Modeling and Simulations of Process and Interactions
CESERE provides analyses, modeling and simulations of environmental and social processes, timing, interactions and situation awareness from multi-actor perspective.
Analysis and modeling of additional aspects as interactions and timing criteria in addition to the process logic is important for capturing all essential elements of heterogeneous sophisticated processes in environment and communities/society. Multi-actor approach enables to construct models that represent relationships, trends, alternative scenarios and links between the components of a system.
Processes and Interactions Analysis
Analysis of processes and interactions is performed by representing all essential process flows, parameters, actors and their relationships. The process model for environment, communities and their interactions comprises all important process components, information flows and other parameters.
Capturing and Representing Timing Criteria and Dynamics
Capturing of timing criteria is important for most of real processes and systems that have interactions, dynamics and response that must be analysed.
Specialized model and analysis tools are used in CESERE for representing, analysis., modeling and simulation of process dynamics and behaviour.
Modeling Multiple Viewpoints and Concurrent Activities with Multi-Actor Approach
Usually it is not enough to represent only the process flow or add actors as passive elements of use cases. In most real systems including environmental systems and social systems the actors have significant freedom is details for acting their roles. Each variation in actual behaviour causes changes in systems interactions and expected outcome. Therefore, it is important to capture also likewise deviations in the behaviour of actors and possible causes for that. CESERE operates with models that enable to capture individual characteristics aspects of communities, groups, actors of environmental actors.
As a result, such models provide more precision and trustworthiness in understanding environmental and societal phenomena and prognosticating possible outcomes and alternative scenarios.