Sökning: "machine learning in R"

Visar resultat 1 - 5 av 112 uppsatser innehållade orden machine learning in R.

1. 1. An evaluation study of 3D imaging technology as a tool to estimate body weight and growth in dairy heifers

   Master-uppsats, SLU/Dept. of Animal Nutrition and Management

   Författare :Emelie Ahlberg; [2024]
   Nyckelord :body measurement; body weight; growth; heifer; three-dimensional imaging; young stock management;

   Sammanfattning : The aim of this thesis was to evaluate the use of a 3D camera as a tool to estimate body weight and growth in dairy heifers. Data collection lasted from October 2022 to January 2023 and was performed at the Swedish Livestock Research Centre in Uppsala, Sweden. LÄS MER

3. 2. A Qualitative Analysis of the Impact of Artificial Intelligence (AI) Adoption (Focusing on Machine Learning (ML)) on the Organizational Capabilities of the Telecom Industry in Sweden and Finland

   Magister-uppsats, Blekinge Tekniska Högskola/Institutionen för industriell ekonomi

   Författare :Neeraj Verma; [2023]
   Nyckelord :AI; R D; Industry 4.0; Qualitative Analysis; Innovation; Machine Learning; Business Performance; People and Culture; Process and Organization; Telecom; Technology.;

   Sammanfattning : The German government's "Industry 4.0" paradigm transforms technology application across domains using real-time data and connectivity. The telecom sector's reliance on digital, software-driven infrastructure for real-time data and connectivity is paramount. LÄS MER

4. 3. Mapping of Dependent Structural Responses on a Prestressed Concrete Bridge using Machine Learning Regression Analysis and Historical Data : A Comparison of Different Non-linear Regression Approaches

   L1-uppsats, Umeå universitet/Institutionen för datavetenskap

   Författare :Vedad Coric; [2023]
   Nyckelord :Prestressed Concrete Bridges; Structural health Monitoring; Machine Learning; Regression analysis; Infrastructure management;

   Sammanfattning : Prestressed concrete bridges are susceptible to deterioration over time which might significantly affect their capacity and overall performance. In previous decades, infrastructure owners have found that continuous monitoring of these assets is a valuable tool for their management as it facilitates the decision-making process regarding the intervention strategies required. LÄS MER

5. 4. Study of evaluation metrics while predicting the yield of lettuce plants in indoor farms using machine learning models

   Magister-uppsats, Högskolan i Skövde/Institutionen för informationsteknologi

   Författare :Divya Chedayan; Harry Geo Fernandez; [2023]
   Nyckelord :machine learning; lettuce yield prediction; Regression; SVR; RF; DNN; MAE; MSE; RMSE; R-squared; Adjusted R-squared;

   Sammanfattning : A key challenge for maximizing the world’s food supply is crop yield prediction. In this study, three machine models are used to predict the fresh weight (yield) of lettuce plants that are grown inside indoor farms hydroponically using the vertical farming infrastructure, namely, support vector regressor (SVR), random forest regressor (RFR), and deep neural network (DNN). LÄS MER

7. 5. Plant yield prediction in indoor farming using machine learning

   Magister-uppsats, Högskolan i Skövde/Institutionen för informationsteknologi

   Författare :Anjali Ashok; Mary Adesoba; [2023]
   Nyckelord :Yield prediction; Machine Learning; Hyperparameter tweaking; Support Vector Regression; Long Short-Term Memory; Artificial Neural Network;

   Sammanfattning : Agricultural industry has started to rely more on data driven approaches to improve productivity and utilize their resources effectively. This thesis project was carried out in collaboration with Ljusgårda AB, it explores plant yield prediction using machine learning models and hyperparameter tweaking. LÄS MER