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@article{146671,
        author = {Rashika Rajput and Amit Gupta},
        title = {Fault Detection and Fault Classification In Transmission Line Using Neural Network},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {5},
        number = {1},
        pages = {748-760},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=146671},
        abstract = {Transmission lines, among the other electrical power framework segments, experience the ill effects of startling disappointments because of different arbitrary causes. These mistakes meddle with the unfaltering nature of the errand of the power structure. Right when unpredicted inadequacies happen protective systems are required to keep the causing of these lacks and shield the structure against the sporadic movement coming to fruition as a result of them. 
The objective of the paper is detecting and classifying the power system transmission line faults. Fault detection and fault classification have been achieved by using artificial neural networks in fitting tools. Feed forward networks have been employed along with back propagation algorithm for each of the three phases in the Fault location process. 
},
        keywords = {Transmission line blame recognition, blame arrangement, neural network, feed forward networks, Back propagation. },
        month = {},
        }