Sökning: "Genetic Algorithm optimisation"

Visar resultat 1 - 5 av 10 uppsatser innehållade orden Genetic Algorithm optimisation.

1. 1. Path Choice Estimation in Urban Rails : Asimulation based optimisation for frequency-based assignment model

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Alexander Adolfsson; [2022]
   Nyckelord :Black-Box Optimisation; Optimization; Simulation based optimisation; Transit Network; Automaton; Urban Transport; Public transportation; Black-Box optimering; Optimering; Simuleringsbaserad Optimering; Transportsystem; Automation; Local Transport; Kollektivtrafik;

   Sammanfattning : Transit system have a large importance in modern urban cities, with urban rail often acting as the central system with it efficient travel time and great capacity. As cities grow in population, so to does the usage of urban rail resulting in increased crowding on the platform and in the trains. LÄS MER

3. 2. Evaluation of Models and Optimisation Methods for Energy Minimisation of Drill Riggs

   Master-uppsats, Linköpings universitet/Fordonssystem

   Författare :Mohamed Faraj; Max Olsson; [2022]
   Nyckelord :Vehicle Propulsion Systems; Electrical powertrain; Modeling; Simulation; Deterministic dynamic programming; AMESim;

   Sammanfattning : There are many benefits from using electrical powertrains over diesel powertrains within the mining industries, where some of these benefits come from reducing the pollution within the mines and therefore improve the working environment as well as reduce the ventilation costs required from ventilating these pollution. It is also desired to optimise the use of the vehicle to increase the efficiency and reduce fuel consumption of the vehicle. LÄS MER

4. 3. Assessment of optimal suspension systems with regards to ride under different road profiles

   Master-uppsats, KTH/Fordonsdynamik

   Författare :Adithya Murali; Pratik Hindraj Vaje; [2021]
   Nyckelord :Ride comfort; Handling; Road profiles; ADAMS; Shaping filter method; Sinusoidal approximation method; Coherence; ISO 8608; Acceleration PSD s; Genetic Algorithm optimisation; ISO 2631.; åkkomfort; Kurvkörningsegenskaper; Vägprofiler; ADAMS; Formningsfiltermetod; Sinusformad approximationsmetod; Koherens; ISO 8608; Acceleration PSDs; Genetisk algoritmoptimering.;

   Sammanfattning : Passenger ride vibration comfort is a critical aspect to consider while developing any vehicle and there is a need to understand how the occupants would be affected when driving on different road profile roughness. Hence, road profile generation is critical as road profiles are used as inputs to simulation tools to investigate vehicle dynamic behaviour in depth. LÄS MER

5. 4. Periodical Maintenance Modelling and Optimisation Assuming Imperfect Preventive Maintenance and Perfect Corrective Maintenance

   Master-uppsats, KTH/Optimeringslära och systemteori

   Författare :Madeleine Engvall Birr; Lisette Lansryd; [2021]
   Nyckelord :Master Thesis; Maintenance Management; Maintenance Modelling; Imperfect PM; Perfect CM; Periodic Policy; Genetic Algorithms; Age Reduction; Masterexamensarbete; Underhållsarbete; Underhållsmodellering; Ofullständiga FU; Perfekta AU; Periodisk Planläggning; Genetiska Algoritmer; Åldersreduktion;

   Sammanfattning : In this paper, a periodic maintenance model is formulated assumingcontinuous monitoring, imperfect preventive maintenance (PM) and perfect correctivemaintenance (CM) using three decision variables, (I, N, Z). The model is derived in aninfinite horizon context where the mean cost per unit time is modelled. LÄS MER

7. 5. Subsampling Strategies for Bayesian Variable Selection and Model Averaging in GLM and BGNLM

   Master-uppsats, Stockholms universitet/Statistiska institutionen

   Författare :Jon Lachmann; [2021]
   Nyckelord :Bayesian model averaging; subsampling; GLM; BGNLM; IRLS; Optimisation;

   Sammanfattning : Bayesian Generalized Nonlinear Models (BGNLM) offer a flexible alternative to GLM while still providing better interpretability than machine learning techniques such as neural networks. In BGNLM, the methods of Bayesian Variable Selection and Model Averaging are applied in an extended GLM setting. LÄS MER