An accurate fault location estimation algorithm based on application of artificial neural networks (ANN) for the protection of double circuit transmission lines is presented. The proposed Artificial Neural Network (ANN) protection scheme uses fundamental components of three phase voltages and current signals of both the circuits to learn the hidden relationship in the input patterns. This method is adaptive to the variation of fault resistance, fault inception angle and fault location. The Simulation results show that all types of shunt faults can be correctly locatedunder varying system conditions. Large numbers of fault simulations using MATLAB/Simulink software has proved the accuracy and effectiveness of the proposed algorithm. Keywords: Fault location (FL); Double circuit transmission line; artificial neural networks (ANN). I.INTRODUCTION Double circuit transmission lines are being most widely used because it has increased the power transmission capability and reliability of the power system. Distance relays used for protection of transmission lines have problems of under-reach, over-reach and mal-operation due to high impedance faults. Further this problem of distance relay is compounded when the distance relays are used for protection of double circuit transmission lines due to mutual coupling effect between the parallel lines. All possible types of faults on double circuit transmission line should be detected, classified and located correctly. The fault location of double circuit lines becomes more difficult and complex than a single circuit line due to the effect of mutual coupling among the circuits. When the fault location algorithm developed for single circuit lines is directly used for double circuit lines, which is often the case in practice, the fault location estimation accuracy can't be guaranteed because of the mutual coupling effect. Therefore a dedicated fault location algorithm has to be developed for the double circuit transmission lines. In previous years, various fault location algorithms on double circuit transmission lines have been developed [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15]. Phase selection algorithm based on superimposed components for protection of double circuit transmission line was proposed in [1] and [2]. A faulted-phase selector based on superimposed sequence components combined with correlation theory was presented in [3]. A fault classifier based on fault-generated high-frequency noise and artificial neural networks was proposed in [4]. In [5] the wavelet transform was used to extract the characteristics of the transient signals to construct the phase selector. In [6] Wavelet fuzzy combined approach for fault classification of a series-compensated transmission linewas presented. The fault classification and faulted-phase selection based on the Initial current travelling wave was reported in [7]. In [8] and [9] the algorithm employs the faulted circuit and healthy circuit of two-parallel line as fault location model and fault type is identified usi...