Search Results - (( learning implementation using algorithm ) OR ( based application optimization algorithm ))
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Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation
Published 2023“…Currently available framework documentation approaches are not very effective for new framework users, and this scenario tends to discourage new users in using frameworks. 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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Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms
Published 2008“…Also, this research involves in developing a machine-learning system and program via genetic algorithm that is capable of performing independent learning capability and optimization for scanning sequence using novel GA operators. …”
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An improved teaching-learning-based optimization for extreme learning machine in floating photovoltaic power forecasting
Published 2025“…This study presents an improved teaching-learning-based optimization algorithm with extreme learning machine for floating photovoltaic power forecasting. …”
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Deep Learning Based Face Attributes Recognition
Published 2018“…Combined-algorithm based optimizers plays an important role in optimizing the training algorithm. …”
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Overhead view based person counting using deep learning
Published 2022“…Second, the OpenVINO Inference Engine is utilized to optimize the trained models in order to facilitate real-time implementation. Third, the accurate tracking of each detected person is performed using the deep learning based tracking framework, known as DeepSORT. …”
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Final Year Project / Dissertation / Thesis -
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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…It has been successfully implemented and used in various areas such as machine learning applications, engineering applications, network applications, parameter control, and other similar applications to solve optimization problems. …”
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Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters
Published 2024“…This research provides new insights into the application of machine learning algorithms for water quality management as well as guidance for optimal algorithm selection.…”
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EEG-based emotion recognition using machine learning algorithms
Published 2024“…Thus, this project proposed an optimised machine learning algorithms to classify emotion by analysing brain activity using Electroencephalogram (EEG) signals. …”
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Final Year Project / Dissertation / Thesis -
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Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar
Published 2019“…In this study, the performance of these three algorithms in obtaining the optimal blade design based on the �436�45D are investigated and compared. …”
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Web Usage Mining for UUM Learning Care Using Association Rules
Published 2004“…In order to produce the university E-Learning (UUM Educare) portal usage patterns and user behaviors, this paper implements the high level process of Web usage mining using basic Association Rules algorithm - Apriori Algorithm. …”
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Automated model selection for corporation credit risk assessment using machine learning / Zulkifli Halim
Published 2023“…The global trend in the CCRA study shows that implementing machine learning and deep learning techniques is expanding rapidly. …”
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Web usage mining for UUM learning care using association rules
Published 2004“…In order to produce the university E-Learning (UUM Educare) portal usage patterns and user behaviors, this paper implements the high level process of Web usage mining using basic Association Rules algorithm - Apriori Algorithm. …”
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Image-based air quality estimation using convolutional neural network optimized by genetic algorithms: A multi-dataset approach
Published 2025“…The convolutional neural network is optimized using genetic algorithms, which dynamically tune hyperparameters such as learning rate, batch size, and momentum to improve performance and generalizability across diverse environmental conditions. …”
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An Improved Grasshopper Optimization Algorithm Based Echo State Network for Predicting Faults in Airplane Engines
Published 2020“…Hence, in this work, we design an improved Grasshopper Optimization Algorithm (GOA) based ESN. The proposed technique uses a new solution representation with a simplified attraction and repulsion mechanisms to enhance performance. …”
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A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…Then, this study aims to optimize the hyperparameters of the developed DNN model using the Arithmetic Optimization Algorithm (AOA) and, lastly, to evaluate the performance of the newly proposed deep learning model with Simulated Kalman Filter (SKF) algorithm in solving image encryption application. …”
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An evaluation of Monte Carlo-based hyper-heuristic for interaction testing of industrial embedded software applications.
Published 2020“…The results show the Q-EMCQ is also capable of outperforming the original EMCQ as well as several recent meta/hyper-heuristic including modified choice function, Tabu high-level hyperheuristic, teaching learning-based optimization, sine cosine algorithm, and symbiotic optimization search in clustering quality within comparable execution time.…”
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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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Earthquake prediction model based on geomagnetic field data using automated machine learning
Published 2024“…Several features were extracted from them through wavelet scattering transform (WST). The features were used as the input to model optimization, of which the strategy for automatic algorithm selection and hyperparameter tuning was performed based on the asynchronous successive halving algorithm (ASHA). …”
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