Výsledky vyhledávání - "Features Selection"

DenseNet-FPA: Integrating DenseNet and Flower Pollination Algorithm for Breast Cancer Histopathology Image Classification

Autoři: Wakili, Musa Adamu Shehu, Harisu Abdullahi Abdollahi, Mahdi a další

Zdroj: IEEE Access. 13:145828-145848

Témata: Breast Cancer, Deep Learning, Densenet, Feature Selection, Flower Pollination Algorithm, Histopathology, Image Classification, Classification (of Information), Computer Aided Diagnosis, Diseases, Image Enhancement, Lung Cancer, Medical Imaging, Patient Treatment, Breast Cancer Diagnosis, Convolutional Networks, Dense Convolutional Network, Features Selection, Histopathological Image Analysis, Images Classification

Popis souboru: electronic

Přístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:bth-28576
https://doi.org/10.1109/ACCESS.2025.3599319

Predicting Depression in Older Adults: A Novel Feature Selection and Neural Network Framework

Autoři: Javeed, Ashir Anderberg, Peter, Professor Ghazi, Ahmad Nauman a další

Zdroj: SNAC Neural Processing Letters. 57(3)

Témata: Depression, Feature selection, Lasso, Neural networks, Optimization, Relief, Contrastive Learning, Risk analysis, Risk assessment, Feature selection methods, Features selection, Network frameworks, Neural-networks, Older adults, Optimisations, Performance

Popis souboru: electronic

Přístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:bth-27770
https://doi.org/10.1007/s11063-025-11760-y

Exploring the role of project status information in effective code smell detection

Autoři: Alkharabsheh, Khalid Alawadi, Sadi Crespo, Yania a další

Zdroj: Cluster Computing. 28(1)

Témata: Code smell detection, Machine learning, Maintainability, Software quality, Computer software selection and evaluation, Random forests, Code smell, Feature data, Features selection, Machine learning techniques, Machine-learning, Numerical information, Status informations, Training sets

Popis souboru: electronic

Přístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:bth-27051
https://doi.org/10.1007/s10586-024-04724-9

Predicting Dementia Risk Factors Based on Feature Selection and Neural Networks

Autoři: Javeed, Ashir Dallora, Ana Luiza Sanmartin Berglund, Johan a další

Zdroj: Computers, Materials and Continua. 75(2):2491-2508

Témata: Dementia prediction, feature selection, genetic algorithm, neural networks, Deep neural networks, Diagnosis, Genetic algorithms, Learning systems, Neurodegenerative diseases, Cognitive decline, Detection/identification, Features selection, Neural-networks, Novel methods, Prediction modelling, Risk factors, Risk Identification, Societal impacts, Forecasting, Family-Centred Health, Familjecentrerad hälsa (FamCeH)

Popis souboru: electronic

Přístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-22473
https://doi.org/10.32604/cmc.2023.033783

INNOVATIVE APPROACH TO ENVIRONMENTAL WASTE CLASSIFICATION WITH ENSEMBLE LEARNING MODELS

Autoři: Mehmet Umut Salur Nermin Elmas

Zdroj: Volume: 28, Issue: 2933-956
Kahramanmaras Sutcu Imam University Journal of Engineering Sciences
Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi

Témata: Atık sınıflandırma, Topluluk öğrenme, Makine öğrenmesi, Derin öğrenme, Öznitelik seçimi, Deep Learning, Waste Management, Reduction, Reuse and Recycling, Görüntü İşleme, Image Processing, Derin Öğrenme, Waste classification, ensemble learning, machine learning, deep learning, features selection, Atık Yönetimi, Azaltma, Yeniden Kullanım ve Geri Dönüşüm

Popis souboru: application/pdf

Přístupová URL adresa: https://dergipark.org.tr/tr/pub/ksujes/issue/92254/1642586

Granular computing framework for credit card fraud detection

Autoři: Mniai Ayoub Tamouh Abdelhamid Jebari Khalid

Zdroj: Alexandria Engineering Journal, Vol 121, Iss, Pp 387-401 (2025)

Témata: Features selection, Fuzzy rough set, Metaheuristic, TA1-2040, Granular computing, Engineering (General). Civil engineering (General)

Přístupová URL adresa: https://doaj.org/article/5dcb53f5ddb34a89a49cd1210c0f37b5

Hybrid Machine Learning-Based Multi-Stage Framework for Detection of Credit Card Anomalies and Fraud

Autoři: Hatoon S. Alsagri

Zdroj: IEEE Access, Vol 13, Pp 77039-77048 (2025)

Témata: deep learning (DL), multi-stage classification, machine learning (ML), Electrical engineering. Electronics. Nuclear engineering, features selection, Credit card fraud (CCF), TK1-9971

Přístupová URL adresa: https://doaj.org/article/d73898dbcabc415cbbb570275d613871

Invariant Feature Selection for Battery State of Health Estimation in Heterogeneous Hybrid Electric Bus Fleets

