بدائل البحث:
machine algorithm » cosine algorithm (توسيع البحث)
method algorithm » mould algorithm (توسيع البحث)
code algorithm » cosine algorithm (توسيع البحث), rd algorithm (توسيع البحث), colony algorithm (توسيع البحث)
machine algorithm » cosine algorithm (توسيع البحث)
method algorithm » mould algorithm (توسيع البحث)
code algorithm » cosine algorithm (توسيع البحث), rd algorithm (توسيع البحث), colony algorithm (توسيع البحث)
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Monitoring Bone Density Using Microwave Tomography of Human Legs: A Numerical Feasibility Study
منشور في 2021"…This study was performed using an in-house finite-element method contrast source inversion algorithm (FEM-CSI). …"
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82
A machine learning model for early detection of diabetic foot using thermogram images
منشور في 2021"…However, the distribution of plantar temperature may be heterogeneous, making it difficult to quantify and utilize to predict outcomes. We have compared a machine learning-based scoring technique with feature selection and optimization techniques and learning classifiers to several state-of-the-art Convolutional Neural Networks (CNNs) on foot thermogram images and propose a robust solution to identify the diabetic foot. …"
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Day-Ahead Load Demand Forecasting in Urban Community Cluster Microgrids Using Machine Learning Methods
منشور في 2022"…From the results, it is found that the Levenberg–Marquardt optimization algorithm-based ANN model gives the best electrical load forecasting results.…"
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88
Gene selection for microarray data classification based on Gray Wolf Optimizer enhanced with TRIZ-inspired operators
منشور في 2021"…The outcomes of the DNA microarray is a table/matrix, called gene expression data. Pattern recognition algorithms are widely applied to gene expression data to differentiate between health and cancerous patient samples. …"
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89
A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method
منشور في 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
منشور في 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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91
Ensemble-Based Spam Detection in Smart Home IoT Devices Time Series Data Using Machine Learning Techniques
منشور في 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
منشور في 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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93
Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification
منشور في 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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Interval-Valued SVM Based ABO for Fault Detection and Diagnosis of Wind Energy Conversion Systems
منشور في 2022"…The developed techniques are based on Support Vector Machine (SVM) model to improve the diagnosis of WEC systems. …"
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The Use of Microwave Tomography in Bone Healing Monitoring
منشور في 2019احصل على النص الكامل
doctoralThesis -
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A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI
منشور في 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. …"