Simuleringsmetoder

91 metoder i denne familien.

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Agent-based cellular automataAgent-Based Cellular Automata (ABCA) is a hybrid simulation framework that integrates the local transition rules of cellular automata with the autonomous behavioral logic of agent-Agent-basert diskret-hendelsessimuleringAgent-based discrete-event simulation (AB-DES) is a hybrid modeling paradigm that couples autonomous agent behavior with an event-driven execution engine. It captures the decision-Agent-basert Markov-modellThe Agent-Based Markov Model (ABMM) is a hybrid simulation framework that embeds Markov chain state-transition logic inside individual autonomous agents. Each agent independently s Agent-basert mikrosimuleringAgent-based microsimulation (ABMS) merges traditional microsimulation's individual-level statistical tracking with agent-based modeling's behavioral rules and interaction mechanism Agent-basert modellering (ABM)Agent-based modeling (ABM) is a computational simulation method, formalized through the work of Thomas Schelling and Robert Axelrod in the 1970s–1990s, that simulates the behavior Agent-basert multi-objektiv optimeringAgent-based multi-objective optimization (ABMOO) embeds autonomous agents inside a simulation environment and evolves their behavior or parameters to simultaneously optimize two or

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This topic's most-referenced foundational methods, in the order they were developed — a place to start if you're new here.

Multimål-optimering1896 (concept); 1989–2002 (evolutionary algorithms era)by Vilfredo Pareto (concept); modern computational formulation by Goldberg and Deb et al.
Markov-modell1906by Andrei Markov
Markov Chain Monte Carlo (MCMC)1953 (Metropolis-Hastings); 1984 (Gibbs)by Metropolis et al. (1953); Gibbs sampler formalised by Geman & Geman (1984)
Diskrete hendelsesbaserte simuleringer (DES)1960s (formalized); modern computational form from 1970s onwardby Banks, Carson, Nelson & Nicol (textbook lineage); foundational work by Tocher & Conway (1960s)
Systemdynamikk1961by Jay W. Forrester
Analyse av politikkscenarier1967–1990sby Kahn, H. & Wiener, A. J. (seminal); adapted for policy by RAND Corporation and OECD
Agent-basert modellering (ABM)1970s–1990s (formalized as a field)by Thomas Schelling and Robert Axelrod (foundational contributions, 1970s–1990s)
Latin Hypercube Sampling1979

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Agent-based cellular automata Agent-basert diskret-hendelsessimulering Agent-basert Markov-modell Agent-basert mikrosimulering Agent-basert modellering (ABM)Agent-basert multi-objektiv optimering Agent-basert scenarioanalyse Agentbasert sensitivitetsanalyse Agentbasert systemdynamikk – hybrid simulering på flere nivåer Cellulære automater Deterministisk agent-basert modellering Deterministiske cellulære automater Deterministisk diskret hendelses-simulering Deterministisk Markov-modell Deterministisk mikrosimulering Deterministisk multi-objektiv optimering Deterministisk scenarioanalyse Deterministisk sensitivitetsanalyse Deterministisk systemdynamikk Digital tvilling-simulering Diskrete valgsimulering Diskrete hendelsesbaserte simuleringer (DES)Diskrete hendelsessystemsimulering Ensemble Kalman Filter Fraktalanalyse Geant4-simulering Global sensitivitetsanalyse Betydningssampling Ising modell Monte Carlo Latin Hypercube Sampling Longstaff-Schwartz-metoden Markov Chain Monte Carlo (MCMC)Markov-modell Mikrosimulering Monte Carlo nøytron- og partikkeltransport Monte Carlo variasjonsanalyse av prosesser Multi-objektiv agentbasert modellering Multi-Mål Celleautomater Multi-Objective Discrete-Event Simulation Multi-objective Markov Model Multimål-mikrosimulering Multimål-optimering Analyse av flere målsettinger i scenarier Følsomhetsanalyse for multi-objektive problemstillinger Systemdynamikk for flere mål Banemodell Monte Carlo Policy Scenario Agent-Based Modeling Analyse av politikkscenarier Policy Scenario Cellular Automata Policy Scenario Discrete-Event Simulation Policy Scenario Microsimulation Policy Scenario Monte Carlo Simulation Policy Scenario Multi-Objective Optimization Policy Scenario Sensitivity Analysis Policy Scenario System Dynamics Kvantemekanisk Monte Carlo Rekurrenskvantifiseringsanalyse (RQA)Robust Agent-Based Modeling Robust Discrete-Event Simulation Robust Markov-modell Robust mikrosimulering Robust multi-objektiv optimering Robust scenarioanalyse Robust sensitivitetsanalyse Sample Entropy Scenarioanalyse og Hva-hvis-simulering Selvorganisert kritikalitet Simuleringsassistert konfirmatorisk forskning Simuleringsassistert reguleringskart Simuleringsassistert hendelsestreetanalyse Simuleringsassistert feilmodus- og effektanalyse Simuleringsassistert feiltre-analyse Forskningsbasert hypotesetesting ved hjelp av simulering Simuleringsassistert prosesskapasitetsanalyse Simuleringsassistert kvantitativ innholdsanalyse Simuleringsassistert pålitelighetsanalyse Simuleringsassistert statistisk prosesskontroll Simuleringsassistert trendforskning Stokastiske cellulære automater Stokastiske differensialligninger (SDE-er)Stokastisk diskret-hendelsessimulering Stokastisk Markov-modell Stokastisk mikrosimulering Stokastisk multi-objektiv optimering Stokastisk scenarioanalyse Stokastisk sensitivitetsanalyse Stokastisk systemdynamikk – Probabilistisk lager-strøm-simulering Systemdynamikk Value at Risk (VaR)Teknikker for variansreduksjon for Monte Carlo-simulering Vegas Monte Carlo