Sökning: "Obalanserad data."

Visar resultat 1 - 5 av 30 uppsatser innehållade orden Obalanserad data..

  1. 1. Clean to be Lean : Implementering av Lean Managment hos kurir- och fraktbolag

    M1-uppsats, Högskolan i Borås/Akademin för textil, teknik och ekonomi

    Författare :Dylan Alejandro Valdez Orbegoso; Fadi Alrais; [2023]
    Nyckelord :Lean managment; logistik;

    Sammanfattning : Detta examensarbete fokuserar på fraktterminalen som tillhör kurir- och fraktbolaget FedEx Corporation. Fraktterminalen är placerad i Landvetter, Sverige. Det finns ett antal brister och problem i terminalen och några av dessa handlar om hur pakethanteringsprocessen är strukturerad och hur berörda arbetsaktiviteter utförs. LÄS MER

  3. 2. Predicting the Impact of Supply Chain Disruptions Using Statistical Analysis and Machine Learning

    Master-uppsats, KTH/Matematisk statistik

    Författare :Hannes Andersson; John Sjöberg; [2023]
    Nyckelord :Supply chain disruption; SMOTE; feature engineering; machine learning; random forest; statistics; applied mathematics; Störning i försörjningskedja; maskininlärning; matematik; statistik;

    Sammanfattning : The dairy business is vulnerable to supply chain disruptions since large safety stocks to cover up losses are not always a viable option, therefore it is crucial to maintain a smooth supply chain to ensure stable delivery accuracies. Disruptions are unpredictable and hard to avoid in the supply chain, especially in cases where production errors cause lost production volume. LÄS MER

  4. 3. Performance comparison of data mining algorithms for imbalanced and high-dimensional data

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Daniel Rubio Adeva; [2023]
    Nyckelord :Data science; neural network; random forest; support vector machine; imbalanced data; average precision; ROC; Datavetenskap; neuralt nätverk; slumpmässig skog; stödvektormaskin; obalanserad data; medelprecision; ROC;

    Sammanfattning : Artificial intelligence techniques, such as artificial neural networks, random forests, or support vector machines, have been used to address a variety of problems in numerous industries. However, in many cases, models have to deal with issues such as imbalanced data or high multi-dimensionality. LÄS MER

  5. 4. Classification of imbalanced disparate medical data using ontology

    Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Ludvig Karlsson; Gustav Wilhelm Kopp Sundin; [2023]
    Nyckelord :Ontology; machine learning; random forest; imbalanced data; oncology; digital transformation;

    Sammanfattning : Through the digitization of healthcare, large volumes of data are generated and stored in healthcare operations. Today, a multitude of platforms and digital infrastructures are used for storage and management of data. The systems lack a common ontology which limits the interoperability between datasets. LÄS MER

  7. 5. Implementation of Bolt Detection and Visual-Inertial Localization Algorithm for Tightening Tool on SoC FPGA

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Muhammad Ihsan Al Hafiz; [2023]
    Nyckelord :Bolt detection; Visual-Inertial localization; System-on-Chip SoC ; Field-Programmable Gate Array FPGA ; Machine learning; Perspective-n-Points; Error-State Extended Kalman Filter ESEKF ; High-Level Synthesis HLS ; YOLO; Tightening tool; Bultdetektering; visuell-tröghetslokalisering; System-on-Chip SoC ; Field-Programmable Gate Array FPGA ; Machine Learning; Perspective-n-Points; Error-State Extended Kalman Filter ESEKF ; High-Level Synthesis HLS ; YOLO; åtdragningsverktyg;

    Sammanfattning : With the emergence of Industry 4.0, there is a pronounced emphasis on the necessity for enhanced flexibility in assembly processes. In the domain of bolt-tightening, this transition is evident. Tools are now required to navigate a variety of bolts and unpredictable tightening methodologies. LÄS MER