Search Results - (( developing learner optimization algorithm ) OR ( java evaluation using algorithm ))
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1
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 -
2
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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3
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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4
A performance analysis of association rule mining algorithms
Published 2016“…In this paper, we evaluate the performance of association rule mining algorithms in-terms of execution times and memory usage using the CPU profiler of Java VisualVM. …”
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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
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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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
Automatic Number Plate Recognition on android platform: With some Java code excerpts
Published 2016“…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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Book -
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
A Model for Evaluation of Cryptography Algorithm on UUM Portal
Published 2004“…The simulation model was developed using Active Server Page, JavaScript and SQL 7.0 as database. …”
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16
Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter
Published 2019“…Cloudsim is used as Discrete Event Simulation tool and Java as coding language to evaluate LACE algorithm. …”
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17
Security Analysis Between Static And Dynamic S-boxes In Block Ciphers
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18
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. …”
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Thesis -
19
Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. …”
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Undergraduates Project Papers -
20
Comparison of performances of Jaya Algorithm and Cuckoo Search algorithm using benchmark functions
Published 2022“…To help engineers select the best metaheuristic algorithms for their problems, there is a need to evaluate the performance of different metaheuristic algorithms against each other using common case studies. …”
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