Search Results - (( developing phase learning algorithm ) OR ( java application optimized algorithm ))
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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
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Conference or Workshop Item -
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Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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Route Optimization System
Published 2005“…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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Final Year Project -
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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Article -
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Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
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Thesis -
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Ant colony optimization algorithm for load balancing in grid computing
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Monograph -
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A Truly Online Learning Algorithm using Hybrid Fuzzy ARTMAP and Online Extreme Learning Machine for Pattern Classification
Published 2015“…The idea of developing FAM-OELM is motivated by the ELM concept proposed by Huang et al., for being an efficient learning algorithm that provides better generalization performance at a much faster learning speed. …”
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Dam haji game using A* search algorithm / Siti Farah Najwa Mukhlis
Published 2017“…This project is about developing a Dam Haji game using A* search algorithm. …”
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Thesis -
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Lexicon-based and immune system based learning methods in Twitter sentiment analysis
Published 2016“…The aim of this article attempts to study the potential of this method in text classification for sentiment analysis.This study consists of three phases; data preparation; classification model development using three selected Immune System based algorithms i.e. …”
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Face expression recognition using artificial neural network (ANN) / Mazuraini Ghani
Published 2005“…There are two important phases that were focused in developing this project. …”
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Thesis -
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Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT
Published 2006“…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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Object detection system using haar-classifier
Published 2009“…Development of this project is categorized into two phase which are training phase and execution phase. …”
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Undergraduates Project Papers -
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An artificial immune system model as talent performance predictor / Siti ‘Aisyah Sa’dan, Hamidah Jantan and Mohd Hanapi Abdul Latif
Published 2016“…To achieve this objective, the research was divided into three phases, which consist of talent data identification and data preparation phase, algorithm development for prototype phase and testing and evaluation phase to identify the most suitable prediction model for talent prediction. …”
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Research Reports -
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…The study on related work and comparison of algorithm also has been done in this phase. In Design phase, the use case diagram, whole system flowchart and subsystem flowchart has been constructed to assist the development of this web tool. …”
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Thesis -
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Credit Card Fraud Detection Using New Preprocessing And Hybrid Machine Learning Techniques
Published 2023“…The developed preprocessing technique consists of three phases. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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