Generic Artificial Neural Network Framework for Habitat Assessment and Prediction of Australian Stream Systems
نویسندگان
چکیده
The Stream Decision Support System (SDSS) is taking advantage of both supervised and nonsupervised artificial neural networks (ANNs) for stream assessment and prediction by an integrated approach. Non supervised ANNs were applied for patterning the natural variability in stream macroinvertebrate communities in Queensland. Supervised ANNs were developed for the prediction of the occurrence of stream macroinvertebrates in Victoria based on “clean-water” approach. Supervised ANNs were also applied for the prediction of taxonomic richness of native macrophytes and macroinvertebrates in the stream system of NSW by means of multi-layer perceptron ANN. The future development of the SDSS and its applicability for environmental management is discussed.
منابع مشابه
Stream Flow Prediction in Flood Plain by Using Artificial Neural Network (Case Study: Sepidroud Watershed)
In order to determine hydrological behavior and water management of Sepidroud River (North of Iran-Guilan) the present study has focused on stream flow prediction by using artificial neural network. Ten years observed inflow data (2000-2009) of Sepidroud River were selected; then these data have been forecasted by using neural network. Finally, predicted results are compared to the observed dat...
متن کاملThe Use of Fundamental Color Stimulus to Improve the Performance of Artificial Neural Network Color Match Prediction Systems
In the present investigation attempts were made for the first time to use the fundamental color stimulus as the input for a fixed optimized neural network match prediction system. Four sets of data having different origins (i.e. different substrate, different colorant sets and different dyeing procedures) were used to train and test the performance of the network. The results showed that th...
متن کاملApplication of Linear Regression and Artificial NeuralNetwork for Broiler Chicken Growth Performance Prediction
This study was conducted to investigate the prediction of growth performance using linear regression and artificial neural network (ANN) in broiler chicken. Artificial neural networks (ANNs) are powerful tools for modeling systems in a wide range of applications. The ANN model with a back propagation algorithm successfully learned the relationship between the inputs of metabolizable energy (kca...
متن کاملPrediction of Driver’s Accelerating Behavior in the Stop and Go Maneuvers Using Genetic Algorithm-Artificial Neural Network Hybrid Intelligence
Research on vehicle longitudinal control with a stop and go system is presently one of the most important topics in the field of intelligent transportation systems. The purpose of stop and go systems is to assist drivers for repeatedly accelerate and stop their vehicles in traffic jams. This system can improve the driving comfort, safety and reduce the danger of collisions and fuel consumption....
متن کاملHybrid Models Performance Assessment to Predict Flow of Gamasyab River
Awareness of the level of river flow and its fluctuations at different times is one of the significant factor to achieve sustainable development for water resource issues. Therefore, the present study two hybrid models, Wavelet- Adaptive Neural Fuzzy Interference System (WANFIS) and Wavelet- Artificial Neural Network (WANN) are used for flow prediction of Gamasyab River (Nahavand, Hamedan, Iran...
متن کامل