HARDWARE ASPECTS OF ARTIFICIAL NEURAL NETWORK AND ITS APPLICATIONS
Published In: 1ST INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTER, ELECTRONICS AND ELECTRICAL ENGINEERING
Author(s): MARIA JAMAL , SAYED A IMAM
Abstract: Artificial Neural Networks became a common solution for a wide variety of problems in many fields, such as control and pattern recognition to name but a few. Many solutions found in these and other Artificial Neural Network fields have reached a hardware implementation phase, either commercial or with prototypes. The most frequent solution for the implementation of Artificial Neural Networks consists of training and implementing the Artificial Neural Networks within a computer. In this paper we discussed the hardware aspects of ANN and its applications in various field.
- Publication Date: 12-Mar-2012
- DOI: 10.15224/978-981-07-1847-3-979
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OPTIMAL PLACEMENT METHODS OF DISTRIBUTED GENERATION: A REVIEW
Published In: 1ST INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTER, ELECTRONICS AND ELECTRICAL ENGINEERING
Author(s): JITENDRA SINGH KUNTAL , O.P.RAHI , VAIBHAV KUMAR GUPTA , VIVEK KUMAR SHRIVASTAVA , POONAM GUPTA
Abstract: Distributed Generation (DG) has been growing rapidly in power systems due to their potential solution for issues, like the deregulation in power system, to meet the power demand and the shortage of transmission capacities. Improper allocation of DG sources in power system would not only lead to increase power or energy losses, but can also jeopardize the system operation. The optimal placement of DG is necessary for the maximization of reliability and stability in power system. There are several research studies to solve DG placement problem by various objectives and their imposed constraints. However, the methodical principle for this subject is still an obscure problem. This paper presents an overview and general backgrounds of research and development in the field of different solution methods for optimal placement of DG found in the literature .This paper has reviewed some of the most popular methods including analytical technique, optimal power flow methods (OPF) and evolutionary
- Publication Date: 12-Mar-2012
- DOI: 10.15224/978-981-07-1847-3-985
- Views: 0
- Downloads: 0