Search Results - (( java implementation clustering algorithm ) OR ( programming based normalization algorithm ))
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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Thesis -
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Image clustering comparison of two color segmentation techniques
Published 2010“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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A Toolkit for Simulation of Desktop Grid Environment
Published 2014“…A simulator for desktop grid environment has been developed using Java as the implementation language due to its wide popularity. …”
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Final Year Project -
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A web-based implementation of k-means algorithms
Published 2022“…Firstly, k-luster could incorporate additional clustering algorithms, or even classification algorithms in the future. …”
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Final Year Project / Dissertation / Thesis -
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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
Published 2009“…The development of this architecture is based on several programming language as it involves algorithm implementation on C, parallelization using Parallel Virtual Machine (PVM) and Java for web services development. …”
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Conference or Workshop Item -
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Parallel computation of maass cusp forms using mathematica
Published 2013“…We find that the parallel programming is about 5.75 times faster than the normal programming while its efficiency is capped at 0.443.…”
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Agent-based extraction algorithm for computational problem solving
Published 2015“…Four agents have been proposed as an agent based model for CPS, which are User_Agent, PAC_Agent, IPO_Agent and Algorithm_Agent. …”
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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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Smart energy meter with adaptive communication data transfer algorithm for electrical energy monitoring
Published 2021“…The prototype of SEM is constructed based on the modern Smart Meter design and modified with additional control devices and sensors, so that it can measure, record and transfer the data using designated algorithm combining three types of communication system in one device; Wi-Fi, GSM and RF. …”
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Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
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Early detection and mitigation of DDoS attacks in software defined networks
Published 2018“…The algorithm was written in Python programming language to be implementing on a POX controller. …”
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Data mining in network traffic using fuzzy clustering
Published 2003“…The network traffic model is very important to know whether that particular network traffic is normal or abnormal. In this project, I have developed a program to capture and filter the packets based on the application. …”
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Data mining in network traffic using fuzzy clustering
Published 2003“…The network traffic model is very important to know whether that particular network traffic is normal or abnormal. In this project, I have developed a program to capture and filter the packets based on the application. …”
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Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation
Published 2023Conference paper -
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Indirect Feedback Kalman Filter Based Sensor Fusion for Reducing Navigation Errors of an Autonomous Wheelchair
Published 2018“…Fusion of the wheel encoders and gyroscope was effected using indirect feedback Kalman filter algorithm. The algorithm was programmed in a small memory microcontroller to increase the portability of the wheelchair. …”
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Final Year Project / Dissertation / Thesis -
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Neural network based model predictive control for a steel pickling process
Published 2009“…The Levenberg-Marquardt algorithm is used to train the process models. In the control (MPC) algorithm, the feedforward neural network models are used to predict the state variables over a prediction horizon within the model predictive control algorithm for searching the optimal control actions via sequential quadratic programming. …”
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