Autoři: Fan, Yuantao Altarabichi, Mohammed Ghaith Pashami, Sepideh a další

Zdroj: CEUR Workshop Proceedings. 3765

Témata: Contrastive Learning, Feature Selection, Federated learning, State of charge, Casual discovery, Condition, Electric bus, Features selection, Invariant feature selection, Invariant features, Machine learning models, State of health, State of health estimation, Transfer learning, Adversarial machine learning

Popis souboru: electronic

Přístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:ri:diva-76020
https://ceur-ws.org/Vol-3765/

Enhancing PV power forecasting through feature selection and artificial neural networks: a case study

Autoři: Mokhtar Ali Abdelhalim Rabehi Abdelkerim Souahlia a další

Zdroj: Scientific Reports, Vol 15, Iss 1, Pp 1-17 (2025)

Témata: PV power, Renewable energy, Features selection, Forecasting, Artificial neural networks, Medicine, Science

Popis souboru: electronic resource

Relation: https://doaj.org/toc/2045-2322

Přístupová URL adresa: https://doaj.org/article/f2cc7b061cdc4bf8a5811dfa8d478e58

Integration of MRMR algorithm with advanced neural networks for modeling long-term crop water demand in agricultural basins

Autoři: Ahmed Elbeltagi Abdullah A. Alsumaiei Ali Raza a další

Zdroj: Applied Water Science, Vol 15, Iss 8, Pp 1-22 (2025)

Témata: Evapotranspiration, Irrigation management, Artificial neural network, Features selection, Machine learning, Water supply for domestic and industrial purposes, TD201-500

Popis souboru: electronic resource

Relation: https://doaj.org/toc/2190-5487; https://doaj.org/toc/2190-5495

Přístupová URL adresa: https://doaj.org/article/a076e5e382fc484ca9a87c2c54d4d834

Hyperspectral imaging and machine learning for herbicide-resistant kochia identification in sugarbeet

Autoři: Bright Mensah Kelvin Betitame Yu Zhang a další

Zdroj: Journal of Agriculture and Food Research, Vol 23, Iss , Pp 102284- (2025)

Témata: Herbicide-resistant kochia, Hyperspectral imaging, Stepwise features selection, Weed identification, Machine learning, Agriculture (General), S1-972, Nutrition. Foods and food supply, TX341-641

Popis souboru: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2666154325006556; https://doaj.org/toc/2666-1543

Přístupová URL adresa: https://doaj.org/article/9cc5a761708a4dfebc38f950ff749832

A Fundamental Framework for Analysis of Rainfall Prediction Features Significance

Autoři: Ye Zhian Teoh Yim Ling Loo

Zdroj: Journal of Informatics and Web Engineering, Vol 4, Iss 2, Pp 36-52 (2025)

Témata: rainfall prediction, rainfall prediction features analysis, features significance, features significance analysis framework, features selection, Electronic computers. Computer science, QA75.5-76.95, Information technology, T58.5-58.64

Popis souboru: electronic resource

Relation: https://journals.mmupress.com/index.php/jiwe/article/view/1473; https://doaj.org/toc/2821-370X

Přístupová URL adresa: https://doaj.org/article/015a97d26e854559840a1b60279bf03e

Finger Movement Recognition using Machine Learning Algorithms with Tree-Seed Algorithm

Autoři: Karakul, Muhammed Sami Gökçen, Ahmet Mühendislik ve Doğa Bilimleri Fakültesi -- Bilgisayar Mühendisliği Bölümü

Přispěvatelé: Karakul, Muhammed Sami Gökçen, Ahmet Mühendislik ve Doğa Bilimleri Fakültesi -- Bilgisayar Mühendisliği Bölümü

Zdroj: Turkish Journal of Electrical Engineering and Computer Sciences. 32:718-731

Témata: Accuracy rate, Prosthetics, Classification accuracy, Electromyography, Features sets, Engineering, Electrical & Electronic, Pattern Recognition, Machine learning algorithms, Adversarial machine learning, Seed-algorithm, Computer Science, Artificial Intelligence, Palmprint recognition, Gesture recognition, Features selection, Nearest neighbor search, Finger movements, Electromyography signals, Feature selection, Tree-seed algorithm, Surface electromyography

Popis souboru: application/pdf

Přístupová URL adresa: https://hdl.handle.net/20.500.12508/3081

A Study on ML-Based Software Defect Detection for Security Traceability in Smart Healthcare Applications

Autoři: Mcmurray, S. Sodhro, A. H.

