Sökning: "Agent Based Modelling"
Visar resultat 1 - 5 av 39 uppsatser innehållade orden Agent Based Modelling.
1. Understanding User Behaviour in a Circular Transport System : From personal choices to societal patterns
Master-uppsats, Stockholms universitet/Stockholm Resilience CentreSammanfattning : The Circular Economy is a growing research field and policy agenda. Yet, integrating the social dimensions of sustainability into the Circular Economy remains a challenge. The significance of reactions to an implemented Circular Economy is poorly understood. LÄS MER
2. Towards an open, automated, and reproducible synthetic population of Switzerland : A preparatory, modular pipeline for agent-based mobility simulations
Master-uppsats, KTH/Transport och systemanalysSammanfattning : This thesis explores the development of an automated re-synthesising tool, called EasySynth, to generate a Swiss synthetic population and travel diaries from publicly available data. The aim is to overcome the limitations of restricted-access real population data while maintaining control over anonymisation and statistical accuracy. LÄS MER
3. Development of a Graphical User Interface Prototype for an Ambulance Dispatchment Simulator
Kandidat-uppsats, Malmö universitet/Institutionen för datavetenskap och medieteknik (DVMT)Sammanfattning : This paper is based on Amouzad Mahdiraji’s research about an agent-based ambulance dispatchment simulator. A simulator which is currently not focused on visual user interfaces and usability. LÄS MER
4. The User Needs Of Agent-Based Modelling Experts : What Information Architecture reveals about ABM frameworks
Kandidat-uppsats, Malmö universitet/Fakulteten för teknik och samhälle (TS)Sammanfattning : Present-day Agent Based Modelling is used to simulate complex systems in which agents are explicitly heterogeneous. Researchers within the field of ABM have a set of tools at their disposal, yet little is known about the usability and learnability of these systems. LÄS MER
5. Machine Learning-Based Instruction Scheduling for a DSP Architecture Compiler : Instruction Scheduling using Deep Reinforcement Learning and Graph Convolutional Networks
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Instruction Scheduling is a back-end compiler optimisation technique that can provide significant performance gains. It refers to ordering instructions in a particular order to reduce latency for processors with instruction-level parallelism. LÄS MER