Search Results - (( developing learning mode algorithm ) OR ( java application learning algorithm ))
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Mobile application for real time baby sign language recognition using YOLOv8 / Siti Aishah Idris and Ahmad Firdaus Ahmad Fadzil
Published 2024“…The model will be designed and developed using a deep learning algorithm, which is YOLOv8, the latest version of YOLO. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…This model relies mainly on dimensionality reduction and machine learning algorithms. The principal component analysis (PCA) and the linear discriminant analysis (LDA) techniques perform the dimensionality reduction in individual and hybrid modes to process and improve the data. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…This model relies mainly on dimensionality reduction and machine learning algorithms. The principal component analysis (PCA) and the linear discriminant analysis (LDA) techniques perform the dimensionality reduction in individual and hybrid modes to process and improve the data. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…This model relies mainly on dimensionality reduction and machine learning algorithms. The principal component analysis (PCA) and the linear discriminant analysis (LDA) techniques perform the dimensionality reduction in individual and hybrid modes to process and improve the data. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2022“…This model relies mainly on dimensionality reduction and machine learning algorithms. The principal component analysis (PCA) and the linear discriminant analysis (LDA) techniques perform the dimensionality reduction in individual and hybrid modes to process and improve the data. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction
Published 2023“…This model relies mainly on dimensionality reduction and machine learning algorithms. The principal component analysis (PCA) and the linear discriminant analysis (LDA) techniques perform the dimensionality reduction in individual and hybrid modes to process and improve the data. …”
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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection
Published 2020“…The second improvement includes the development and use of new Local Search Algorithm with SSA to improve its exploitation. …”
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Comparative study on job scheduling using priority rule and machine learning
Published 2021“…We’ve achieved better for SJF and a decent machine learning algorithm outcome as well.…”
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An Educational Tool Aimed at Learning Metaheuristics
Published 2020“…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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A new hybrid fuzzy ARTMAP and radial basis function neural network with online pruning strategy
Published 2023Conference Paper -
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New Learning Models for Generating Classification Rules Based on Rough Set Approach
Published 2000“…So, the application of the theory as part of the learning models was proposed in this thesis. Two different models for learning in data sets were proposed based on two different reduction algorithms. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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An intelligent framework for modelling and active vibration control of flexible structures
Published 2004“…The work is further extended to developing and integrating the idea of active control of flexible structures into an interactive learning environment. …”
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Classification of imbalanced travel mode choice to work data using adjustable svm model
Published 2021“…This study deals with imbalanced mode choice data by developing an algorithm (SVMAK) based on a support vector machine model and the theory of adjusting kernel scaling. …”
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Fostering motivation in TVET students: the role of learner-paced segments and computational thinking in digital video learning
Published 2024“…Content delivered in the learner-paced mode allows students to progress through segments at their own pace, while the system-paced mode follows a fixed sequence. …”
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Hybrid OCSSA-VMD and optimized deep learning networks for runoff forecasting
Published 2025“…To improve accuracy and address the non-linearity and non-stationarity in monthly runoff forecasting, this paper proposes a method that integrates intelligent optimization techniques with Deep Learning (DL) network. The Osprey-Cauchy-Sparrow Search Algorithm (OCSSA) is employed to fine-tune the parameters of Variational Mode Decomposition (VMD), which is utilized to break down the original runoff data into multiple Intrinsic Mode Functions (IMFs). …”
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Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan
Published 2020“…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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