System Dynamics Modelling and Simulation of the Malaysian Rice Value Chain: Effects of the Removal of Price Controls and an Import Monopoly on Rice Prices and Self-sufficiency Levels in Malaysia

2017 ◽  
Vol 35 (3) ◽  
pp. 248-264 ◽  
Author(s):  
Bonhee Chung
Keyword(s):  
System Dynamics ◽  
Value Chain ◽  
Modelling And Simulation ◽  
Price Controls ◽  
System Dynamics Modelling ◽  
Self Sufficiency ◽  
Rice Prices ◽  
Dynamics Modelling

scholarly journals Applications of system dynamics modelling to computer music

2000 ◽  
Vol 5 (3) ◽  
pp. 149-157 ◽  
Author(s):  
IAN WHALLEY
Keyword(s):  
System Dynamics ◽  
Computer Music ◽  
Music Composition ◽  
Modelling And Simulation ◽  
Simulation Tools ◽  
System Dynamics Modelling ◽  
Dynamics Modelling ◽  
Dynamic Shape

Based on a composer's psycho-acoustic imagination or response to music, system dynamics modelling and simulation tools can be used as a scoring device to map the structural dynamic shape of interest of computer music compositions. The tools can also be used as a generator of compositional ideas reflecting thematic juxtaposition and emotional flux in musical narratives. These techniques allow the modelling of everyday narratives to provide a structural/metaphorical means of music composition based on archetypes that are shared with wider audiences. The methods are outlined using two examples.

Integrating Systems Modelling and Data Science

2016 ◽  
Vol 5 (1) ◽  
pp. 1-16 ◽  
Author(s):  
Erik Pruyt
Keyword(s):  
Big Data ◽  
System Dynamics ◽  
Data Science ◽  
Modelling And Simulation ◽  
System Dynamics Modelling ◽  
The Future ◽  
Systems Modelling ◽  
Dynamics Modelling

Although System Dynamics modelling is sometimes referred to as data-poor modelling, it often is –or could be– applied in a data-rich manner. However, more can be done in the era of ‘big data'. Big data refers here to situations with much more available data than was until recently manageable. The field of data science makes big(ger) data manageable. This paper provides a perspective on the future of System Dynamics with a prominent place for bigger data and data science. It discusses different approaches for dealing with bigger data. It reviews methods, techniques and tools for dealing with bigger data in System Dynamics, and sheds light on the modelling phases for which data science is most useful. Finally, it provides several examples of current applications in which big data, data science, and System Dynamics modelling and simulation are being merged.

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