Sökning: "technique feature analysis"

Visar resultat 1 - 5 av 58 uppsatser innehållade orden technique feature analysis.

1. 1. Data analysis for predictive maintenance and potential challenges associated with the technology integration of steel industry machines.

   Master-uppsats, Högskolan i Gävle/Elektronik

   Författare :Pradip Nath; [2024]
   Nyckelord :Data Science; Data processing; Industrial Manufacturing; System Identification; Predictive maintenance; Conditional monitoring; Statistical Analysis; Signal processing; Hydraulic System; IoT; Sustainable Maintenance; Data vetenskap; Databehandling; Industriell tillverkning; System identifiering; Prediktivt underhåll; Tillståndsövervakning; Statistisk analys; Signal behandling;

   Sammanfattning : The recharge is the focus of data analysis of the different situations with the integration of the system and development of the two-stage 2/2 proportional cartridge valve for the steel industry machine. Using the statistical analysis technique to visualize the valve signal data behavior identify the accuracy of the machine data and apply the statistical feature extracting model using classification and clustering algorithms of real-time data analysis for the manufacturing. LÄS MER

3. 2. The Effectiveness of Word Focused Tasks. How Elaborate Processing Predicts Vocabulary Learning. A Literature Review.

   Uppsats för yrkesexamina på avancerad nivå, Göteborgs universitet / Lärarutbildningsnämnden

   Författare :Jane Ekenberg; Mirjeta Makolli; [2023-06-12]
   Nyckelord :English as a foreign language; involvement load hypothesis; technique feature analysis; vocabulary learning; vocabulary tasks.;

   Sammanfattning : L2 vocabulary learning is a sizeable challenge for all EFL students. Particularly, the lexical threshold for reading is a substantial learning feat requiring time and effort. Vocabulary research indicates that incidental learning alone is not sufficient for learners to achieve a functional EFL vocabulary. LÄS MER

4. 3. COMPARATIVE ANALYSIS OF MACHINE LEARNING LOAD FORECASTING TECHNIQUES

   Magister-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

   Författare :Humphry Takang Bate; [2023]
   Nyckelord :;

   Sammanfattning : Load forecasting plays a critical role in energy management, and power systems, enabling efficient resource allocation, improved grid stability, and effective energy planning and distribution. Without accurate very short term load forecasting, utility management companies face uncertain load patterns, unrealistic prices, and poor infrastructure planning. LÄS MER

5. 4. The Tale of Two Techniques - The comparative accuracy of machine learning and statistical techniques in predicting corporate bankruptcy for Swedish industrial firms

   D-uppsats, Handelshögskolan i Stockholm/Institutionen för redovisning och finansiering

   Författare :Edvin Lindhout; Hampus Ljunglöf; [2023]
   Nyckelord :Bankruptcy prediction; Machine learning; XGBoost; Probit analysis; Swedish firms;

   Sammanfattning : Bankruptcy prediction has long been an important area of study, yet the evolution of these predictive models in the context of modern machine learning techniques remains underexplored. Our thesis addresses this by comparing the effectiveness of probit analysis - a time-tested statistical approach - with XGBoost - a new-era machine learning technique - in predicting corporate bankruptcy among Swedish firms. LÄS MER

7. 5. Beyond Traditional Tomography: X-ray Multi-projection Imaging for Additive Manufacturing

   Kandidat-uppsats, Lunds universitet/Synkrotronljusfysik; Lunds universitet/Fysiska institutionen

   Författare :Maria Esther Vilar Alvarez; [2023]
   Nyckelord :X-ray tomography; X-ray multiprojection-imaging; deep learning; additive manufacturing; synchrotron radiation; Physics and Astronomy;

   Sammanfattning : The main aim of this bachelor thesis is to push the limits of 3D X-ray imaging by studying the minimum number of projections required to retrieve high-quality reconstructions for additive manufacturing processes. This project first focuses on understanding how X-ray tomography works, by reconstructing additive manufacturing data already obtained (from PSI, TOMCAT beamline) using two standard reconstruction algorithms, GRIDREC and SIRT. LÄS MER