Zdroj: Sensors. 23(7)

Témata: Algorithms, Bayes Theorem, Machine Learning, Neural Networks, Computer, Software, Support Vector Machine, Adaptive boosting, Application programs, Decision trees, Defects, Extraction, Learning systems, Least squares approximations, Life cycle, Nearest neighbor search, Principal component analysis, Software design, Support vector machines, Elastic net, Ensemble learning, Features extraction, Features selection, Machine-learning, Partial least square regression, Principal-component analysis, Selection techniques, Software defect prediction, Software development life-cycle, algorithm, Feature extraction, feature selection, software defects prediction

Popis souboru: print

Přístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-60226
https://doi.org/10.3390/s23073470

Breaking barriers: a statistical and machine learning-based hybrid system for predicting dementia

Autoři: Javeed, Ashir Anderberg, Peter, Professor Ghazi, Ahmad Nauman a další

Zdroj: Frontiers in Bioengineering and Biotechnology. 11

Témata: dementia, F-score, feature selection, machine learning, voting classifier, Decision trees, Deterioration, Diagnosis, Forecasting, Hybrid systems, Learning systems, Logistic regression, Neurodegenerative diseases, Noninvasive medical procedures, Support vector machines, Baseline machines, Breakings, Correlation coefficient, Diagnostic systems, Features selection, Machine learning models, Machine-learning, Voting classifiers, Family-Centred Health, Familjecentrerad hälsa (FamCeH)

Popis souboru: electronic

Přístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-23566
https://doi.org/10.3389/fbioe.2023.1336255

Anomaly-based intrusion detection system based on SMOTE-IPF, Whale Optimization Algorithm, and ensemble learning

Autoři: Tibebu Bekele Shana Neetu Kumari Mayank Agarwal a další

Zdroj: Intelligent Systems with Applications, Vol 27, Iss , Pp 200543- (2025)

Témata: Network intrusion detection systems, Whale Optimization Algorithm, Machine learning, Features selection, Imbalanced data, Cyber security, Cybernetics, Q300-390, Electronic computers. Computer science, QA75.5-76.95

Popis souboru: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2667305325000699; https://doaj.org/toc/2667-3053

Přístupová URL adresa: https://doaj.org/article/1fcff709aae54bc4b9313b07e76830bc

Classification and recognition of black tea with different degrees of rolling based on machine vision technology and machine learning algorithms

Autoři: Hanting Zou Xiao-Lan Yu Tianmeng Lan a další

Zdroj: Heliyon, Vol 11, Iss 14, Pp e43862- (2025)

Témata: Black tea rolling, Classification recognition, Nondestructive testing, Color features selection, Science (General), Q1-390, Social sciences (General), H1-99

Popis souboru: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2405844025022558; https://doaj.org/toc/2405-8440

Přístupová URL adresa: https://doaj.org/article/a8796fd55a4d44d981c1b0eb4f0f4567

A Study on Comparative Analysis of Feature Selection Algorithms for Students Grades Prediction

Autoři: Arham Tariq, Muhammad

Zdroj: Journal of Information and Organizational Sciences, Vol 48, Iss 1, Pp 133-147 (2024)
Journal of Information and Organizational Sciences
Volume 48
Issue 1

Témata: Student Performance, Information theory, 4. Education, Features Selection, Multi-Class Datasets, Classification Models, Q350-390, Educational Data Mining

Popis souboru: application/pdf

Přístupová URL adresa: https://doaj.org/article/790c30f623a34c8cad6e383aeeda9ff6
https://hrcak.srce.hr/318118
https://doi.org/10.31341/jios.48.1.7
https://hrcak.srce.hr/file/459740
https://hrcak.srce.hr/318118
https://doi.org/10.31341/jios.48.1.7

Probabilistic prediction intervals of short-term wind speed using selected features and time shift dependent machine learning models

Autoři: Rami Al-Hajj Gholamreza Oskrochi Mohamad M. Fouad a další

Zdroj: Mathematical Biosciences and Engineering, Vol 22, Iss 1, Pp 23-51 (2025)

Témata: wind speed forecasting, wind energy, features selection, support vector regressors, prediction intervals, probabilistic energy forecasting, kernel density estimator., Biotechnology, TP248.13-248.65, Mathematics, QA1-939

Popis souboru: electronic resource

Relation: https://doaj.org/toc/1551-0018

Přístupová URL adresa: https://doaj.org/article/a927e598e03a4663be499a3e73ec7fdd

Identifying the Spectral-Based Neurophysiological Biomarkers to Detect Panic Disorder from Alpha Band Using Machine Learning Algorithms

Autoři: Unlu, B. Yetkin, S. Nassehi, F. a další

Zdroj: 2023 Medical Technologies Congress (TIPTEKNO). :1-4

Témata: Adaptive boosting, Panic disorder, Biomedical signal processing, Electroencephalography, Machine learning algorithms, Electroencephalogram (EEG), Machine Learning, Panic Disorder (PD), Electrophysiology, Electroencephalogram, Features selection, Spectral density, Physical symptoms, Alpha band, Alpha Band, Feature Selection, Optimal combination, Condition, Machine-learning, Spectral feature

Přístupová URL adresa: https://hdl.handle.net/20.500.11851/11033
https://doi.org/10.1109/TIPTEKNO59875.2023.10359173 10.1109/TIPTEKNO59875.2023.10359173