Towards Liquid Models: An Evolutionary Modeling Approach

2016 ◽  
Author(s):  
Alexandra Mazak ◽  
Manuel Wimmer
Keyword(s):  
Evolutionary Modeling ◽  
Modeling Approach

An evolutionary modeling approach for designing a contractual REDD+ payment scheme

2017 ◽  
Vol 79 ◽  
pp. 276-285 ◽  
Author(s):  
Jichuan Sheng ◽  
You Wu ◽  
Mingyang Zhang ◽  
Zhuang Miao
Keyword(s):  
Evolutionary Modeling ◽  
Payment Scheme ◽  
Modeling Approach

Application of an Evolutionary Modeling Approach to Automotive Bumper System Design and Analysis

1998 ◽  
Author(s):  
Stephen C.-Y. Lu ◽  
Christine Ping Ge ◽  
Nanxin Wang
Keyword(s):  
System Design ◽  
Early Stage ◽  
Selection Procedure ◽  
Empirical Models ◽  
Evolutionary Modeling ◽  
Modeling Approach ◽  
Initial Application ◽  
Cost Constraints ◽  
Available Information ◽  
Bumper System

Abstract Both empirical and mechanistic models are needed to design complex engineering systems. Empirical models play a particularly important role in design especially at the early stage. Large amounts of information, in terms of prior knowledge and experimental data, are needed for statistical analysis and machine learning methods to build empirical models with high quality. However, in some engineering domains, such as vehicle bumper system design, information is very limited due to the time/cost constraints and unknown physics of the problem. Methods are needed to construct reliable empirical models with limited amounts of available information. An Evolutionary Modeling Approach (EMA) has been developed as a first attempt to address this problem. In this approach, empirical model construction is viewed as a multistage, iterative learning process, in which the inaccurate and/or incomplete models gradually evolve into more accurate ones through a heuristically guided data selection procedure. This paper describes the EMA methodology and its initial application to an automotive bumper design and analysis problem.

A closed-loop, ACT-R approach to modeling approach and landing with and without synthetic vision system (SVS) technology

2004 ◽  
Author(s):  
Michael D. Byrne ◽  
Alex Kirlik ◽  
Michael D. Fleetwood ◽  
David G. Huss ◽  
Alex Kosorukoff ◽  
...  
Keyword(s):  
Closed Loop ◽  
Vision System ◽  
Modeling Approach ◽  
Synthetic Vision
Sign in / Sign up

Export Citation Format

Share Document