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The implications for ahybrid detection technique against malicious sqlattacks on web applications
Published 2025“…The proposed DetectCombined is an innovated technique that execute a protection code based on a sequence of three stages: filtration-validation-history, this technique produces a robust protection code that distinguish between safe SQL commands and malicious ones, and reinforce the memory of detection procedure by saving previous SQL attacks in special tables in the remote database, regardless of the types of users whether a general user of admin. …”
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A case study of microarray breast cancer classification using machine learning algorithms with grid search cross validation
Published 2023“…Machine learning is a subfield of artificial intelligence (AI) and computer science that uses data and algorithms to mimic how humans learn, and gradually improving its accuracy. …”
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Phylogenetic tree classification system using machine learning algorithm
Published 2015“…A study is conducted to develop an automated phylogenetic tree image classification system by using machine learning algorithm. …”
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Final Year Project Report / IMRAD -
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Prediction of Machine Failure by Using Machine Learning Algorithm
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Final Year Project -
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Evaluation of the Transfer Learning Models in Wafer Defects Classification
Published 2022“…This enhanced image data numbers then went through Logistic Regression as a classifier. A 20-fold cross-validation was used to validate the score metrics. …”
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Job position prediction based on skills and experience using machine learning algorithm / Ezaryf Hamdan
Published 2024“…The algorithm undergoes rigorous training with a vast dataset to ensure high prediction accuracy and reliability. …”
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A deep reinforcement learning hybrid algorithm for the computational discovery and characterization of small proteins utilizing mycobacterium tuberculosis as a model
Published 2025“…This study presents the development and evaluation of a novel hybrid machine learning algorithm that integrates the strengths of Random Forest and Gradient Boosting models to enhance the prediction of smORFs. …”
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Green building valuation based on machine learning algorithms / Thuraiya Mohd ... [et al.]
Published 2021“…This experiment used five common machine learning algorithms namely 1) Linear Regressor, 2) Decision Tree Regressor, 3) Random Forest Regressor, 4) Ridge Regressor and 5) Lasso Regressor tested on a real estate data-set of covering Kuala Lumpur District, Malaysia. 3 set of experiments was conducted based on the different feature selections and purposes The results show that the implementation of 16 variables based on Experiment 2 has given a promising effect on the model compare the other experiment, and the Random Forest Regressor by using the Split approach for training and validating data-set outperformed other algorithms compared to Cross-Validation approach. …”
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Suicide and self-harm prediction based on social media data using machine learning algorithms
Published 2023“…In combined with robust machine learning algorithms, social networking data may provide a potential path ahead. …”
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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM)
Published 2024“…Finally, the proposed algorithms were also validated on another dataset of a university campus in a different region. …”
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The Implementation of a Machine Learning-based Routing Algorithm in a Lab-Scale Testbed
Published 2024“…Due to network complexity, conventional QoS-improving routing algorithms (RAs) may be impractical. Thus, researchers are developing intelligent RAs, including machine learning (ML)-based algorithms to meet traffic Q oS r equirements. …”
Conference Paper -
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Brain Tumour Classification using Deep Learning with Residual Attention Network: A Comparative Study
Published 2021“…The algorithm performance is evaluated based on training accuracy, testing accuracy, validation accuracy, and validation loss metrices. …”
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Brain Tumour Classification using Deep Learning with Residual Attention Network : A Comparative Study
Published 2021“…The algorithm performance is evaluated based on training accuracy, testing accuracy, validation accuracy, and validation loss metrices. …”
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Proceeding -
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Fractional Stochastic Gradient Descent Based Learning Algorithm For Multi-layer Perceptron Neural Networks
Published 2021“…The performance is highly subjective to the optimization of learning parameters. In this study, we propose a learning algorithm for the training of MLP models. …”
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An interactive analytics approach for sustainable and resilient case studies: a machine learning perspective
Published 2023“…Moreover, the proposed algorithm is compared with two other algorithms for validation purposes. …”
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The formulation of a transfer learning pipeline for the classification of the wafer defects
Published 2023“…The ML classifiers were tuned via a 5-fold cross-validation technique through grid search approach. …”
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Evaluating the Performance of a Visual Support System for Driving Assistance using a Deep Learning Algorithm
Published 2024“…The model utilises the YOLO V8 deep learning algorithm in the Google Colab environment and is trained using a custom dataset managed by the Roboflow dataset manager. …”
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