A Review of Membrane Computing Models for Complex Ecosystems and a Case Study on a Complex Giant Panda System

Figure 7

How the difference occurs in the process of prediction by PDP models (dotted line to solid line). The changes of five-year time interval (2006–2010) deviation rates (2005 as the input); the changes of five-year (2009–2013) deviation rates (2008 as the input); the changes of five-year (2012–2016) deviation rates (2011 as the input); the changes of five-year (2015–2017) deviation rates (2014 as the input); the deviation trajectory generated by the prediction errors. Overlapping prediction parts, i.e., 2009–2010 {input 2005 (5.61% and 0.99%), 2008 (10.11% and 9.9%)}, 2012–2013 {input 2008 (14.41% and 6.98%), 2011 (10.11% and 9.48%)}, and 2015–2016{input 2011 (17.19% and 6.98%), 2014 (4.46% and 2.69%)}, indicate the input data of different years can predict different results for the same year. In this graph, “No value” means no deviation rate due to the lack of statistical data in reality.