Search Results - (( data processing ((tasks algorithm) OR (based algorithm)) ) OR ( java application _ algorithm ))
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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Article -
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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 -
3
Workflow optimization in distributed computing environment for stream-based data processing model / Saima Gulzar Ahmad
Published 2017“…To avoid such overheads many techniques have been used, however in this thesis stream-based data processing model is used in which data is processed in the form of continuous instances of data items. …”
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4
Dynamic Task Offloading Algorithm for optimising IoT network quality of service in the Mobile-Fog-Cloud System
Published 2023“…Finally, a Dynamic Task Offloading Algorithm (DTOA) based on rank accuracy estimation model to efficiently schedule tasks and resources in the Mobile-Fog-Cloud system is proposed. …”
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5
Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. …”
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Enhanced utility accrual scheduling algorithms for adaptive real time system.
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Multi-objective algorithms for effective resource management in Edge-Fog-Cloud computing
Published 2023“…Edge-Fog-Cloud computing is a platform that facilitates the processing of loT tasks that generate a massive amount of data from edge computing. …”
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9
An improved dynamic load balancing for virtualmachines in cloud computing using hybrid bat and bee colony algorithms
Published 2021“…The proposed HBAC algorithm was tested and compared with other stateof-the-art algorithms on 200 to 2000 even tasks by using CloudSim on standard workload format (SWF) data sets file size (200kb and 400kb). …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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11
DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH
Published 2005“…The project's objective is identifying the available data mining algorithms in data classification and applying new data mining algorithm to perform classification tasks. …”
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Final Year Project -
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An online density-based clustering algorithm for data stream based on local optimal radius and cluster pruning
Published 2019“…Experimental results are compared with other alternative online/offline hybrid density-based clustering algorithms. The average processing time for data point in the data stream is about 2 milliseconds which is much lower than the aligned clustering algorithms in literature. …”
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13
Framework for stream clustering of trajectories based on temporal micro clustering technique
Published 2018“…In some scenarios, spatio-temporal data are received in a streamed manner. Clustering of the stream data is a challenging task due to single pass over the data, the unbounded size of data stream, and the limited processing time and memory space. …”
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14
Smart student timetable planner
Published 2025“…Course data is managed in CSV format, parsed into JSON for fast processing, while sessionStorage and localStorage handle user data within active sessions. …”
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Final Year Project / Dissertation / Thesis -
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DTWFF-pitch feature and faster neural network convergence for speech recognition
Published 2007“…The processed features are pitch and Linear Predictive Coefficients (LPC) for input and reference templates, based on Dynamic Time Warping (DTW) algorithm. …”
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Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection
Published 2015“…Subsequently, the integration of embedded correlation-based filtering algorithm has further increased the classification accuracy of training process and testing process by 4.93% and 14.73% respectively. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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Automated time series forecasting
Published 2011“…Moving Average, Decomposition, Exponential Smoothing, Time Series Regressions and ARIMA) were used.The algorithm was developed in JAVA using up to date forecasting process such as data partition, several error measures and rolling process.Successfully, the results of the algorithm tally with the results of SPSS and Excel.This automatic forecasting will not just benefit forecaster but also end users who do not have in depth knowledge about forecasting techniques.…”
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Monograph -
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An ensemble data summarization approach based on feature transformation to learning relational data
Published 2015“…A ensemble clustering is designed, used and evaluated to generate the final classification framework that will take all input generated from the GA based clustering with Feature Selection and Feature Construction algorithms and perform the classification task for the relational datasets. …”
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Dimensionality reduction in data summarization approach to learning relational data
Published 2013“…Based on the experimental results, the DARA algorithm is proven to be very effective in learning relational data. …”
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