Function Points is an important and well-accepted software size metric. However, it is absolutely essential to accurately calibrate Function Point (FP), whose aims are to fit specific software application, to reflect software industry trend, and to improve cost estimation. Neuro-Fuzzy is a technique that incorporates the learning ability from neural network and the ability to capture human know...

A new pilot model consisting of neural networks and supervisory fuzzy logic control is proposed to reveal a pilot’s control characteristics in the visual approach to landing. The model is constructed from real or simulated flight and can be used for pilot training or assesment.

Network sensors consist of sensor nodes in which every node covers a limited area. The most common use ofthese networks is in unreachable fields.Sink is a node that collects data from other nodes.One of the main challenges in these networks is the limitation of nodes battery (power supply). Therefore, the use oftopology control is required to decrease power consumption and increase network acce...

This paper focuses on the Genetic Algorithm learning paradigm applied to train the ANNs for balancing the cart-pole balancing system. The studied system is a control problem namely “cart-pole” problem. We will apply the unconventional techniques Artificial Neural Network, Genetic Algorithm and Fuzzy Logic to a classic control problem “cart-pole”. In this paper we have tried to train the Artific...

the functions employed in an estimation of costly measured soil properties from either widely available or more easily obtained basic soil properties are referred to as pedotransfer functions. to develop pedotransfer functions, one can use multivariate regression, neural networks and neuro-fuzzy models. to make a comparison among the mentioned models, 153 soil samples were collected from soils ...

This paper proposes the neural network solution to the indirect vector control of three phase induction motor including an adaptive neuro fuzzy controller. The basic equations and elements of the indirect vector control scheme are given. The proposed control scheme is realized by an adaptive neuro-fuzzy controller and two feed forward neural network. The neuro-fuzzy controller incorporates fuzz...

A fuzzy logic controller (FLC) is designed to maintain constant tension for tandem rolling mills. Envisioning fuzzy inference system as neural network and introducing tutor, backward propagation algorithm is used as self-organization technique for FLC to approach the best parameters under supervision. Simulation results exhibit the generalization and adaptivity of neuro-fuzzy controller in offl...

Computational intelligence paradigm covers several approaches for technical problems solving in an intelligence manner, such as artificial neural networks, fuzzy logic systems, evolutionary computation, etc. Each approach provides engineers and researchers with the smart and powerful tools to handle various real-life concerns. Even more powerful tools were designed at the joint of different com...

Three hybrid fuzzy control schemes for robotics applications are described. The rst scheme concentrates on a control architecture which incorporates fuzzy logic theory into the framework of behavior control for mobile robot navigation. The second scheme develops a two-level hierarchical fuzzy control structure for exible manipulators. It incorporates Genetic Algorithms (GA) in a learning scheme...