You are training a deep Recurrent Neural Network (RNN) for long-sequence time-series prediction, but the model is suffering from vanishing gradients, preventing it from learning long-term dependencies. Analyze the mathematical reasons behind this phenomenon in the context of backpropagation through time (BPTT) and propose three distinct architectural modifications (e.g., specific gating mechanisms or regularization techniques) to resolve it.