Search Results - (( java implementation using algorithm ) OR ( using complex colony algorithm ))
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1
Global gbest guided-artificial bee colony algorithm for numerical function optimization
Published 2018“…Numerous computational algorithms are used to obtain a high performance in solving mathematics, engineering and statistical complexities. …”
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2
RSA Encryption & Decryption using JAVA
Published 2006“…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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Final Year Project -
3
Comparison between ant colony and genetic algorithm using traveling salesman problem
Published 2013“…The Travelling Salesman Problem (TSP) is a complex problem in combinatorial optimization. The aim of this study is compare the effect of using two distributed algorithm which are ant colony as a Swarm intelligence algorithm and genetic algorithm. …”
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4
Provider independent cryptographic tools
Published 2003“…The library is implemented by using Java cryptographic service provider framework that conforms to Java Cryptographic Architecture (JCA) and Java Cryptographic Extension (JCE). …”
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Monograph -
5
Direct approach for mining association rules from structured XML data
Published 2012“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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6
Application of Bee Colony Optimization (BCO) in NP-Hard Problems
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Final Year Project -
7
Solving robot path planning problem using Ant Colony Optimisation (ACO) approach / Nordin Abu Bakar and Rosnawati Abdul Kudus
Published 2009“…Learning is a complex cognitive process; thus, the algorithms that can simulate learning are also complex. …”
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8
Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm
Published 2008“…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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Thesis -
9
An adaptive ant colony optimization algorithm for rule-based classification
Published 2020“…Ant-Miner is a variant of ant colony optimisation and a prominent intelligent algorithm widely use in rules-based classification. …”
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Thesis -
10
Neural Network Training Using Hybrid Particle-move Artificial Bee Colony Algorithm for Pattern Classification
Published 2017“…Artificial Bees Colony (ABC) optimization algorithm is one of the competitive algorithms in the SI algorithms group. …”
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11
Incremental continuous ant colony optimization for tuning support vector machine’s parameters
Published 2013“…The process of classifying a pattern with high classification accuracy counts mainly on tuning Support Vector Machine parameters which are the generalization error parameter and the kernel function parameter.Tuning these parameters is a complex process and Ant Colony Optimization can be used to overcome the difficulty. …”
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12
Bee colony optimisation of the travelling salesman problem in light rail systems
Published 2019“…Many optimisation algorithms have been tested but failed to facilitate passengers getting to multiple stations by way of a complex rail transit network. …”
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13
BAT-BP: A new BAT based back-propagation algorithm for efficient data classification
Published 2016“…The performance of the proposed Bat-BP algorithm is then compared with Artificial Bee Colony using BPNN (ABC-BP), Artificial Bee Colony using Levenberg-Marquardt (ABC-LM) and BPNN algorithm. …”
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14
Neural network training using hybrid particle-move artificial bee colony algorithm for pattern classification
Published 2017“…By optimizing the training of the neural networks using optimal weight set, better results can be obtained by the neural networks.Traditional neural networks algorithms such as Back Propagation (BP) were used for ANNT, but they have some drawbacks such as computational complexity and getting trapped in the local minima.Therefore, evolutionary algorithms like the Swarm Intelligence (SI) algorithms have been employed in ANNT to overcome such issues.Artificial Bees Colony (ABC) optimization algorithm is one of the competitive algorithms in the SI algorithms group. …”
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15
Binary ant colony optimization algorithm in learning random satisfiability logic for discrete hopfield neural network
Published 2024“…This study introduced a novel ant colony optimization algorithm that implements the population selection strategy of the Estimation of Distribution Algorithm and a new pheromone updating formula. …”
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16
Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…We hyave used the CPU profiler of Oracle JavaTM VisualVM to monitor the execution of LRE-TL as well as USG algorithms. …”
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17
Automatic Number Plate Recognition on android platform: With some Java code excerpts
Published 2016“…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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18
A smart guidance indoor parking system based on Dijkstra's algorithm and ant colony algorithm
Published 2020“…The hardware part explains the components used in the system and the software part explains the algorithms which have been used in the system. …”
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19
Simulation and Visualization of TSP Using Ant Colony Optimization
Published 2023“…This study aims to simulate and visualize the TSP by developing a software simulation model. This model can be used to explain how to solve the traveling salesman problem by providing step-by-step instructions performed by users using ant colony optimization. …”
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20
Optimizing support vector machine parameters using continuous ant colony optimization
Published 2012“…Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous parameters, there is a need to discretize the continuous value into a discrete value.This discretization process results in loss of some information and, hence, affects the classification accuracy and seek time.This study proposes an algorithm to optimize Support Vector Machine parameters using continuous Ant Colony Optimization without the need to discretize continuous values for Support Vector Machine parameters.Seven datasets from UCI were used to evaluate the performance of the proposed hybrid algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques.Experimental results of the proposed algorithm also show promising performance in terms of computational speed.…”
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