Search Results - (( developing learner optimization algorithm ) OR ( java _ visualization algorithm ))
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1
A performance analysis of association rule mining algorithms
Published 2016“…The results of the CPU profiler of Java VisualVM showed that Binary-Based algorithm performs better than Eclat algorithm in-terms of both execution times and memory usage. …”
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2
A conceptual multi-agent framework using ant colony optimization and fuzzy algorithms for learning style detection
Published 2023“…The multi-agent system applies ant colony optimization and fuzzy logic search algorithms as tools to detecting learning styles. …”
Conference Paper -
3
Meta-Heuristic Algorithms for Learning Path Recommender at MOOC
Published 2021“…We have developed Metaheuristic algorithms includes the Genetic Algorithm (GA) and Ant Colony Optimization Algorithm (ACO), to solve the proposed model. …”
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4
Performance evaluation of real-time multiprocessor scheduling algorithms
Published 2016“…We hyave used the CPU profiler of Oracle JavaTM VisualVM to monitor the execution of LRE-TL as well as USG algorithms. …”
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5
An ensemble deep learning classifier stacked with fuzzy ARTMAP for malware detection
Published 2023“…The stacked ensemble method uses several heterogeneous deep neural networks as the base learners. During the training and optimization process, these base learners adopt a hybrid BP and Particle Swarm Optimization algorithm to combine both local and global optimization capabilities for identifying optimal features and improving the classification performance. …”
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6
Visdom: Smart guide robot for visually impaired people
Published 2025“…An Android mobile application, developed using Java and the java.net.Socket library, provides an intuitive and accessible user interface for seamless interaction with the robot. …”
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Final Year Project / Dissertation / Thesis -
7
New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning
Published 2023“…The SMOTE method is used to balance the data, the feature selection LightGBM and stacking ensemble learning (LGBFS-StackingXGBoost) to optimize machine learning accuracy. A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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8
New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning
Published 2023“…The SMOTE method is used to balance the data, the feature selection LightGBM and stacking ensemble learning (LGBFS-StackingXGBoost) to optimize machine learning accuracy. A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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9
New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning
Published 2023“…The SMOTE method is used to balance the data, the feature selection LightGBM and stacking ensemble learning (LGBFS-StackingXGBoost) to optimize machine learning accuracy. A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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10
New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning*
Published 2023“…The SMOTE method is used to balance the data, the feature selection LightGBM and stacking ensemble learning (LGBFS-StackingXGBoost) to optimize machine learning accuracy. A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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11
New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning*
Published 2023“…The SMOTE method is used to balance the data, the feature selection LightGBM and stacking ensemble learning (LGBFS-StackingXGBoost) to optimize machine learning accuracy. A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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12
New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning*
Published 2023“…The SMOTE method is used to balance the data, the feature selection LightGBM and stacking ensemble learning (LGBFS-StackingXGBoost) to optimize machine learning accuracy. A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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13
New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning*
Published 2023“…The SMOTE method is used to balance the data, the feature selection LightGBM and stacking ensemble learning (LGBFS-StackingXGBoost) to optimize machine learning accuracy. A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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14
New model combination meta-learner to improve accuracy prediction P2P lending with stacking ensemble learning
Published 2023“…The SMOTE method is used to balance the data, the feature selection LightGBM and stacking ensemble learning (LGBFS-StackingXGBoost) to optimize machine learning accuracy. A new model of stacking ensemble learning by combining three base-learner algorithms namely KNN, SVM and Random Forest into the XGBoost meta-learner algorithm. …”
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15
Web-based RIG performance reporting system using interactive visualization techniques / Amir Hambaly Nasaruddin
Published 2019“…D3.js is used as a technology to visualize the result in interactive form or dynamic visualization which is a JavaScript library and Python is a language to program the system. …”
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Thesis -
16
Enhanced bibliographic data retrieval and visualization using query optimization and spectral centrality measure
Published 2019“…This study proposing an enhance bibliographic data retrieval and visualization using hybrid clustering method consists of K-harmonic mean (KHM) and Spectral Algorithm and eigenvector centrality measure. …”
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17
Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
Published 2009“…The development of this architecture is based on several programming language as it involves algorithm implementation on C, parallelization using Parallel Virtual Machine (PVM) and Java for web services development. …”
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18
Design Of Robot Motion Planning Algorithm For Wall Following Robot
Published 2006“…Algorithms are developed for a simulated mobile robot that uses an array of range finders for navigation. …”
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Monograph -
19
Dynamic force-directed graph with weighted nodes for scholar network visualization
Published 2022“…The approach is realized by creating a web-based interface using D3 JavaScript algorithm that allows the visualization to focus on how data are connected to each other more accurately than the conventional lines of data seen in traditional data representation. …”
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20
Graphical user interface for bounded-addition fuzzy splicing systems and their variants / Mathuri Selvarajoo ... [et al.]
Published 2023“…In this research, a graphical user interface is developed to generate all the splicing languages generated by bounded-addition fuzzy splicing systems and their variants. An algorithm is developed using JAVA and Visual Studio Code software in order to replace the time-consuming manual computation of the languages generated by bounded-addition fuzzy DNA splicing systems and their variants.…”
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