Search Results - (( simulation classification techniques algorithm ) OR ( java implementation real algorithm ))
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Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…The aim of this evolution is to reflect the unseen time overhead incurred by optimal real-time algorithm, represented by LRE-TL, which might hinder the claimed optimality of such algorithms when they are practically implemented. …”
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Conference or Workshop Item -
2
Audio Streaming System Using Real-Time Transport Protocol Based on Java Media Framework
Published 2004“…A design proposal was outlined to provide an adaptive client/server approach to stream audio contents using Real-Time Transport Protocol (RTP) involving architecture based on the Java Media Framework (JMF) Application Programmable Interfaces (API).RTP protocol is the Internet-standard protocol for the transport of real-time data, including audio and video and can be implemented by using Java Media Framework (JMF). …”
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Thesis -
3
A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules
Published 2013“…Thus, this thesis proposed two variants of hybrid ACO with simulated annealing (SA) algorithm for solving problem of classification rule induction. …”
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Thesis -
4
An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani
Published 2015“…The forms of urban growth can be simulated using satellite remote sensing data and suitable classification technique. …”
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5
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 -
6
An improved data classification framework based on fractional particle swarm optimization
Published 2019“…It can be concluded from the simulation results that the proposed MOFPSO-ERNN classification algorithm demonstrated good classification performance in terms of classification accuracy (Breast Cancer = 99.01%, EEG = 99.99%, PIMA Indian Diabetes = 99.37%, Iris = 99.6%, Thyroid = 99.88%) as compared to the existing hybrid classification techniques. …”
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Thesis -
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Network game (Literati) / Chung Mei Kuen
Published 2003“…With the powerful networking features of Java applet, it is expected that this project would produce a real game engine. …”
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Thesis -
8
Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam
Published 2017“…The study continued with other classification technique which is neural network with random weights (NNRW). …”
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Thesis -
9
Application of genetic algorithm and JFugue in an evolutionary music generator
Published 2025“…This project explores the application of Genetic Algorithms (GA) with JFugue, which is a Java-based music programming library to develop an Evolutionary Music Generator. …”
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Final Year Project / Dissertation / Thesis -
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An Adaptive Fuzzy Contrast Enhancement Algorithm with Details Preserving
Published 2014“…In the proposed AFCEDP technique, the image type classification is handled in a better way with the integration of a fuzzy element. …”
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Article -
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Route Optimization System
Published 2005“…Using that process, we have settled on Java as our development platform as we found it able to both implement DA and the GIS component (map display and manipulation). …”
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Final Year Project -
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Feature extraction and classification :a case study of classifying a simulated digital mammogram images using self-organizing maps (som)
Published 2007“…Feature extraction is important in image processing and is a preliminary step to perform pattern classification. This project aims to propose a feature extraction technique. …”
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Final Year Project Report / IMRAD -
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A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification
Published 2023“…The simulation results on the benchmark medical datasets revealed that the proposed SCSO-KNN approach has outperformed comparative algorithms with an average classification accuracy of 93.96 by selecting 14.2 features within 1.91 s. …”
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Article -
15
PV fault classification: Impact on accuracy performance using feature extraction in random-forest cross validation algorithm
Published 2024“…This paper introduces a Solar PV Smart Fault Diagnosis and Classification (SFDC) model that harnesses the Random Forest (RF) algorithm in conjunction with Cross-Validation (CV) and an optimized feature extraction (FE) set. …”
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Deep learning-based item classification for retail automation
Published 2025“…Real-time processing was achieved through the integration of object detection algorithms like YOLO and image segmentation techniques. …”
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Final Year Project / Dissertation / Thesis -
18
Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…The advantage of the cluster labelling algorithm compared to co-spectral plot and maximum-likelihood classifier was the algorithm provided a rapid production of high accuracy classification map.…”
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Thesis -
19
Prevention And Detection Mechanism For Security In Passive Rfid System
Published 2013“…The proposed protocol implemented in real RFID system outperforms other related protocols because of 13.46 % shorter read time and write time consumed. …”
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Thesis -
20
A new ant based rule extraction algorithm for web classification
Published 2011“…Using Classifier-based attribute subset selection will reduce more attributes, but sacrifice the performance of the classifier.A hybrid ant colony optimization with simulated annealing algorithm to discover rules from data is proposed.The simulated annealing technique will minimize the problem of low quality discovered rule by an ant in a colony.The best rule for a colony will then be chosen and later the best rule among the colonies will be included in the rule set.The best rule for a colony will then be chosen and later the best rule among the colonies will be included in the rule set.The rule set is arranged in decreasing order of generation.Thirteen data sets which consist of discrete and continuous data were used to evaluate the performance of the proposed algorithm in terms of accuracy, number of rules and number of terms in the rules.Experimental results obtained from the proposed algorithm are comparable to the results of the Ant-Miner algorithm in terms of rule accuracy but are better in terms of rule simplicity.…”
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