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Generalized versus non-generalized neural network model for multi-lead inflow forecasting at Aswan High Dam
non-generalized neural network model multi-lead inflow
2011/3/15
Artificial neural networks (ANN) have been found efficient, particularly in problems where characteristics of the processes are stochastic and difficult to describe using explicit mathematical models....
We present a network model in which words over a specific alphabet, called {\it structures}, are associated to each node and undirected edges are added depending on some distance between different st...
Assessment of earthquake-triggered landslide susceptibility in El Salvador based on an Artificial Neural Network model
Assessment earthquake-triggered landslide susceptibility El Salvador based Artificial Neural Network model
2010/10/20
This paper presents an approach for assessing earthquake-triggered landslide susceptibility using artificial neural networks (ANNs). The computational method used for the training process is a back-pr...
Continuous-time quantum walks on the threshold network model
quantum walks threshold network model
2010/3/10
It is well known that many real world networks have the power-law degree distribution (scale-free property). However there are no rigorous results for continuous-time quantum walks on such realistic g...
Total ozone time series analysis:a neural network model approach
Total ozone time series analysis neural network model approach
2009/11/11
This work is focused on the application of neural network based models to the analysis of total ozone (TO) time series. Processes that affect total ozone are extremely non linear, especially at the co...
Watershed Bounded Network Model (WBNM) for Runoff Prediction of Large Basins
Watershed Bounded Network Model Runoff Prediction Large Basins
2009/10/28
Applicability of a nonlinear version of the watershed bounded network model
(WBNM) for large basins namely Shellbyville (1,246 km2), Columbia (3,129
km2), Centreville (5,304 kmz) and Hurricane Mills...
An artificial neural network model for rainfall forecasting in Bangkok, Thailand
network model rainfall forecasting Thailand
2009/9/11
This paper presents a new approach using an Artificial Neural Network technique to improve rainfall forecast performance. A real world case study was set up in Bangkok; 4 years of hourly data from 75 ...
A weighted network model based on the preferential selection of edges
Weighted networks Strength distribution Weight distribution
2010/9/15
A model for the growth of weighted networks is proposed. The model is based on the edge preferential selection. By the master equation approach, the distributions of strength, weight and degree are pr...
An Adaptive Neural Network Model for Nonlinear Programming Problems
adaptive neural network canonical neural network
2007/12/11
In this paper a canonicalneural network with adaptively changing synaptic weights and activation function parameters is presented to solve general nonlinear programming problems. The basic part of the...
A neural network model for short term river flow prediction
neural network model short term river flow prediction
2009/12/29
This paper presents a model using rain gauge and weather radar data to predict the runoff of a small alpine catchment in Austria. The gapless spatial coverage of the radar is important to detect small...