In the Artificial Intelligence field, two areas have attracted a lot of attention in the past years: Artificial Neural Networks (ANN’s) and Genetic Algorithms (GA). The artificial neural networks, by their capacity to learn non-linear relationships between an input and an output space have a lot of applications: modeling and controlling dynamic processes and systems, signal processing, pattern ...

The arguments against the death penalty in the United States have centered on due process and fairness. Since the death penalty is so rarely rendered and subsequently applied, it appears on the surface to be arbitrary. Considering the potential utility of determining whether or not a death row inmate is actually executed along with the promising behavior of Artifi cial Neural Networks (ANNs) as...

Artificial intelligence technology has rapidly developed; it has already fused into all walks of life. The paper applies artificial intelligence knowledge to make diagnosis and evaluation on China men table tennis players’ competition technical and tactics, the paper firstly briefly introduces artificial intelligence method and decision-making tree, rough set, artificial neural network, and the...

This paper surveys the recent trends in quantum computational intelligence. Initially we focus on Grover’s search algorithm and its extensions. Next we summarize the current research aimed at applying the search algorithm to create quantum Artificial Neural Networks and look at methods of improving the performance of our newly created quantum neural networks.

The pervasive potential of artificial intelligence techniques in business scenarios has gained momentum recently through the combination of traditional software engineering disciplines and cutting-edge computer science research areas such as neural networks or genetic algorithms. Following this approach, MORGANA is a platform to perform competence oriented personnel staffing in software project...

Planning is a subject of interest to the Artificial Intelligence community. Genetic algorithms, neural networks, and simulated annealing are heuristic search methods often used to solve complex optimization problems. In this paper, we have proposed a novel intelligence paradigm to solve planning problems. This paper extends the Artificial Immune System (AIS) approach by proposing a new methodol...

Graphical models have become a standard tool for representing complex probability models in statistics and artificial intelligence. In problems arising in artificial intelligence, it is useful to use the belief network formalism to represent uncertain relationships among variables in the domain, but it may not be possible to use a single, fixed belief network to encompass all problem instances....

In this study, a method based on using image processing and artificial neural network is introduced to determine pelt color and curl size of newborn lambs in Zandi sheep. The data was collected from 300 newborn lambs reared in the Zandi sheep breeding centre of Khojir, Tehran. Primarily, curl size and pelt color of new born lambs was recorded by experienced appraisers, and at the same time, sev...

In this study, we showed various approachs implemented in Artificial Neural Networks for network resources management and Internet congestion control. Through a training process, Neural Networks can determine nonlinear relationships in a data set by associating the corresponding outputs to input patterns. Therefore, the application of these networks to Traffic Engineering can help achieve its g...

The positioning of isolation valves on water distribution networks is a hard design issue in hydroinformatics. Hydraulic engineers usually solve it by way of genetic algorithms, which do not exploit the constrained structure of the problem. Several solving approaches, based on constrained optimisation, have been developed in Artificial Intelligence, and prove that this discipline can surely hav...