abstract the study of natural disasters is one of the most important primary principles for the growth of developing cities and the development of infrastructures. to this end, evaluating geodynamic activities using morphological data is considered one of the most pivotal applied methods. in this study, it was tried to detect active faults in yazd province using desert studies and remote sensin...

Fault location and distance protection are essential smart grid technologies ensuring reliability of the power system. This paper describes an accurate algorithm for locating faults on double-circuit transmission lines. The proposed approach is capable of identifying the faulted circuit of a parallel transmission line by checking the estimated fault location and fault resistance. Voltage and cu...

The aim of this paper is to study communication in networks where nodes fail in a random dependent way. In order to capture fault dependencies, we introduce the neighborhood fault model, where damaging events, called spots, occur randomly and independently with probability p at nodes of a network, and cause faults in the given node and all of its neighbors. Faults at distance at most 2 become d...

We investigate the design of dynamic programming algorithms in unreliable memories, i.e., in the presence of faults that may arbitrarily corrupt memory locations during the algorithm execution. As a main result, we devise a general resilient framework that can be applied to all local dependency dynamic programming problems, where updates to entries in the auxiliary table are determined by the c...

rotating machines in particular induction electrical machines are important industry instruments. in manufacturing, electrical motors are exposed to many damages, and this causes stators and rotors not to work correctly. in this paper we addressed modal analysis and an intelligent method to detect motor load condition and also the stator faults such as turn-to-turn and coil-to-coil faults using...

This paper introduces fuzzy belief nets (FBN). The ability to invert arcs between nodes is key to solving belief nets. The inversion is accomplished by defining closeness measures which allow diagnostic reasoning from observed symptoms to cause of failures. The closeness measures are motivated by a Lukasiewicz operator which takes into account the distance from an observed symptom set to the mo...