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Machine learning-based classification of maritime accidents
SHIPS AND OFFSHORE STRUCTURES, Ocak 2025, ISSN: 1744-5302
ATAK ÜSTÜN,DEMİRAY AHMET
Üstün Atak Özgün Makale "Maritime transportation""accident analysis""machine learning""classification"
Best Paper Award 'Machine Learning for Communications and Networking''
IEEE International Conference on Communications, 2024
Algorithmic Trading with Machine Learning
Mathematical Sciences, Xi'an Jiaotong University, 2019
JUAN DU
Ahmet Göncü Tez Doktora Tamamlandı
Emotion Recognition via Galvanic Skin Response: Comparison of Machine Learning Algorithms and Feature Extraction Methods
ISTANBUL UNIVERSITY-JOURNAL OF ELECTRICAL AND ELECTRONICS ENGINEERING, Vol. 17, No. 1, Ocak 2017, s. 3129-3136, ISSN: 1303-0914
AYATA DEĞER,YASLAN YUSUF,KAMAŞAK MUSTAFA ERSEL
Yusuf Yaslan Özgün Makale Biomedical Signal ProcessingEmotion RecognitionPattern RecognitionMachine LearningPhysiological SignalGalvanic Skin ResponseDecision TreeRandom Forestk-Nearest NeighborsSupport Vector Machine
Machine learning approach to ship fuel consumption: A case of container vessel
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT, Vol. 84, No. 102389, Haziran 2020, s. 1-14, ISSN: 1361-9209
UYANIK TAYFUN,KARATUG CAGLAR,ARSLANOĞLU YASİN
Yasin Arslanoğlu Özgün Makale Fuel consumptionMachine learningPerformance monitoringShip operational efficiencyREGRESSIONREDUCTIONSYSTEMSRIDGEdata drivenenergy efficiencycontainer vesselfuel oilfuel consumption
Analysis of Mining Lost Time Incident Duration Influencing Factors Through Machine Learning
Mining, Metallurgy & Exploration, Vol. 38, No. 2, Ocak 2021, s. 1031-1039, ISSN: 2524-3462","2524-3470
KAHRAMAN MUHAMMET MUSTAFA
Muhammet Mustafa Kahraman Özgün Makale Decision tree; Lost time incidents; Machine learning; Neural network; Occupational safety
Machine learning approach to ship fuel consumption: A case of container vessel
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT, Vol. 84, Temmuz 2020, ISSN: 1361-9209
UYANIK TAYFUN,KARATUĞ ÇAĞLAR,ARSLANOĞLU YASİN
Yasin Arslanoğlu Özgün Makale Fuel consumptionMachine learningPerformance monitoringShip operational efficiencyREGRESSIONREDUCTIONSYSTEMSDRIVENRIDGE
Machine learning based visibility estimation to ensure safer navigation in strait of Istanbul
APPLIED OCEAN RESEARCH, Vol. 112, Temmuz 2021, ISSN: 0141-1187
UYANIK TAYFUN, KARATUĞ ÇAĞLAR, ARSLANOĞLU YASİN
Tayfun Uyanık Özgün Makale Safe navigation Risk assessment Istanbul strait Machine learning Visibility prediction
A Machine Learning Approach to Predict AdvancedMalware
BalkanCom2018, Second International Balkan Conference on Communications and Networking, Podgorica/KARADAĞ, 6 Haziran 2018
BAHTİYAR ŞERİF,YAMAN MEHMET BARIŞ,ALTINİĞNE CAN YILMAZ
Şerif Bahtiyar Tam metin bildiri SecurityMachine LearningMalware
Machine learning-based estimation of energy dissipation capacity of RC shear walls
STRUCTURES, Vol. 45, Kasım 2022, s. 10, ISSN: 2352-0124
TOPALOGLU BERKAY, TAŞKIN KAYA GÜLŞEN, SÜTCÜ FATİH, DEĞER ZEYNEP
Zeynep Değer Özgün Makale Cumulative dissipated energy Energy-based design approach Feature selection Machine learning Predictive models Reinforced concrete shear walls
Machine learning approach to ship fuel consumption: A case of container vessel
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT, Vol. 84, Temmuz 2020, ISSN: 1361-9209
UYANIK TAYFUN,KARATUĞ ÇAĞLAR,ARSLANOĞLU YASİN
Çağlar Karatuğ Özgün Makale Fuel consumptionMachine learningPerformance monitoringShip operational efficiencyREGRESSIONREDUCTIONSYSTEMSDRIVENRIDGE
Advanced Mobility Robustness Optimization Models in Future Mobile Networks Based on Machine Learning Solutions
