Issues Related to Modelling and Parameter Settings of Models for Ecological Systems the Case of Distribution of Thorny Devil
- Resource Type
- Conference
- Authors
- Zhao, Yuting; Romero, Julio; Mohammadian, Masoud
- Source
- 2022 2nd International Conference on Innovative Practices in Technology and Management (ICIPTM) Innovative Practices in Technology and Management (ICIPTM), 2022 2nd International Conference on. 2:669-674 Feb, 2022
- Subject
- Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Fields, Waves and Electromagnetics
General Topics for Engineers
Geoscience
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Sensitivity
Biological system modeling
Decision making
Robustness
Data models
Australia
Optimization
species distribution modelling
Throny devil
model optimization
performance evaluation
configuration
- Language
Ecological modelling is a kind of important framework applied in environmental protection decision-making and strategies generation. The data sets used for ecological systems are complex and mega, and the elements to affect modelling are multiple and complex. Optimizing ecological species modelling is difficult. Configuration selection is one step in ecological modelling, which might improve models. Researchers need to understand the importance of configuration selection, which require more investigation in this area. The purpose of this paper is to advance Thorny Devil distribution modelling by evaluating and providing several modelling techniques with robustness criteria operation framework to improve the modelling of Thorny Devil distribution in Australia. This paper provides the results of several models for Thorny Devil distribution models and compares the results of these models. It also discusses which models would be more suitable for a field-based implementation, based on the parameters set. It also provides more references for configuration selection strategies.