Sökning: "prediction by regression"

Visar resultat 1 - 5 av 399 uppsatser innehållade orden prediction by regression.

1. 1. Station-level demand prediction in bike-sharing systems through machine learning and deep learning methods

   Master-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

   Författare :Nikolaos Staikos; [2024]
   Nyckelord :Physical Geography; Ecosystem Analysis; Bike-sharing demand; Machine learning; Deep learning; Spatial regression; Graph Convolutional Neural Network; Multiple Linear Regression; Multilayer Perceptron Regressor; Support Vector Machine; Random Forest Regressor; Urban environment; Micro-mobility; Station planning; Geomatics; Earth and Environmental Sciences;

   Sammanfattning : Public Bike-Sharing systems have been employed in many cities around the globe. Shared bikes are an efficient and convenient means of transportation in advanced societies. Nonetheless, station planning and local bike-sharing network effectiveness can be challenging. LÄS MER

3. 2. ML implementation for analyzing and estimating product prices

   Kandidat-uppsats, Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)

   Författare :Abel Getachew Kenea; Gabriel Fagerslett; [2024]
   Nyckelord :Machine Learning; ML; Regression; Deep Learning; Artificial Neural Network; ANN; TensorFlow; ScikitLearn; CUDA; cuDNN; Estimation; Prediction; AI; Artificial Intelligence; Price Tracking; Price Logging; Price Estimation; Supervised Learning; Random Forest; Decision Trees; Batch Learning; Hyperparameter Tuning; Linear Regression; Multiple Linear Regression; Maskininlärning; Djup lärning; Artificiellt Neuralt Nätverk; Regression; TensorFlow; SciktLearn; ML; ANN; Estimation; Uppskattning; CUDA; cuDNN; AI; Artificiell Intelligens; pris loggning; pris estimation; prisspårning; Batchinlärning; Hyperparameterjustering; Linjär Regression; Multipel Linjär Regression; Supervised Learning; Random Forest; Decision Trees;

   Sammanfattning : Efficient price management is crucial for companies with many different products to keep track of, leading to the common practice of price logging. Today, these prices are often adjusted manually, but setting prices manually can be labor-intensive and prone to human error. LÄS MER

4. 3. 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

5. 4. Machine Learning Prediction of Enzymes’ Optimal Catalytic Temperatures

   Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

   Författare :Camille Finlinson Porter; [2023-03-22]
   Nyckelord :enzyme; protein; amino acid; protein structure; optimal catalytic temperature;

   Sammanfattning : Enzymes that have been genetically engineered to withstand high temperatures are used by industry to make products with less waste and pollution. Different features of protein structure affect the optimal catalytic temperature ("topt") at which enzymes catalyze reactions most efficiently. LÄS MER

7. 5. Predicting Patent Data using Wavelet Regression and Bayesian Machine Learning

   Master-uppsats, KTH/Matematik (Avd.)

   Författare :Mattias Martinsen; [2023]
   Nyckelord :Wavelet; Regression; Bayesian network; Prediction; Patent; Machine Learning; Wavelet; Regression; Bayesiskt nätverk; Predicering; Patent; Maskininlärning;

   Sammanfattning : Patents are a fundamental part of scientific and engineering work, ensuringprotection of inventions owned by individuals or organizations. Patents areusually made public 18 months after being filed to a patent office, whichmeans that current publicly available patent data only provides informationabout the past. LÄS MER