Sökning: "Performance anomaly detection"

Visar resultat 11 - 15 av 38 avhandlingar innehållade orden Performance anomaly detection.

  1. 11. On a learning system for industrial automation : Model-based control and diagnostics for decision support

    Författare :Moksadur Rahman; Konstantinos Kyprianidis; Anders Avelin; Gunnar Bengtsson; John Hedengren; Mälardalens högskola; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Learning system; Supervisory system; Pulp and paper; Micro gas turbine; Process modelling; Model-based control; Diagnostics; Decision support; Anomaly detection; Fault detection; Energy- and Environmental Engineering; energi- och miljöteknik;

    Sammanfattning : Access to energy is fundamental to economic and technological advancement. Hence, the more the world develops, the greater the demand for energy becomes. Evidently, the production and consumption of energy alone account for more than 80% of global anthropogenic greenhouse gas (GHG) emissions. LÄS MER

  3. 12. Onboard condition monitoring of vehicle-track dynamic interaction using machine learning : Enabling the railway industry’s digital transformation

    Författare :Rohan Kulkarni; Mats Berg; Ulf Carlsson; Alireza Qazizadeh; Sebastian Stichel; Jordi Viñolas; KTH; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Active preventive maintenance; intelligent fault diagnosis; anomaly detection; vehicle fleet; track irregularities; vehicle hunting; wheel-rail interface.; Farkostteknik; Vehicle and Maritime Engineering;

    Sammanfattning : The railway sector’s reliability, availability, maintainability, and safety (RAMS) can significantly improve by adopting condition based maintenance (CBM). In the CBM regime, maintenance decisions are driven by condition monitoring (CM) of the asset. LÄS MER

  4. 13. Generalisation and reliability of deep learning for digital pathology in a clinical setting

    Författare :Milda Pocevičiūtė; Claes Lundström; Stina Garvin; Gabriel Eilertsen; Nasir Rajpoot; Linköpings universitet; []
    Nyckelord :MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; Deep learning; Digital pathology; Generalisation; Uncertainty estimation; Anomaly detection; Data distribution shift;

    Sammanfattning : Deep learning (DL) is a subfield of artificial intelligence (AI) focused on developing algorithms that learn from data to perform some tasks that can aid humans in their daily life or work assignments. Research demonstrates the potential of DL in supporting pathologists with routine tasks like detecting breast cancer metastases and grading prostate cancer. LÄS MER

  5. 14. How can data science contribute to a greener world? : an exploration featuring machine learning and data mining for environmental facilities and energy end users

    Författare :Dong Wang; Mats Tysklind; Johan Trygg; Lili Jiang; Venkat Venkatasubramanian; Umeå universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Wastewater treatment; Process analytics; Big data; Machine learning; Interpretable AI; Power plants; Failure analysis; Data mining; Buildings; Energy consumption; Anomaly detection;

    Sammanfattning : Human society has taken many measures to address environmental issues. For example, deploying wastewater treatment plants (WWTPs) to alleviate water pollution and the shortage of usable water; using waste-to-energy (WtE) plants to recover energy from the waste and reduce its environmental impact. LÄS MER

  7. 15. Machine learning-based diagnostics and observability in mobile networks

    Författare :Tobias Sundqvist; Erik Elmroth; Monowar H. Bhuyan; Rolf Stadler; Umeå universitet; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Anomaly detection; Root cause analysis; Observability; Machine learning; Radio Access Network; 5G; Computer Science; datalogi;

    Sammanfattning : To meet the high-performance and reliability demands of 5G, the Radio Access Network (RAN) is moving to a cloud-native architecture. The new microservice architecture promises increased operational efficiency and a shorter time-to-market, but it also comes with a price. LÄS MER