abstract evapotranspiration as one of the important elements in agriculture has a considerable role in water resource management. therefore, using a more exact estimation method is an essential step of agricultural development, especially in arid semi-arid area. in this research, in order to exact estimate of garlic evapotranspiration using lysimeteric data, an artificial neural network (ann) m...

evaporation is one of the most important components of hydrologic cycle.accurate estimation of this parameter is used for studies such as water balance,irrigation system design, and water resource management. in order to estimate theevaporation, direct measurement methods or physical and empirical models can beused. using direct methods require installing meteorological stations andinstruments ...

Neural networks with external memories (NNEM),such as the Neural Turing Machine [1] and Memory Networks [2], have often been compared to the human hippocampus in their ability to maintain episodic information over long timescales [3]. But so far, these networks have only been trained on tasks requiring memory storage comparable to a few minutes, whereas the hippocampus stores information on the...

Studies were carried out on the localization and mapping of gas stations in the urban area of São Carlos city, for an environmental diagnosis related to soil, surface water and underground water contamination resulting from likely leaking in fuel underground storage tanks. Considering that a provision of legal restriction makes it possible that most of public areas are not located in gas statio...

Artificial neural networks and genetic algorithms derived from the corresponding simulation of biology, anatomy. The paper analyzes the advantages and the disadvantages of the artificial neural networks and genetic algorithms. The artificial neural networks and genetic algorithms to be combine in the prediction model. This method is used to predict traffic volume in a road, the accuracy of fore...

this paper investigates the forecasting gold coin futures contract price in iran mercantile exchange. this research has presented a hybrid model based on genetic fuzzy systems (gfs) and artificial neural network (ann) to forecast the gold futures contract, at first, we use stepwise regression analysis (sra) to determine factors which have most influence on stock prices. at the next stage we div...

this paper presents the application of three main artificial neural networks (anns) in damage detection of steel bridges. this method has the ability to indicate damage in structural elements due to a localized change of stiffness called damage zone. the changes in structural response is used to identify the states of structural damage. to circumvent the difficulty arising from the non-linear n...

Understanding the glassy nature of neural networks is pivotal both for theoretical and computational advances in Machine Learning Theoretical Artificial Intelligence. Keeping focus on dense associative Hebbian networks, purpose this paper two-fold: at first we develop rigorous mathematical approaches to address properly a statistical mechanical picture phenomenon {\em replica symmetry breaking}...

We address the problem of 3D rotation equivariance in convolutional neural networks. 3D rotations have been a challenging nuisance in 3D classification tasks requiring higher capacity and extended data augmentation in order to tackle it. We model 3D data with multivalued spherical functions and we propose a novel spherical convolutional network that implements exact convolutions on the sphere b...

We report on our continuing work on pedigree-based record linkage. In particular, we show how a structured neural network can be designed to learn weights across pieces of information and how the inherent skewness of the data can be reduced by filtering, or blocking, through a series of these networks. The results, both quantitative and qualitative, are encouraging.