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81
A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method
Published 2022“…To deal with the data-imbalance issue, this research develops an efficient hybrid network-based IDS model (HNIDS), which is utilized using the enhanced genetic algorithm and particle swarm optimization(EGA-PSO) and improved random forest (IRF) methods. …”
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Design of adaptive arrays based on element position perturbations
Published 1993“…The main advantage of using this technique over the other commonly used methods is that the amplitudes and phases of the array elements can be used mainly to steer the main beam towards the desired signal. …”
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Ensemble-Based Spam Detection in Smart Home IoT Devices Time Series Data Using Machine Learning Techniques
Published 2020“…A spamicity score was awarded to each of the IoT devices by the algorithm, based on the feature importance and the root mean square error score of the machine learning models to determine the trustworthiness of the device in the home network. …”
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Fault Diagnosis Based Machine Learning and Fault Tolerant Control of Multicellular Converter Used in Photovoltaic Water Pumping System
Published 2023“…Meanwhile, the serial connection and redundant topology of multicellular converters render the system more vulnerable to failure. fault diagnosis-based machine learning approach and fault tolerant control (FTC) are proposed for multicellular power converters. …”
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Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification
Published 2025“…<p dir="ltr">In recent years, deep learning methods have dramatically improved medical image analysis, though earlier models faced difficulties in capturing intricate spatial and contextual details. …”
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UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data
Published 2024“…Moreover, the study proposes a hybrid algorithm that combines UniBFS with two filter-based FS methods, ReliefF and Fisher, to identify pertinent features during the global search phase. …”
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Interval-Valued SVM Based ABO for Fault Detection and Diagnosis of Wind Energy Conversion Systems
Published 2022“…The developed techniques are based on Support Vector Machine (SVM) model to improve the diagnosis of WEC systems. …”
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A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI
Published 2025“…After handling missing values, balancing the dataset, and analyzing the classifier’s performance, it is found that tree-based algorithms, particularly RF, perform better for all the datasets. …”
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Predicting Dropouts among a Homogeneous Population using a Data Mining Approach
Published 2019“…Our study also reveals that ensemble machine learning algorithms are more reliable and outperform standard algorithms.…”
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93
An Efficient Prediction System for Diabetes Disease Based on Deep Neural Network
Published 2021“…A performance comparison between the DNN algorithm and some well‐known machine learning techniques as well as the state‐of‐the‐art methods is presented. …”
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Machine Learning Techniques for Pharmaceutical Bioinformatics
Published 2018“…A predictive model is developed to predict drug indication as well as to predict new DDIs using multiple machine learning algorithms. This dissertation presents a case study of predicted anti-cancer activity for 38 drugs. …”
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Utilization of AI to Predict Shear Strength Parameters of Soil Based on Their Physical Properties
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Type 2 Diabetes Mellitus Automated Risk Detection Based on UAE National Health Survey Data: A Framework for the Construction and Optimization of Binary Classification Machine Learn...
Published 2020“…Machine Learning (ML) saw a great increase in general and domain specific research. …”
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