This paper attempts to develop a backpropagation neural network algorithm for fault detection and location in overhead transmission lines and high-speed protection system using terminal data. The suggested neural FL is trained using various available sets of data from a selected power system model and simulating distinct fault scenarios (fault location and fault types) and various power system data (source voltages, source capacities and time constant of source). Two ANN-based fault locators (FLs) termed as FL1 and FL2 are recommended for a correlative study of FL. The study is carried out with reference to travelling wave-based FL in order to determine which FL delivers greater performance. The result shows that the proposed ANN-based FL provides better results in locating the fault as compared to travelling wave-based FL. The result also indicates that the recommended ANN-based FL is capable of identifying and determining the different single line to ground fault with greater accuracy.