Search Results - (( data optimization means algorithm ) OR ( framework implementation based algorithm ))
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1
The conceptual framework of knowledge of large scale and incomplete graphs of skyline queries optimization using machine learning
Published 2025“…The preliminary results using the K means Clustering Algorithm showed that the conceptual framework successfully grouped similar data points, facilitating the identification of skyline points. …”
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Proceeding Paper -
2
Context enrichment framework for sentiment analysis in handling word ambiguity resolution
Published 2024“…However, ambiguous words pose a challenge for sentiment analysis algorithms as they require the identification of the correct meaning and word polarity within a specific context. …”
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Thesis -
3
Online teleoperation of writing manipulator through graphics processing unit based accelerated stereo vision
Published 2021“…To deal with these issues, adaptive sampling algorithm is applied to the data points to adhere to the manipulators speed constraints. …”
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4
State-of-charge estimation for lithium-ion batteries with optimized self-supervised transformer deep learning model
Published 2023“…The Transformer model with transferred weights outperformed models trained from scratch using supervised learning. To select the optimal hyperparameters for the Transformer model, the Tree Parzen Estimator(TPE) optimization in combination with the Hyperband pruning algorithm is employed to search for the best combination that yields the lowest Root Mean Squared Error(RMSE)and Mean Absolute Error (MAE) error metrics. …”
text::Thesis -
5
A study on component-based technology for development of complex bioinformatics software
Published 2004“…The second layer uses discriminative SVM algorithm with a state-of-the-art string kernel based on PSI-BLAST profiles that is used to leverage the unlabeled data. …”
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Monograph -
6
Analytical framework for predicting online purchasing behavior in Malaysia using a machine learning approach
Published 2025“…It is organized into three phases: preliminary investigation, implementation and analysis, and validation. The descriptive analysis examines purchasing behavior through correlation and regression analyses, while the predictive model uses decision trees (J48, Random Tree, REPTree), rule-based algorithms (JRip, OneR, PART), and clustering (K-Means) to identify patterns and predict trends. …”
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7
Optimized clustering with modified K-means algorithm
Published 2021“…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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8
Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation
Published 2023“…The main objective of this paper is to propose and implement an intelligent framework documentation approach that integrates case-based learning (CBL) with genetic algorithm (GA) and Knuth-Morris-Pratt (KMP) pattern matching algorithm with the intention of making learning a framework more effective. …”
Conference paper -
9
A near-optimal centroids initialization in K-means algorithm using bees algorithm
Published 2009“…This creates problem for novice users especially to those who have no or little knowledge on the data.Trial-error attempt might be one of the possible preference to deal with this issue.In this paper, an optimization algorithm inspired from the bees foraging activities is used to locate near-optimal centroid of a given data set.Result shows that propose approached prove it robustness and competence in finding a near optimal centroid on both synthetic and real data sets.…”
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10
Data clustering using the bees algorithm
Published 2007“…K-means clustering involves search and optimization. …”
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11
Quantum Processing Framework And Hybrid Algorithms For Routing Problems
Published 2010“…The framework is used to increase the implementation performance of quantum algorithms. …”
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Thesis -
12
Low-level hybridization scripting language with dynamic parameterization in PSO-GA / Suraya Masrom
Published 2015“…The scripting language is designed and developed based on the algorithm structure that is defined in the proposed implementation frameworks with the dynamic parameterization. …”
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13
An improvement of stochastic gradient descent approach for mean-variance portfolio optimization problem
Published 2021“…Furthermore, the applicability of SGD, Adam, AdaMax, Nadam, AMSGrad, and AdamSE algorithms in solving the mean-variance portfolio optimization problem is validated.…”
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Article -
14
Implementing case-based reasoning approach to framework documentation
Published 2023“…This paper discusses and implements the case-based reasoning (CBR) approach to documenting a framework. …”
Conference paper -
15
Optimization of the hidden layer of a multilayer perceptron with backpropagation (bp) network using hybrid k-means-greedy algorithm (kga) for time series prediction
Published 2012“…The proposed KGA model combines greedy algorithm withk-means++ clustering in this research to assist users in automating the finding of the optimal number of new-ons inside the hidden layer of the BP network. …”
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16
Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems
Published 2023“…SGD uses random or batch data sets to compute gradient in solving optimization problems. …”
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Article -
17
Design and Implementation of Intelligent Interoperability Framework for Heterogeneous Subsystems in Smart Home Environment
Published 2011“…The first algorithm, named as Framework Initialization algorithm, is developed to initialize the framework and discovering the subsystems configured in order to derive the interoperation tasks. …”
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18
Clustering chemical data set using particle swarm optimization based algorithm
Published 2008“…In this study, Particle Swarm Optimization (PSO) based clustering algorithm is exploited to optimize the results of other clustering algorithm such as K-means. …”
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19
An improved data classification framework based on fractional particle swarm optimization
Published 2019“…The proposed algorithm is tested and verified for optimization performance comparison on ten benchmark functions against six existing established algorithms in terms of Mean of Error and Standard Deviation values. …”
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20
Cluster optimization in VANET using MFO algorithm and K-Means clustering
Published 2023“…Proven to be an effective and efficient method for solving optimization problem. To design K-Means algorithm that portion nodes based on their proximities by optimize the distance between nodes within same cluster by assigning them to the closet cluster center. …”
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