Search Results - (( _ implication based algorithm ) OR ( framework implementation 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“…We propose a new dimension to detect learning styles, which involves the individuals of learners' social surrounding such as friends, parents, and teachers in developing a novel agent-based framework. The multi-agent system applies ant colony optimization and fuzzy logic search algorithms as tools to detecting learning styles. …”
Conference Paper -
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Manufacturing process planning optimisation in reconfigurable multiple parts flow lines
Published 2008“…Design/methodology/approach: The genetic algorithm methodology implements a genetic algorithm that is augmented by application specific heuristics in order to guide the search for an optimal solution. …”
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Enhancing project completion date prediction using a hybrid model: rule-based algorithm and machine learning algorithm
Published 2025“…The study employs a hybrid predictive model that combines Big Data technologies, Extract Load Transfer (ELT) processes, rule-based algorithms (RBA), machine learning (ML), and Power BI visualizations. …”
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4
Application of machine learning and artificial intelligence in detecting SQL injection attacks
Published 2024“…The study uses a mixed-methods approach to evaluate how well different AI and ML algorithms identify SQL injection attacks by combining algorithmic evaluation with empirical investigation. …”
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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 -
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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 -
7
Low-level hybridization scripting language with dynamic parameterization in PSO-GA / Suraya Masrom
Published 2015“…Evaluations of four different sets of applications that used the proposed implementation frameworks with dynamic parameterization have indicated the effectiveness of each tested algorithm in comparison to the single PSO and constant parameterization. …”
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8
Why coding? Why now? From coding to computational thinking through computational mathematics problem based learning (CM-PBL)
Published 2019“…It is also highlights ways that students can evolve from technical skills in using technology to soft engineering skills by using coding knowledge.…”
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The effectiveness of problem-based serious games on learning and learning motivation in the context of 3D computer graphics / Meisam Moradi
Published 2022“…To this end, the researcher designed a quantitative study with a between subject design and aimed at implementing a treatment course using the problem-based SG. …”
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10
Implementing case-based reasoning approach to framework documentation
Published 2023“…In CBR, reasoning is based on remembering past cases. Genetic algorithm (GA) is used in implementing the CBR's "retrieve", "reuse", and "revise" steps. …”
Conference paper -
11
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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12
Implementation of perez-dumortier calibration algorithm
Published 2014“…The implementation of the filtration procedure in step-by-step is discussed to render better framework of the proposed calibration algorithm. …”
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Chapter In Book -
13
A Telemedicine Tool Framework For Lung Sounds Classification Using Ensemble Classifier Algorithms
Published 2020“…The overall classification accuracy for the Improved Random Forest algorithm has 99.04%. The telemedicine framework was implemented with the Improved Random Forest algorithm. …”
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Genetic algorithm based ensemble framework for sentiment analysis
Published 2018“…Finally, the last experiment involves creating the complete optimized multilayered ensemble framework and implementation of the framework to find the suitable combination of methods in each layer to produce satisfactory sentiment analysis accuracy. …”
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16
Edge assisted crime prediction and evaluation framework for machine learning algorithms
Published 2022“…In particular, this study proposes a crime prediction and evaluation framework for machine learning algorithms of the network edge. …”
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An intelligent framework for modelling and active vibration control of flexible structures
Published 2004“…Performance of the AVC algorithm is assessed based on parametric design techniques, using RLS and GAS, and non-parametric design techniques, using MLP-NN and ANFIS in the suppression of vibration of the flexible structures. …”
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Immune-based technique for undergraduate programmes recommendation / Muhammad Azrill Mohd Zamri
Published 2017“…Based on the framework, a prototype was implemented to evaluate the accuracy of the proposed technique. 52% is the highest accuracy obtained from the technique by using ten-fold cross validation. …”
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Real-time anomaly detection using clustering in big data technologies / Riyaz Ahamed Ariyaluran Habeeb
Published 2019“…Based on the outcome of the analysis, this research proposed a novel framework namely real-time anomaly detection based on big data technologies (RTADBDT), along with supporting implementation algorithms. …”
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Rapid software framework for the implementation of machine learning classification models
Published 2021“…The machine learning model in the two platforms were tested on breast cancer and tax avoidance datasets with Decision Tree algorithm. The results indicated that although the software framework is easier than the programming platform for implementing the machine learning model, the results from the software framework were highly accurate and reliable. …”
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