Search Results - (( using function based algorithm ) OR ( framework implementation learning algorithm ))
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1
An intelligent framework for modelling and active vibration control of flexible structures
Published 2004“…The second controller design strategy is based on a cost function optimization using GAS. …”
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2
Constrained–Optimization-based Bayesian posterior probability extreme learning machine for pattern classification
Published 2023“…Using random computational hidden neurons, ELM shows faster learning speed over the traditional learning algorithms. …”
Conference Paper -
3
Reassembly and clustering bifragmented intertwined jpeg images using genetic algorithm and extreme learning machine
Published 2019“…The RX_myKarve is a framework that contains both structure-based carving and content-based carving approaches. …”
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4
An Artificial Intelligence-Based Knowledge Management System for Outcome-Based Education Implementing in Higher Education Institutions
Published 2025“…Recommendation system on learning analysis was implemented in a hybrid algorithm combines Rule-based and Content-based filtering algorithms. …”
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5
A novel framework for potato leaf disease detection using an efficient deep learning model
Published 2022“…Moreover, the usage of the reweighted cross-entropy loss function makes our proposed algorithm more robust as the training data is highly imbalanced. …”
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6
A novel framework for potato leaf disease detection using an efficient deep learning model
Published 2022“…Moreover, the usage of the reweighted cross-entropy loss function makes our proposed algorithm more robust as the training data is highly imbalanced. …”
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7
Recommendation System Model For Decision Making in the E-Commerce Application
Published 2024thesis::doctoral thesis -
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A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition
Published 2002“…A vector quantization model that incorporate rough sets attribute reduction and rules generation with a modified version of the K-means clustering algorithm was developed, implemented and tested as a part of a speech recognition framework, in which the Learning Vector Quantization (LVQ) neural network model was used in the pattern matching stage. …”
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9
Implementation of machine learning techniques with big data and IoT to create effective prediction models for health informatics
Published 2024“…Moreover, the parameters present in the EL classifiers are optimized by using the same HFPBOA. Thefinal prediction output is obtained by averaging the weight function between the outputs of the NN, KNN, and fuzzy classifier. …”
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10
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 -
11
Digital assistant for workspace apps
Published 2022“…The problem is that way too many functions to be configured or used in the Microsoft Teams consider time waste to achieve a task with many steps. …”
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Final Year Project / Dissertation / Thesis -
12
State-of-charge estimation for lithium-ion batteries with optimized self-supervised transformer deep learning model
Published 2023“…The SSL framework trains the Transformer in two stages. In the first stage, the model is pre-trained using unlabeled data with unsupervised learning. …”
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3D face recognition using triplet point cloud network for the identification of a person with a face mask / Muhammad Azhad Zuraimi
Published 2023“…A triplet framework was proposed using the triplet loss function.…”
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14
Evaluation of machine learning classifiers in faulty die prediction to maximize cost scrapping avoidance and assembly test capacity savings in semiconductor integrated circuit (IC)...
Published 2019“…This resulting in wasted good raw material (good die and good substrate) and manufacturing capacity used to assemble and test affected bad package. In this research work, a new framework is proposed for model training and evaluation for the machine learning application in semiconductor test with objective to screen bad die using machine learning before die attachment to package. …”
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15
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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Conference or Workshop Item -
16
Rapid software framework for the implementation of machine learning classification models
Published 2021“…This paper provides an insight of a rapid software framework for implementing machine learning. This paper also demonstrates the empirical research results of machine learning classification models from the rapid software framework. …”
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17
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. Ultimately, a working prototype will be developed to validate the framework using ant colony optimization and fuzzy logic. � 2013 Springer-Verlag.…”
Conference Paper -
18
Implementing case-based reasoning approach to framework documentation
Published 2023“…Genetic algorithm (GA) is used in implementing the CBR's "retrieve", "reuse", and "revise" steps. …”
Conference paper -
19
Interactive framework for dynamic modelling and active vibration control of flexible structures
Published 2008“…Controller-design strategies, parametric as well as nonparametric, are integrated within this framework. The design and implementation of the interactive learning system incorporating the simulation algorithms, modelling and control strategies, are developed using MATLAB. …”
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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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