원문정보
초록
영어
Data analysis on environmental factors is crucial to aquaculture. Several significant parameters (temperature, pH and dissolved oxygen) and factors related to it are discussed in this paper. Data preparation including fixing some missing data and inaccurate records by non-linear function approaching in the first sampling process. Then the utilization of deterministic tracking theory is adopted for dynamic system analysis. Furthermore, time series analysis from different water layers based on this theory suits the real environment well, Radial Basis Function Neural Networks is well applied in tracking the parameters trend both globally and locally. The results provide effective references for systemic data analysis and control engineering.
목차
1. Introduction
2. Preliminary Results
2.1. Background of Aquaculture Conditions
2.2. Acquisition of Water Quality Data
2.3. Preparation of Water Quality Data
3. Dynamics Analysis of Aquaculture Water Quality Data
3.1. Dynamics Analysis of Temperature
3.2. Dynamics Analysis of Dissolved Oxygen
3.3. Dynamics Analysis of PH
4. Identification Based on Dynamics system and Artificial Intelligence
4.1. Dynamics Model of System Parameters
4.2. Radial Basis Function Neural Networks Identification
5. Conclusions & Future Works
References