Search Results - (( developing learning mode algorithm ) OR ( java data normalization algorithm ))
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1
Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…Even a normal people using clustering to grouping their data. …”
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2
SANAsms: Secure short messaging system for secure GSM mobile communication
Published 2008“…The system is developed using Java 2 Micro Edition (J2ME) which is written in Java. …”
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3
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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4
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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5
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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6
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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7
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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8
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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9
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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10
A new hybrid fuzzy ARTMAP and radial basis function neural network with online pruning strategy
Published 2023Conference Paper -
11
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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12
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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13
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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14
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Electing the best set of features will help to improve the classifier predictions in terms of the normal and abnormal pattern. The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. …”
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15
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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16
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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17
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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18
Forecasting of fine particulate matter based on LSTM and optimization algorithm
Published 2024Subjects:Article -
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Operational structural damage identification using de-noised modal feature in machine learning / Chen Shilei
Published 2021“…By integrating ISMA, both supervised and unsupervised machine learning algorithms were investigated to develop real-time damage identification schemes. …”
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20
Appliance level stand-by burst forecast modelling using machine learning techniques
Published 2020“…This work proposes a technique to model power consumption data and presents a comparative study of five different machine learning algorithms to study their suitability to forecast an appliance's state and standby burst. …”
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