Sökning: "machine learning approaches"
Visar resultat 1 - 5 av 480 uppsatser innehållade orden machine learning approaches.
1. Data analytics and machine learning for railway track degradation: Using Bothnia Line track measurements for maintenance forecasting
Master-uppsats, KTH/Väg- och spårfordon samt konceptuell fordonsdesignSammanfattning : In this paper, a statistical method is developed to improve predictive maintenance on railway track. The problem tackled is being able to predict when the next maintenance event should take place to guarantee a certain track quality class. LÄS MER
2. Evaluation of Deep Q-Learning Applied to City Environment Autonomous Driving
Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Signaler och systemSammanfattning : This project’s goal was to assess both the challenges of implementing the Deep Q-Learning algorithm to create an autonomous car in the CARLA simulator, and the driving performance of the resulting model. An agent was trained to follow waypoints based on two main approaches. LÄS MER
3. Time Series Forecasting on Database Storage
Kandidat-uppsats, Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)Sammanfattning : Time Series Forecasting has become vital in various industries ranging from weather forecasting to business forecasting. There is a need to research database storage solutions for companies in order to optimize resource allocation, enhance decision making process and enable predictive data storage maintenance. LÄS MER
4. LP_MQTT - A Low-Power IoT Messaging Protocol Based on MQTT Standard
Master-uppsats, Högskolan i Halmstad/Akademin för informationsteknologiSammanfattning : In the Internet of Things (IoT) era, the MQTT Protocol played a bigpart in increasing the flow of uninterrupted communication betweenconnected devices. With its functioning being on the publish/subscribe messaging system and having a central broker framework, MQTTconsidering its lightweight functionality, played a very vital role inIoT connectivity. LÄS MER
5. Machine learning for molecular property prediction and drug safety
Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknikSammanfattning : Utilizing machine learning methods for the prediction of acid dissociation (pKa ) values of compounds holds great significance, as pKa is an important parameter, optimized frequently in drug discovery. Accurate prediction of pKa values could potentially provide valuable insights on other molecular properties and thereby support compound design. LÄS MER