Search Results - (( using selection problem algorithm ) OR ( java application designing algorithm ))
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Improving Class Timetabling using Genetic Algorithm
Published 2006“…We have targeted the research on class timetabling problem. Hence, Genetic Algorithm (GA) is used as one of the most popular optimization solutions. …”
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Thesis -
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Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…Conventional material selections are mostly based on the experience of product design engineers and the materials in common use. …”
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Thesis -
3
Message based random variable length key encryption algorithm.
Published 2009“…Value of random number should be greater than 35 bits and plaintext must be at least 7 bits. A padding algorithm was used for small size messages or big random numbers. …”
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Campus safe: Safeguarding GPS-based Physical Identity and Access Management (PIAM) system with a lightweight Geo-Encryption
Published 2022“…The selected lightweight geo-encryption algorithm will be implemented in the proposed system, vi which develops by using Java language. …”
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Academic Exercise -
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RSA Encryption & Decryption using JAVA
Published 2006“…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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Final Year Project -
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Provider independent cryptographic tools
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Monograph -
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Formulating new enhanced pattern classification algorithms based on ACO-SVM
Published 2013“…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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Audio Streaming System Using Real-Time Transport Protocol Based on Java Media Framework
Published 2004“…Java Media Framework library and the RTP protocol for audio transmission were used as development tools.The developed system designed in this thesis together with experimental results proved that the system could be implemented successfully. …”
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Thesis -
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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection
Published 2020“…An improved version of Salp Swarm Algorithm (ISSA) is proposed in this study to solve feature selection problems and select the optimal subset of features in wrapper-mode. …”
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Dengue classification system using clonal selection algorithm / Karimah Mohd
Published 2012“…Some popular intelligent techniques like Genetic Algorithm, Fuzzy Logic and Artificial Neural Network are often used by reasearcher to perform classifcation problems. …”
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Thesis -
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Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier
Published 2013“…In order to enhance SVM performance, these problems must be solved simultaneously because error produced from the feature subset selection phase will affect the values of the SVM parameters and resulted in low classification accuracy.Most approaches related with solving SVM model selection problem will discretize the continuous value of SVM parameters which will influence its performance.Incremental Mixed Variable Ant Colony Optimization (IACOMV) has the ability to solve SVM model selection problem without discretising the continuous values and simultaneously solve the two problems.This paper presents an algorithm that integrates IACOMV and SVM.Ten datasets from UCI were used to evaluate the performance of the proposed algorithm.Results showed that the proposed algorithm can enhance the classification accuracy with small number of features.…”
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A Comparative Study on three Component Selection Mechanisms for Hyper-Heuristics in Expensive Optimization
Published 2018“…Numerous studies in optimization problems often lead to tailoring a specific algorithm to adapt to the problem instances, especially in expensive optimization problems. …”
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Diagnosis of eyesight using Improved Clonal Selection Algorithm (ICLONALG) / Nor Khirda Masri
Published 2017“…This study aims to implement the classification algorithm using the Improved Clonal Selection Algorithm (ICLONALG) to classify the eyesight’s problems. …”
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Thesis -
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Static and self-scalable filter range selection algorithms for peer-to-peer networks
Published 2011“…The research works were implemented by simulation in which it was used to identify the selection problem, implementation of the proposed algorithms and the measurement of the results. …”
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Thesis -
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Investigation of evolutionary multi-objective algorithms in solving view selection problem / Seyed Hamid Talebian
Published 2013“…In this research, we showed how evolutionary multi-objective algorithms can be used to solve the view selection problem and its advantage over classical optimization problems were described. …”
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Thesis -
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Design Of Robot Motion Planning Algorithm For Wall Following Robot
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Monograph -
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Broadening selection competitive constraint handling algorithm for faster convergence
Published 2020“…The proposed algorithm has been evaluated using 24 benchmark functions. …”
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