Design of an Artificial-Neural-Network-Based
نویسندگان
چکیده
This paper analyzes a serious limitation of existing metacomputing directory service of Globus project that the existing metacomputing directory service doesn’t support application-oriented queries, and then designs an artificial-neural-network-based GRC (grid resources classifier) to eliminate this limitation. This classifier extends the metacomputing directory service by classifying grid resources into application-oriented categories. The classification precision of this GRC can be continuously improved by selflearning. This kind of new metacomputing directory service will be compatible with the old ones. Thus, the practicability of metacomputing directory service will be improved.
منابع مشابه
Design, Development and Evaluation of an Orange Sorter Based on Machine Vision and Artificial Neural Network Techniques
ABSTRACT- The high production of orange fruit in Iran calls for quality sorting of this product as a requirement for entering global markets. This study was devoted to the development of an automatic fruit sorter based on size. The hardware consisted of two units. An image acquisition apparatus equipped with a camera, a robotic arm and controller circuits. The second unit consisted of a robotic...
متن کاملDevelopment of an in-cylinder processes model of a CVVT gasoline engine using artificial neural network
Today, employing model based design approach in powertrain development is being paid more attention. Precise, meanwhile fast to run models are required for applying model based techniques in powertrain control design and engine calibration. In this paper, an in-cylinder process model of a CVVT gasoline engine is developed to be employed in extended mean valve control oriented model and also mod...
متن کاملApplication of statistical techniques and artificial neural network to estimate force from sEMG signals
This paper presents an application of design of experiments techniques to determine the optimized parameters of artificial neural network (ANN), which are used to estimate force from Electromyogram (sEMG) signals. The accuracy of ANN model is highly dependent on the network parameters settings. There are plenty of algorithms that are used to obtain the optimal ANN setting. However, to the best ...
متن کاملDesign of an Intelligent Controller for Station Keeping, Attitude Control, and Path Tracking of a Quadrotor Using Recursive Neural Networks
During recent years there has been growing interest in unmanned aerial vehicles (UAVs). Moreover, the necessity to control and navigate these vehicles has attracted much attention from researchers in this field. This is mostly due to the fact that the interactions between turbulent airflows apply complex aerodynamic forces to the system. Since the dynamics of a quadrotor are non-linear and the ...
متن کاملPrediction of Engineered Cementitious Composite Material Properties Using Artificial Neural Network
Cement-based composite materials like Engineered Cementitious Composites (ECCs) are applicable in the strengthening of structures because of the high tensile strength and strain. Proper mix proportion, which has the best mechanical properties, is so essential in ECC design material to use in structural components. In this paper, after finding the best mix proportion based on uniaxial tensile st...
متن کاملPredictions of Tool Wear in Hard Turning of AISI4140 Steel through Artificial Neural Network, Fuzzy Logic and Regression Models
The tool wear is an unavoidable phenomenon when using coated carbide tools during hard turning of hardened steels. This work focuses on the prediction of tool wear using regression analysis and artificial neural network (ANN).The work piece taken into consideration is AISI4140 steel hardened to 47 HRC. The models are developed from the results of experiments, which are carried out based on De...
متن کامل