Search Results - (( parallel classification learning algorithm ) OR ( program implementation model algorithm ))
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The forecasting of poverty using the ensemble learning classification methods
Published 2023“…This research was conducted to forecast poverty using classification methods. Random Forest and Extreme Gradient Boosting (XGBoost) algorithms were applied to forecast poverty since they are supervised learning algorithms that use the ensemble learning approach for classification. …”
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Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms
Published 2015“…This was achieved by mitigating convergence in the genetic algorithms by employing a hierarchical parallel architecture. …”
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…The proposed method combined the improved teaching-learning-based optimisation (ITLBO) algorithm, improved parallel JAYA (IPJAYA) algorithm, and support vector machine. …”
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Robust tweets classification using arithmetic optimization with deep learning for sustainable urban living
Published 2024“…In this view, this research develops an arithmetic optimization algorithm with deep learning based tweets classification (AOADL-TC) approach for sustainable living. …”
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Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm
Published 2011“…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
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Conference or Workshop Item -
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Combining deep and handcrafted image features for MRI brain scan classification
Published 2019“…In this paper, a deep learning feature extraction algorithm is proposed to extract the relevant features from MRI brain scans. …”
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Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System
Published 2019“…The incorporation of a single parallel hidden layer feed-forward neural network to the Fast Learning Network (FLN) architecture gave rise to the improved Extreme Learning Machine (ELM). …”
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Conference or Workshop Item -
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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Thesis -
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Development of dynamic programming algorithm for maintenance scheduling problem
Published 2020“…The dynamic programming model developed for this research reflected the flow of the maintenance activity of the company and implemented the model by Lieberman and Hillier (2010). …”
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Implementation of repetitive control algorithm in reducing vibration using MATLAB/SIMULINK / Mohamad Zuhairy Mohamed
Published 2008“…In this report, it analyzes an application of repetitive control algorithm that deal with periodic disturbance.. To investigates the possibility of using a truncated finite impulse response (FIR) model approximation to implement a well-known gradient type repetitive control algorithm. …”
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A multi-depot vehicle routing problem with stochastic road capacity and reduced two-stage stochastic integer linear programming models for rollout algorithm
Published 2021“…A matheuristic approach based on a reduced two-stage Stochastic Integer Linear Programming (SILP) model is presented. The proposed approach is suitable for obtaining a policy constructed dynamically on the go during the rollout algorithm. …”
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AUTOMATED MODEL GENERATION OF FSM AND NUSMV MODEL FROM RSA JAVA SOURCE CODE FOR MODEL CHECKING
Published 2021“…RSA is one of these encryption algorithms that have been implemented in security systems. …”
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A study on solution of matrix riccati differential equations using ant colony programming and simulink / Mohd Zahurin Mohamed Kamali
Published 2015“…It has been found that by implementing the ACP algorithm, the solution predicted is approximately close or similar to the exact solution. …”
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CSC773 - Parallel Computing / College of Computing, Informatics And Media
Published 2023“…It emphasizes the decomposition and mapping techniques in constructing parallel algorithms. The parallel programming paradigms, namely, the shared address space and message passing are applied to implement parallel programs. …”
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Teaching Resource -
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Solving Sudoku puzzles in Binary Integer Linear Programming using Branch and Bound algorithm / Ahida Waliyyah Ahmad Fuad
Published 2024“…This study explores the application of a Binary Integer Linear Programming (BILP) model combined with the Branch and Bound (B&B) algorithm to solve Sudoku puzzles. …”
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Controller And Circuitry Design And Implementation For Fire Fighting Robot For MIROC 2014 Competition
Published 2014“…This algorithm is designed using an iterative design model, whereby the program is continually tested and improved. …”
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Final Year Project -
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Implementation of Galerkin's method and modal analysis for unforced vibration response of a tractor suspension model
Published 2014“…In order to develop a stand-alone algorithm implementable in any programming environment, Galerkin’s method was applied over smaller elements of time domain. …”
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Rapid software framework for the implementation of machine learning classification models
Published 2021“…The results indicated that although the software framework is easier than the programming platform for implementing the machine learning model, the results from the software framework were highly accurate and reliable. …”
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