Search Results - (( based solution learning algorithm ) OR ( java implementation real algorithm ))
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1
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 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 -
4
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 -
5
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 -
6
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 -
7
Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…Firstly, an architecture for the clustering ensemble based on incremental genetic-based algorithms is proposed consisting of two phases: (i) to produce cluster partitions as initial populations, (ii) to combine cluster partitions and to generate final clustering solution by incremental genetic based clustering ensemble learning algorithm. …”
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Thesis -
8
PMT : opposition based learning technique for enhancing metaheuristic algorithms performance
Published 2020“…Nonetheless, OBL-based solutions often consider one particular direction of the opposition. …”
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Thesis -
9
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 -
10
Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic
Published 2004“…These two adaptive routing algorithms enhance the existing Confidence-based Q (CQ) and Confidence-based Dual Reinforcement Q (CDRQ) Routing Algorithms. …”
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Thesis -
11
A modified generalized RBF model with EM-based learning algorithm for medical applications
Published 2006“…An EM-based training algorithm is also introduced, which uses fewer parameters compared to some classical supervised learning methods. …”
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Proceeding Paper -
12
A harmony search-based learning algorithm for epileptic seizure prediction
Published 2016“…The proposed harmony search-based learning algorithm is used in the task of epileptic seizure prediction. …”
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Article -
13
Wavelet neural networks based solutions for elliptic partial differential equations with improved butterfly optimization algorithm training
Published 2020“…Although the gradient information of the commonly used gradient descent training algorithm in WNNs may direct the search to optimal weight solutions that minimize the error function, the learning process is slow due to the complex calculation of the partial derivatives. …”
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Article -
14
An energy-efficient spectrum-aware reinforcement learning-based clustering algorithm for cognitive radio sensor networks
Published 2015“…In this paper, we propose a reinforcement learning-based spectrum-aware clustering algorithm that allows a member node to learn the energy and cooperative sensing costs for neighboring clusters to achieve an optimal solution. …”
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Article -
15
Opposition-based learning simulated kalman filter for Numerical optimization problems
Published 2016“…The opposition-based learning can be applied either after the solution is updated or as the prediction step in SKF. …”
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Research Book Profile -
16
PMT: opposition-based learning technique for enhancing meta-heuristic performance
Published 2019“…Like existing OBL-based approaches, the PMT generates new potential solutions based on the currently selected candidate. …”
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Article -
17
A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System
Published 2020“…Finally, surface defects are segmented from an anomaly heat map which is generated based on histogram distance functions. Results show that the proposed algorithm required a learning dataset size as small as 5 samples and was resistant to learning labelling error up to 50%.…”
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Thesis -
18
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. The image clustering is major part of data mining where study about how to binds the similar data together in a cluster and show the meaningful data. …”
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Thesis -
19
Evaluation of machine learning algorithms in predicting CO 2 internal corrosion in oil and gas pipelines
Published 2019“…This creates a demand of utilizing machine learning in predicting corrosion occurrence. This paper discusses on the evaluation of machine learning algorithms in predicting CO 2 internal corrosion rate. …”
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Article -
20
Evaluation of machine learning algorithms in predicting CO2 internal corrosion in oil and gas pipelines
Published 2019“…This creates a demand of utilizing machine learning in predicting corrosion occurrence. This paper discusses on the evaluation of machine learning algorithms in predicting CO2 internal corrosion rate. …”
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