of those models. …”
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Experimental studies on impact damage location in composite aerospace structures using genetic algorithms and neural networks
Published 2010“…The strain data are used for learning in the Neural Network approach. …”
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NN-Based FECG extraction from the composite abdominal ECG
Published 2008“…According to the output it can be said that the algorithm is working satisfactory on high learning rate and low momentum value. …”
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Proceeding Paper -
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Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system
Published 2011“…The PLSR architecture model, workflow and algorithms are described. The PLSR has been developed using Java Programming language. …”
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Thesis -
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Producer gas composition prediction using artificial neural network algorithm / Mohd Mahadzir Mohammud ... [et al.]
Published 2023“…It is then used to predict the output gas composition from the parameters of a gasification experiment that has been used before in UiTM’s laboratory. …”
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Data Analysis and Machine Learning Algorithms Evaluation for Bioliq AI-based Predictive Tool
Published 2019“…This final year project identified relevant parameters through literature research, analysis and expert interview, and evaluated different machine learning algorithms and identified linear regression as the most applicable and efficient with its R-square of 0.8015, qualifying it to be used for the development of a hybrid model for the AI-based tool for predictive process optimization for chemical plants.…”
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Final Year Project -
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Parametric analysis of critical buckling in composite laminate structures under mechanical and thermal loads: a finite element and machine learning approach
Published 2024“…In summary, this paper delves into the study of the stability of C-section thin-walled composite structures with holes under mechanical and thermal loading conditions using finite element analysis and machine learning studies.…”
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Modelling and optimization of microhardness of electroless Ni-P-TiO2composite coating based on machine learning approaches and RSM
Published 2021“…The microhardness of the electroless Ni-P-TiO2 coated composite was measured and predicted by various machine learning algorithms. …”
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Self learning neuro-fuzzy modeling using hybrid genetic probabilistic approach for engine air/fuel ratio prediction
Published 2017“…A fitness function is proposed to deal with multi-objective problem without weight using a new composition method. The model was compared to other learning algorithms for NFS such as Fuzzy c-means (FCM) and grid partition algorithm. …”
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Thesis -
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Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed...
Published 2022“…Whereas the best performance in terms of prediction of the syngas composition was obtained using the NLRQM algorithm with an inbuilt SQP and LM algorithms. …”
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