Institute of Electrical and Electronics Engineers (IEEE), Vol. 10, Ocak 2022, s. 19, ISSN: 2169-3536
SHAYEA IBRAHEEM ABDULLAH MOHAMMED
Ibraheem Abdullah Mohammed Shayea Özgün Makale Optimization 5G mobile communication Heuristic algorithms Handover Robustness Cellular networks Q-learning Machine learning Heterogeneous networks handover self-optimization mobility robustness optimization handover margin time-to-trigger heterogeneous networks 5G network
Developing a Machine Learning Model to Predict Silicate Impurity in Iron Ore Flotation Concentrate
IMPS 2022 - 17th International Mineral Processing Symposium, İstanbul/TÜRKİYE, 15 Aralık 2022, s. 991-1000
PURAL YUSUF ENES
Yusuf Enes Pural Tam metin bildiri FlotationGrade EstimationMachine LearningRandom ForestMulti-Layer Perceptron
Machine learning based visibility estimation to ensure safer navigation in strait of Istanbul
APPLIED OCEAN RESEARCH, Vol. 112, Temmuz 2021, ISSN: 0141-1187
UYANIK TAYFUN, KARATUĞ ÇAĞLAR, ARSLANOĞLU YASİN
Yasin Arslanoğlu Özgün Makale Safe navigation Risk assessment Istanbul strait Machine learning Visibility prediction
Machine learning approach to ship fuel consumption: A case of container vessel
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT, Vol. 84, No. 102389, Haziran 2020, s. 1-14, ISSN: 1361-9209
UYANIK TAYFUN,KARATUG CAGLAR,ARSLANOĞLU YASİN
Tayfun Uyanık Özgün Makale Fuel consumptionMachine learningPerformance monitoringShip operational efficiencyREGRESSIONREDUCTIONSYSTEMSRIDGEdata drivenenergy efficiencycontainer vesselfuel oilfuel consumption
Developing meta-heuristic optimization based ensemble machine learning algorithms for hydraulic efficiency assessment of storm water grate inlets
URBAN WATER JOURNAL, Vol. 19, No. 10, Ocak 2022, ISSN: 1573-062X
EKMEKÇİCOĞLU ÖMER, BAŞAKIN EYYUP ENSAR, ÖZGER MEHMET
Mehmet Özger Özgün Makale Hydraulic efficiency meta-heuristics optimization storm water grate inlet tree-based machine learning urban drainage
Machine learning assisted estimation of total solids content of drilling fluids
ARTIFICIAL INTELLIGENCE IN GEOSCIENCES, Vol. 6, No. 2, Ocak 2025, s. 18, ISSN: 26665441
GÜNEL BERAT TUĞBERK,PAK YASEMİN DEFNE,HEREKELİ AHMET ÖZGÜN,GÜL SERCAN,KULGA İHSAN BURAK,ARTUN FAZIL EMRE
İhsan Burak Kulga Özgün Makale Drilling fluids Total solids content Machine learning
Measurement and Analysis of In Vivo Microwave Dielectric Properties Collected From Normal, Benign, and Malignant Rat Breast Tissues: Classification Using Supervised Machine Learning Algorithms
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, Vol. 73, 2024, s. 11, ISSN: 0018-9456
PASTACI ÖZSOBACI NURAL,ÖNEMLİ EMRE,AYDINALP CEMANUR,YILMAZ ABDOLSAHEB TUBA
Tuba Yılmaz Abdolsaheb Özgün Makale Cancer Rats Dielectrics In vivo Microwave measurement Permittivity measurement Pathology Animal experiments breast cancer dielectric spectroscopy in vivo dielectric properties (DPs) machine learning (ML) microwave diagnostics rat breast models supervised learning
Prediction of flyrock distances using XGBoost machine learning method
13th WORLD CONFERENCE ON EXPLOSIVES AND BLASTING, Krakow/POLONYA, 20 Eylül 2025, s. 315-324
AĞAN YAŞAR,HÜDAVERDİ TÜRKER
Yaşar Ağan Tam metin bildiri Blasting Machine LearningFlyrock
AirWave: Enhancing UAV Connectivity in Cellular Networks through an Integrated Simulation Framework
2024 IEEE International Conference on Big Data & Machine Learning (ICBDML), Bhopal/HİNDİSTAN, 24 Şubat 2024, s. 295-302
ZOR EMİRHAN,TASKİRAN YUSUF,DAEL FARES ABDULHAFIDH DERHEM,SHAYEA IBRAHEEM ABDULLAH MOHAMMED,RZAYEVA LEİLA,SYZDYKOVA ZULEİKHA
Ibraheem Abdullah Mohammed Shayea Tam metin bildiri UAV communications 5G and beyond Handover management Reinforcement learning machine learning

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