Sökning: "Master scheduling"
Visar resultat 1 - 5 av 73 uppsatser innehållade orden Master scheduling.
1. Sensorless Hybrid Field-Oriented Control Two-Phase Stepper Motor Driver
Master-uppsats, Linköpings universitet/ReglerteknikSammanfattning : Hybrid stepper motors are small electrical motors with high torque production, compared with other electrical motors of the same size. Hybrid stepper motors are reliable in open-loop systems, in Sinusoidal mode, but with a drawback of high power consumption. LÄS MER
2. Simultaneous scheduling of railway maintenance and trains : Modelling and solving train interactions close to a maintenance operation
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Rail transport plays a key role in the mobility of passengers and goods. It is expected to grow the decarbonization of society. In that context, it is important to use the railway network efficiently, and jointly planning trains and network maintenance allows for better use of resources. LÄS MER
3. Hur ter sig teknikämnet i en slöjdsal?
Uppsats för yrkesexamina på avancerad nivå, KTH/LärandeSammanfattning : I detta examensarbete undersöks hur teknikämnet ter sig när det undervisas i en slöjdsal sett utifrån aktörerna elever, lärare och Skolverket. Följande frågeställningar har formulerats inom ramen för denna studie:1. Hur framträder teknikämnet hos elever och hos lärare när undervisningen sker i en slöjdsal? 2. LÄS MER
4. CHECK this out : Designing a resource planning feature into an existing accounting system
Uppsats för yrkesexamina på avancerad nivå, Luleå tekniska universitet/Institutionen för ekonomi, teknik, konst och samhälleSammanfattning : Oh My is a design and brand agency that has been developing CHECK, an accounting, billing, and time reporting system. CHECK has been developed to ease the billing and accounting process by making a front-shell system that is easier to use than the existing back-end economic system (Fortnox). LÄS MER
5. Deep Reinforcement Learning and Simulation for the Optimization of Production Systems
Master-uppsats, Uppsala universitet/Institutionen för informationsteknologiSammanfattning : The main objective of this master thesis project is to use the deep reinforcement learning (DRL) and simulation method for optimization of production systems. In this project, the Deep Q-learning Networks (DQN) algorithm is first used to optimize seven decision variables in Averill Law’s production system to find the best profit, with 99. LÄS MER