In this paper, we present two different techniques to accelerate and approximate particle-based fluid simulations. The first technique identifies and employs larger time steps than dictated by the CFL condition. The second introduces the concept of approximation in the context of particle advection. For that, the fluid is segregated into active and inactive particles, and a significant amount of computation is saved on the passive particles. Using these two optimization techniques, our approach can achieve up to 7 times speed-up compared to a standard SPH method and it is compatible with other SPH improvement methods. We demonstrate the effectiveness of our method using up to one million particles and also compare it to standard SPH particle simulation visually and statistically.