Stride prediction is a nonignorable part of value prediction. Most hybrid predictors cannot eliminate this pattern. Existing stride predictors can handle the regular stride pattern, but it is hard to fit well with the interval stride pattern. To deal with it, we introduce the notion of Stride Equality Prediction (SEP), which predicts the stride feature of the current instruction is equal to that of the last committed same instruction. SEP can deal well with interval-style stride patterns, which always perform a constant stride during an interval, although there may be different endpoints and strides in different intervals. SEP predicts the value of stride equality instructions from the last committed occurrence of the same instruction and the number of the same instruction in the instruction window. Evaluation results show that SEP is effective in stride value prediction. It outperforms the Enhanced Stride predictor for 5.3% and state-of-art computational predictor Context-based Computational Value TAGE (CBC-VTAGE) for 1.5% on average. Moreover, by applying the SEP update condition, CBC-VTAGE can obtain performance gain without extra cost.