Wavelet and neuro-fuzzy conjunction model for predicting water table depth fluctuations
نویسندگان
چکیده
منابع مشابه
Comparison of genetic programming with neuro-fuzzy systems for predicting short-term water table depth fluctuations
This paper investigates the ability of genetic programming (GP) and adaptive neuro-fuzzy inference system (ANFIS) techniques for groundwater depth forecasting. Five different GP and ANFIS models comprising various combinations of water table depth values from two stations, Bondville and Perry, are developed to forecast one-, twoand three-day ahead water table depths. The root mean square errors...
متن کاملcomparison of three intelligence techniques for predicting water table depth fluctuations (case study: zarringol plain)
0
متن کاملA simple model for predicting water table fluctuations in a tidal marsh
[1] Wetland restoration efforts are ongoing in many urban estuaries. In this context the hydrologic characteristics of restored wetlands are of paramount importance since the spatially and temporally variable position of the water table and of soil saturation establishes the oxidation state of the substrate, which, in turn, affects the wetland’s biogeochemical composition and the biological com...
متن کاملAn Algorithmic Approach for Efficient Image Compression using Neuro-Wavelet Model and Fuzzy Vector Quantization Technique
Applications, which need to store large database and/or transmit digital images requiring high bit-rates over channels with limited bandwidth, have demanded improved image compression techniques. This paper describes practical and effective image compression system based on neuro-fuzzy model which combines the advantages of fuzzy vector quantization with neural network and wavelet transform. Th...
متن کاملA Learning Algorithm for Forecasting Adaptive Wavelet-neuro- Fuzzy Network
The architecture of forecasting adaptive wavelet-neuro-fuzzy-network and its learning algorithm for the solving of nonstationary processes forecasting tasks are proposed. The learning algorithm is optimal on rate of convergence and allows to tune both the synaptic weights and dilations and translations parameters of wavelet activation functions. The simulation of developed wavelet-neuro-fuzzy n...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Hydrology Research
سال: 2012
ISSN: 0029-1277,2224-7955
DOI: 10.2166/nh.2012.104b