Search Results - (( java implementation modified algorithm ) OR ( using complex learning algorithm ))
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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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Thesis -
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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT
Published 2023“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. The objectives of this work are: i) to provide a comprehensive review of the cloud and scheduling process; ii) to classify the scheduling strategies and scientific workflows; iii) to implement our proposed algorithm with various scheduling algorithms (i.e., Min-Min, Round-Robin, Max-Min, and Modified Max-Min) for performance comparison, within different cloudlet sizes (i.e., small, medium, large, and heavy) in three scientific workflows (i.e., Montage, Epigenomics, and SIPHT); and iv) to investigate the performance of the implemented algorithms by using CloudSim. …”
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Effectiveness of algorithm visualisation in studying complex algorithms: a case study using TRAKLA Ravie / Chandren Muniyandi, Ali Maroosi
Published 2015“…Students then used TRAKLA2to learn five different types of algorithms. …”
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Prevention And Detection Mechanism For Security In Passive Rfid System
Published 2013“…The proposed protocol is designed with lightweight cryptographic algorithm, including XOR, Hamming distance, rotation and a modified linear congruential generator (MLCG). …”
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Automatic generation of content security policy to mitigate cross site scripting
Published 2016“…It can be extended to support generating CSP for contents that are modified by JavaScript after loading. Current approach inspects the static contents of URLs.…”
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Conference or Workshop Item -
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Bat Algorithm for Complex Event Pattern Detection in Sentiment Analysis
Published 2021“…For learning and predicting the event patterns, dynamic Bayesian network (DBN) with Hidden Markov Model (HMM) and heuristic search learning algorithms have been a popular technique used in which structure learning is trained to classify complex events pattern. …”
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Functional link neural network with modified bee-firefly learning algorithm for classification task
Published 2016“…The standard learning method for tuning weights in FLNN is Backpropagation (BP) learning algorithm. …”
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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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The Implementation of a Machine Learning-based Routing Algorithm in a Lab-Scale Testbed
Published 2024“…Thus, researchers are developing intelligent RAs, including machine learning (ML)-based algorithms to meet traffic Q oS r equirements. …”
Conference Paper -
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A comparative study of deep learning algorithms in univariate and multivariate forecasting of the Malaysian stock market
Published 2023“…This study aims to develop a univariate and multivariate stock market forecasting model using three deep learning algorithms and compare the performance of those models. …”
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SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA
Published 2012“…This thesis gives a systematic investigation of various MLP learning mainly Sliding Window (SW) learning mode which is treated as the adaptation of offline algorithms into online application Consequently this thesis reviews various offline algorithms including: batch backpropagation, nonlinear conjugate gradient, limited memory and full-memory Broyden, Fletcher, Goldfarb and Shanno algorithms and different forms of the latest proposed bimary ensemble learning. …”
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Medical Image Analysis Using Deep Learning and Distribution Pattern Matching Algorithm
Published 2023Article -
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Watermarking in safe region of frequency domain using complex-valued neural network
Published 2010“…It has been discovered by computational experiments that Complex Back-Propagation (CBP) algorithm is well suited for learning complex pattern, and it has been reported that this ability can successfully be applied in image processing with complex values. …”
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Proceeding Paper -
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Binary ant colony optimization algorithm in learning random satisfiability logic for discrete hopfield neural network
Published 2024“…It aimed to optimize the performance of G-type random high-order satisfiability logic structures embedded in Discrete Hopfield Neural Networks, thereby enhancing the efficiency of the Hopfield Neural Network learning algorithm. Through comparative analysis with other metaheuristic algorithms, our model demonstrated superior performance in terms of global convergence, time complexity, and algorithm complexity. …”
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Optimization of cost-based hybrid flowshop scheduling using teaching-learning-based optimization algorithm
Published 2024“…This paper investigates the optimization of a CHFS problem using the Teaching Learning-Based Optimization (TLBO) algorithm. …”
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Algorithm animation for cryptanalysis of caesar and hill ciphers / Sapiee Haji Jamel and Giuseppina Sherry Sayan
Published 2009“…This new trend gives an advantage to cryptanalyst since types of algorithm(s) used are no longer a secret. Cryptanalysis steps can be easily explained using algorithm animation that can be easily integrated with any e-learning platform. …”
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BAT-BP: A new BAT based back-propagation algorithm for efficient data classification
Published 2016“…Training neural networks particularly back propagation algorithm is a complex task of great importance in the field of supervised learning. …”
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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
Published 2019“…From the reviews, it is evident that autonomous system is set to handle finite number of encountered states using finite sequences of actions. In order to learn the optimized states-action policy the self-learning algorithm is developed using hybrid AI algorithm by combining unsupervised weightless neural network, which employs AUTOWiSARD and reinforcement learning algorithm, which employs Q-learning. …”
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