Sökning: "random analysis"

Visar resultat 1 - 5 av 835 uppsatser innehållade orden random analysis.

1. 1. Betesrestaureringens effekter på växtartrikedom och biologisk mångfald : -restaurering av betesmark på Hallands Väderö

   Kandidat-uppsats, Karlstads universitet/Avdelningen för biologi; Karlstads universitet/Fakulteten för hälsa, natur- och teknikvetenskap (from 2013)

   Författare :Rolfsdotter Söderberg Ylva; [2024]
   Nyckelord :pasture restoration; biodiversity; species richness; effective number of species; plants; plant species; number of species; clearing; pasture; betesrestaurering; biologisk mångfald; artrikedom; effektivt artantal; växter; växtarter; antal arter; artantal; hävd; betesmark; naturbetesmark;

   Sammanfattning : Abstract Pasture is a very species-rich but threatened nature type, and compared to 200 years ago, only five percent of natural pastures remain in Sweden. One way to try to save the biological diversity that pastures harbor is to restore overgrown land by clearing and reintroducing grazing animals. LÄS MER

3. 2. 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

4. 3. Land cover classification using machine-learning techniques applied to fused multi-modal satellite imagery and time series data

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

   Författare :Anastasia Sarelli; [2024]
   Nyckelord :Geography; GIS; Land Cover Classification; Landsat; Machine Learning; Earth and Environmental Sciences;

   Sammanfattning : Land cover classification is one of the most studied topics in the field of remote sensing, involving the use of data from satellite sensors to analyze and categorize different land surface types. There are numerous satellite products available, each offering different spatial, spectral, and temporal resolutions. LÄS MER

5. 4. Attack Strategies in Federated Learning for Regression Models : A Comparative Analysis with Classification Models

   Master-uppsats, Umeå universitet/Institutionen för datavetenskap

   Författare :Sofia Leksell; [2024]
   Nyckelord :Federated Learning; Adversarial Attacks; Regression; Classification;

   Sammanfattning : Federated Learning (FL) has emerged as a promising approach for decentralized model training across multiple devices, while still preserving data privacy. Previous research has predominantly concentrated on classification tasks in FL settings, leaving  a noticeable gap in FL research specifically for regression models. LÄS MER

7. 5. Exploring the Impact of Pseudo and Quasi Random Number Generators on Monte Carlo Integration of the Multivariate Normal Distribution

   Kandidat-uppsats, Lunds universitet/Statistiska institutionen

   Författare :Marcus Stolz; Jonathan Christopher; [2024]
   Nyckelord :Monte Carlo integration; Quasi monte carlo integration; Random number generation; Mathematics and Statistics;

   Sammanfattning : This thesis examines the effects of pseudo and quasi-random number generators on the accuracy and efficiency of Monte Carlo Integration in the case of the multivariate normal distribution. The study compares the performance of the Mersenne Twister (a pseudo-random number generator) with Sobol and Halton sequences (quasi-random number generators). LÄS MER