Sökning: "Optimera med AI"

Hittade 3 avhandlingar innehållade orden Optimera med AI.

  1. 1. 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

  3. 2. From Models to Code and Back : A Round-trip Approach for Model-driven Engineering of Embedded Systems

    Författare :Federico Ciccozzi; Mikael Sjödin; Antonio Cicchetti; Dániel Varró; Mälardalens högskola; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; model-driven engineering; embedded systems; code generation; extra-functional properties; back-propagation; Computer Science; datavetenskap;

    Sammanfattning : The complexity of modern systems is continuously growing, thus demanding novel powerful development approaches.In this direction, model-driven and component-based software engineering have reached the status of promising paradigms for the development of complex systems. LÄS MER

  4. 3. A study of wireless communications with reinforcement learning

    Författare :Wanlu Lei; Ming Xiao; Chenguang Lu; Mikael Skoglund; Geoffrey Ye Li; KTH; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Reinforcement learning; wireless communications; decentralized learning; beam tracking; machine learning; Förstärkningsinlärning; trådlös kommunikation; decentrali- serad inlärning; strålspårning i mmvåg; maskininlärning; Electrical Engineering; Elektro- och systemteknik;

    Sammanfattning :  The explosive proliferation of mobile users and wireless data traffic in recent years pose imminent challenges upon wireless system design. The trendfor wireless communications becoming more complicated, decentralized andintelligent is inevitable. LÄS MER