Search Results - (( java application testing algorithm ) OR ( parameter reducing learning algorithm ))
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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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Enhancement processing time and accuracy training via significant parameters in the batch BP algorithm
Published 2020“…The learning rate and momentum factor are the are the most significant parameter for increasing the efficiency of the BBP algorithm. …”
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Article -
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Neural Network Multi Layer Perceptron Modeling For Surface Quality Prediction in Laser Machining
Published 2009“…The researchers conducted the prediction of laser machining quality, namely surface roughness with seven significant parameters to obtain singleton output using machine learning techniques based on Quick Back Propagation Algorithm. …”
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Book Chapter -
4
Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application
Published 2020“…Performance Testing is used to test the performance of algorithm implementations in applications. …”
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Journal -
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Topological Clustering via Adaptive Resonance Theory With Information Theoretic Learning
Published 2019“…In contrast, the proposed algorithm realizes a stable computation and reduces the number of parameters compared to existing algorithms. …”
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Article -
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Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui
Published 2019“…Numerous researchers have tried different methods to enhance the algorithm to improve performance, some of these methods include Support Vector Machine (SVM), Decision Trees, Extreme Learning Machine (ELM), Kernel Extreme Learning Machine (KELM), and Deng’s Reduced Kernel Extreme Learning Machine (RKELM). …”
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Thesis -
7
Improved Manta Ray Foraging Optimizer-based SVM for Feature Selection Problems: A Medical Case Study
Published 2024“…Support Vector Machine (SVM) has become one of the traditional machine learning algorithms the most used in prediction and classification tasks. …”
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Article -
8
Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System
Published 2019“…In this paper, the particle swan optimization algorithm (PSO) was used to obtain an optimal set of initial parameters for Reduce Kernel FLN (RK-FLN), thus, creating an optimal RKFLN classifier named PSO-RKELM. …”
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Conference or Workshop Item -
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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 -
10
Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Hence, the algorithm must overcome the problem of dynamic updates in the internal parameters or counter the concept drift. …”
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Thesis -
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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm
Published 2023Conference Paper -
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Implementation of (AES) Advanced Encryption Standard algorithm in communication application
Published 2014“…The concept of ABS algorithm was firstly studied, including the definition, historical background, and a brief comparison was made between the ABS algorithm with other types of algorithm. …”
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Undergraduates Project Papers -
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An implementation of brain emotional learning based intelligent controller for AVR system
Published 2023“…In this paper, an intelligent controller based on brain emotional learning called BELBIC is applied and optimized by Particle Swarm optimization algorithm. …”
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Conference or Workshop Item -
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RECURSIVE LEARNING ALGORITHMS ON RBF NETWORKS FOR NONLINEAR SYSTEM IDENTIFICATION
Published 2010“…The thesis also try to investigate the influence of initialization of RBF weights parameters on the overall learning performance using random method and advanced unsupervised learning, such as clustering techniques, as a comparison. …”
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Thesis -
16
Hybridization of metaheuristic algorithm in training radial basis function with dynamic decay adjustment for condition monitoring / Chong Hue Yee
Published 2023“…In this research work, the motivation is to develop an autonomous learning model based on the hybridization of an adaptive ANN and a metaheuristic algorithm for optimizing ANN parameters so that the network could perform learning and adaptation in a more flexible way and handle condition classification tasks more accurately in industries, such as in power systems. …”
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Classification System for Heart Disease Using Bayesian Classifier
Published 2007“…This system was developing base on to three main part which is data processing, testing and implementation of the algorithm. In this system a Bayesian algorithm was used in order to implement the system. …”
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Active force control with iterative learning control algorithm for a vehicle suspension
Published 2013“…ILC algorithm is implemented into AFC-based control scheme to reduce its complexity and hence faster response, by replacing the use of artificial intelligence (Al) method as proposed by previous researcher. …”
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Extremal region selection for MSER detection in food recognition
Published 2021“…Therefore, this research proposes an Extremal Region Selection (ERS) algorithm to improve MSER detection by reducing the number of irrelevant extremal regions by using unsupervised learning based on the k-means algorithm. …”
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