Artificial neural networks (ANNs) are computational intelligence techniques, which are used in many applications, such as disease diagnosis. The objective of this study was to evaluate two artificial neural networks created for the diagnosis of diseases in fish caused by protozoa and bacteria. As a classification system, ANNs are an important tool for decisionmaking in disease diagnosis. A back...

The application of artificial neural networks (ANNs) for prognostic and diagnostic classification in clinical medicine has become very popular. In particular, feed-forward neural networks have been used extensively, often accompanied by exaggerated statements of their potential. In this paper, the essentials of feed-forward neural networks and their statistical counterparts (that is, logistic r...

This paper presents a new model for predicting the compressive strength of steel-confined concrete on circular concrete filled steel tube (CCFST) stub columns under axial loading condition based on Artificial Neural Networks (ANNs) by using a large wide of experimental investigations. The input parameters were selected based on past studies such as outer diameter of column, compressive strength...

Accurate estimation of evaporation is important for design, planning and operation of water systems. In arid zones where water resources are scarce, the estimation of this loss becomes more interesting in the planning and management of irrigation practices. This paper investigates the ability of artificial neural networks (ANNs) technique to improve the accuracy of daily evaporation estimation....

BACKGROUND Artificial neural networks is one of pattern analyzer method which are rapidly applied on a bio-medical field. OBJECTIVE The aim of this research was to propose an appendicitis diagnosis system using artificial neural networks (ANNs). METHODS Data from 801 patients of the university hospital in Dongguk were used to construct artificial neural networks for diagnosing appendicitis ...

Neural networks, more accurately called Artificial Neural Networks (ANNs), are computational models that consist of a number of simple processing units that communicate by sending signals to one another over a large number of weighted connections. They were originally developed from the inspiration of human brains. In human brains, a biological neuron collects signals from other neurons through...

Trajectory tracking is an essential capability of robotics operation in industrial automation. In this article, an artificial neural controller is proposed to tackle trajectory-tracking problem of an autonomous ground vehicle (AGV). The controller is implemented based on fractional order proportional integral derivative (FOPID) control that was already designed in an earlier work. A non-holonom...

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...

estimate of sediment load is required in a wide spectrum of water resources engineering problems. the nonlinear nature of suspended sediment load series necessitates the utilization of nonlinear methods to simulate the suspended sediment load. in this study artificial neural networks (anns) are employed to estimate daily suspended sediment load. two different ann algorithms, multi layer percept...