In their seminal paper [1] McCulloch and Pitts have shown the strong relationship between finite automata and so-called McCullochPitts networks. Our goal is to extend this result to weighted automata. In other words, we want to integrate artificial neural networks and weighted automata. For this task, we introduce semiring artificial neural networks, that is, artificial neural networks which im...

In recent years, researches on reinforcement learning (RL) have focused on bridging the gap between adaptive optimal control and bio-inspired learning techniques. Neural network reinforcement learning (NNRL) is among the most popular algorithms in the RL framework. The advantage of using neural networks enables the RL to search for optimal policies more efficiently in several real-life applicat...

Modelling and forecasting Stock market is a challenging task for economists and engineers since it has a dynamic structure and nonlinear characteristic. This nonlinearity affects the efficiency of the price characteristics. Using an Artificial Neural Network (ANN) is a proper way to model this nonlinearity and it has been used successfully in one-step-ahead and multi-step-ahead prediction of di...

abstract accurate prediction of river flow is one of the most important factors in surface water recourses management especially during floods and drought periods. in fact deriving a proper method for flow forecasting is an important challenge in water resources management and engineering. although, during recent decades, some black box models based on artificial neural networks (ann), have bee...

the present investigation entails a procedure by which the surface tension and viscosity of liquids could be redicted.to this end, capillary experiments were performed for porous media by utilizing fifteen different liquids and powders. the time of capillary rise to a certain known height of each liquid in a particular powder was recorded. two artificial neural networks (anns) were designed and...

abstract process of evapotranspiration (eto) is a major component of the hydrologic cycle that its accurate estimation plays an important role to achieve sustainable development in water balance, irrigation system design and planning and management of water resources. being a function of different metrological parameters and their interactions, evapotranspiration is a complex, nonlinear phenome...

Since the early 1990s, artificial neural networks play an increasing role in the development of new biomedical systems. In United States, over last decades, the granted biomedical patents that explicitly refer to artificial neural networks in their title, abstract or key references amount to about 50% of the total number of granted biomedical patents with a significant element of computational ...

Since the early 1990s, artificial neural networks play an increasing role in the development of new biomedical systems. In United States, over last decades, the granted biomedical patents that explicitly refer to artificial neural networks in their title, abstract or key references amount to about 50% of the total number of granted biomedical patents with a significant element of computational ...

Artificial neural networks have been used to support applications across a variety of business and scientific disciplines during the past years. Artificial neural network applications are frequently viewed as black boxes which mystically determine complex patterns in data. Contrary to this popular view, neural network designers typically perform extensive knowledge engineering and incorporate a...

This paper focuses on a new kind of artificial neural networks – the Z-transform artificial neural networks (ZTANN). It is proposed to use the Z-transform instead of ordinary weights and a linear activation function of an artificial neuron. This extension allows to use artificial neural networks in new areas. The ordinary description of artificial neural networks is a special case of the descri...