نتایج جستجو برای: runoff model using an ann approach
تعداد نتایج: 8719474 فیلتر نتایج به سال:
This paper presents a new approach based on HMM/ANN hybrid for online signature verification. The hybrid HMM/ANN model is constructed by using a type of time delay Neural Networks as local probability estimators for an HMM, where a posterior probability of the model is worked out by the Viterbi algorithm, given an observation sequence. The proposed HMM/ANN hybrid has a strong discriminant abili...
artificial neural networks (ann) have shown to be a powerful tool for system modeling in a wide range of applications. the focus of this study is on neural network applications to data analysis in egg production. an ann model with two hidden layers, trained with a back propagation algorithm, successfully learned the relationship between the input (age of hen) and output (egg production) variabl...
runoff estimation resulted from precipitation is the basis of more study in various develop and exploit design from water resource, then its measure and calculation due to environmental bottlenecks, always have a plenty problem. as a result of the importance of output runoff estimation and flood volume in watershed for the sake of country integrated watershed management in this study tried to 9...
A novel application of a neuro-fuzzy computational technique in event-based rainfall-runoff modeling
Please cite this article in press as: Talei, A., et a Expert Systems with Applications (2010), doi:10.1 Intelligent computing tools based on fuzzy logic and Artificial Neural Networks (ANN) have been successfully applied in various problems with superior performances. A new approach of combining these two powerful AI tools, known as neuro-fuzzy systems, has increasingly attracted scientists in ...
Estimation of sediment loads in rivers is one of the most important, difficult components of sediment transport studies and river engineering. Accessing new methods that can be effective in this background are more important. In this research, we have used the artificial neural network (ANN) to optimize the results of the sediment rating curve (SRC) to predict the suspended sediment loads. For ...
Runoff create problems like erosion, flood and etc. Withe Assessment of the watershed we can identify the areas that have a potential for flood. And control operations taking only in those area. In this regard, identification areas with high potential for runoff for flood controls is great importance. Here, two major objectives have been considered: 1. evaluation Modclark model in simulation of...
This study compares the accuracy of the short-term rainfall forecasts obtained with time-series analysis techniques, using past rainfall depths as the only input information. The techniques proposed here are linear stochastic auto-regressive movingaverage (ARMA) models, artificial neural networks (ANN) and the non-parametric nearest-neighbours method. The rainfall forecasts obtained using the c...
the wepp physically model is able to dynamically simulate runoff and soil erosion using physical concepts of erosion and hydraulic of overland flow science considering plant growth, residue decomposition, winter process. determination of the capability of this model in runoff and erosion estimation in different range type with investigation the effects of management were the main objectives of ...
Prediction of watershed responses and simulation of runoff rate and volume are required for design purposes in most water resources projects. For this purpose, different hydrologic methods and events based on continuous hydrologic mathematical models are applied. In this research, a continuous hydrologic model, Stanford Watershed Model-IV (SWM-IV) is used for simulation of annual and monthly vo...
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