Biodegradation Prediction and Modelling for Decision Support

被引:3
|
作者
Nettleton, David [1 ]
Fernandez-Avila, Cristina [1 ]
Sanchez-Esteva, Sara [1 ]
Verstichel, Steven [2 ]
Coltelli, Maria [3 ]
Marti-Soler, Helena [1 ]
Aliotta, Laura [3 ]
Gigante, Vito [3 ]
机构
[1] IRIS Technol Solut, Ctra Esplugues 39-41, Barcelona 08940, Spain
[2] OWS, Dok Noord 5, B-9000 Ghent, Belgium
[3] Univ Pisa, Dipartimento Ingn Civile & Ind, I-56122 Pisa Pi, Italy
基金
欧盟地平线“2020”;
关键词
Modelling; Simulation; Interpolation; Multi-agent System; Case based Reasoning; Time-Series; Biodegradation; Bioplastics; ARTIFICIAL-INTELLIGENCE;
D O I
10.5220/0011136200003274
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper we describe the functionality of a decision support modelling approach to select appropriate biomaterial blends depending on their mechanical/chemical properties on the one hand, and their biodegradation behaviour, on the other. Firstly, a Case Based Reasoning (CBR) approach is applied to predict expected biodegradation behaviour over time, based on historical examples and using a weighted distance metric on the material properties in order to calculate the trend curve of the new case. Secondly, a Multi Agent System (MAS) is applied to dynamically simulate the biodegradation curve, in which the two main agents, bacteria and plastic, interact to reproduce the biodegradation kinetics over time. The results of the interpolation are very promising with a good approximation to the real curve time series and % biodegradation, and the Multi-Agent System successfully simulates the different trend curves over time. The system has been confirmed as useful by materials expert end-users, who participated in the project, in order to evaluate a priori new blends "in silico", and identify and select the most promising, before conducting the long duration biodegradation experiments in the real environment.
引用
收藏
页码:26 / 35
页数:10
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