This research work investigates how to control the chaos in dissipative dynamical systems. To this aim, we have analyzed the novel systems: one is related to the variation in temperature caused by micro-organisms, and the other corresponds to the proliferation of cancer cells via interaction with healthy host cells and immune effector cells introduced in Kumar et al. [23]. To control the chaos between these two systems, we have developed the anti-synchronization technique based on neural networks which is capable to manage unknown nonlinearities by approximating it withi the time. Further, the effectiveness of the purposed scheme was assessed through numerical simulation and confirmed that anti-synchronisation conditions were rapidly achieved even with the presence of perturbation. This study emphasizes the impact for controlling the chaos by using neural network methods and to obtain the stability in dissipative biological and environmental systems.