A Novel Symbolic Type Neural Network Model- Application to River Flow Forecasting
نویسندگان
چکیده
— In this paper we introduce a new symbolic type neural tree network called symbolic function network (SFN) that is based on using elementary functions to model systems in a symbolic form. The proposed formulation permits feature selection, functional selection, and flexible structure. We applied this model on the River Flow forecasting problem. The results found to be superior in both fitness and sparsity.
منابع مشابه
Evaluation of the Neuro-Fuzzy and Hybrid Wavelet-Neural Models Efficiency in River Flow Forecasting (Case Study: Mohmmad Abad Watershed)
One of the most important issues in watersheds management is rainfall-runoff hydrological process forecasting. Using new models in this field can contribute to proper management and planning. In addition, river flow forecasting, especially in flood conditions, will allow authorities to reduce the risk of flood damage. Considering the importance of river flow forecasting in water resources ma...
متن کاملFlood Forecasting Using Artificial Neural Networks: an Application of Multi-Model Data Fusion technique
Floods are among the natural disasters that cause human hardship and economic loss. Establishing a viable flood forecasting and warning system for communities at risk can mitigate these adverse effects. However, establishing an accurate flood forecasting system is still challenging due to the lack of knowledge about the effective variables in forecasting. The present study has indicated that th...
متن کاملDaily river flow forecasting in a semi-arid region using twodatadriven
Rainfall-runoff relationship is very important in many fields of hydrology such as water supply and water resourcemanagement and there are many models in this field. Among these models, the Artificial Neural Network (ANN) wasfound suitable for processing rainfall-runoff and opened various approaches in hydrological modeling. In addition,ANNs are quick and flexible approaches which provide very ...
متن کامل"Technical Report" Performance Comparison of IHACRES Model and Artificial Neural Network to Predict the Flow of Sivand River
The accurate determination of river flow in watersheds without sufficient data is one of the major challenges in hydrology. In this regard, given the diversity of existing hydrological models, selection of an appropriate model requires evaluation of the performance of the hydrological models in each region. The objective of this study was to compare the performance of artificial neural network ...
متن کاملForecasting Gold Price Changes: Application of an Equipped Artificial Neural Network
The forecast of fluctuations and prices is the major concern in financial markets. Thus, developing an accurate and robust forecasting decision model is critically favorable to the investors. As gold has shown a special capability to smooth inflation fluctuations, governors use gold as a price controlling lever. Thus, more information about future gold price trends will help to make the firm de...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- CoRR
دوره abs/0808.1378 شماره
صفحات -
تاریخ انتشار 2008