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Visar resultat 1 - 5 av 269 uppsatser som matchar ovanstående sökkriterier.

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. Android Malware Detection Using Machine Learning

   Kandidat-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

   Författare :Rahul Sai Kesani; [2024]
   Nyckelord :Malware; Machine Learning; Random Forest; Sequential Neural Network.;

   Sammanfattning : Background. The Android smartphone, with its wide range of uses and excellent performance, has attracted numerous users. Still, this domination of the Android platform also has motivated the attackers to develop malware. The traditional methodology which detects the malware based on the signature is unfit to discover unknown applications. LÄS MER

5. 4. Automation of manual tasks at Statistics Sweden : Supervised machine learning as proof-of-concept

   Master-uppsats, Uppsala universitet/Institutionen för informationsteknologi

   Författare :Simon Godskesen; [2024]
   Nyckelord :;

   Sammanfattning : Supervised machine learning is used to create a proof-of-concept for automation of manual tasks for Statistics Sweden. The goal of the first part is to classify occupations with an SSYK code using descriptions entered by the employee, the education level of the employee, and their industry. LÄS MER

7. 5. Predicting Counter-Strike Matches using Machine Learning Models

   Kandidat-uppsats, Lunds universitet/Statistiska institutionen

   Författare :Erik Broms; William Nordansjö; [2024]
   Nyckelord :Mathematics and Statistics;

   Sammanfattning : Sports betting is a widespread industry where predictive modeling play a big role. The goal of this thesis is to explore the possibilities of machine learning within the realm of e-sport prediction. The data used for this thesis is publicly available data was recorded over a three year period. LÄS MER