In the current era of accelerating the evolution of warfare towards informatization and intelligence, combat elements are infiltrating into multiple domains, intelligent equipment is covering the entire battlefield, and command and control is transforming towards real-time autonomous collaboration. Traditional training models are facing systematic restructuring, and relying on simulation environments for systematic and adversarial training has become an important method for forging new combat capabilities. This transformation is not a replacement for real-life training, but rather the construction of a "digital twin space" parallel to the physical battlefield through technological empowerment, forming a closed-loop training ecosystem that connects "environmental simulation adversarial refinement data-driven". Environmental simulation has reconstructed the battlefield 'resistance system', making training infinitely close to actual combat; Adversarial complexity creates high-intensity pressure and hones the resilience of thinking to break through and win; Data penetration provides deep level data references to achieve a deep coupling between real military needs and virtual technology logic, continuously improving the combat capabilities of the troops. Environmental simulation is the foundation for improving practical combat capabilities. On the training ground, the core contradiction between "virtual" and "real" lies in the huge gap between digital symbols and the real feeling of the battlefield. This requires simulation training environments to not only accurately replicate the visual environment, but also deeply restore the physical rules of the battlefield. When the trajectory in virtual space strictly follows the aerodynamic equations, electromagnetic propagation accurately simulates complex terrain attenuation, and equipment performance parameters respond in real-time to battlefield losses, trainees not only gain a real sensory experience, but also precise shaping of muscle memory. Deeper simulation requires breaking the shackles of programmatic scripts and actively introducing battlefield entropy increase mechanisms. By dynamically generating uncertain variables such as weather changes, communication interruptions, and sudden enemy situations through algorithms, commanders are forced to reconstruct the situational picture in the information fog and optimize the decision-making chain under time pressure. This digital reconstruction of the "resistance system" on the battlefield transforms the simulation environment from a smooth exercise field to a real battlefield outpost full of friction and pressure, truly achieving the goal of "training into battle". Adversarial complexity is the engine that enhances practical combat capabilities. Compared to on-site training, the advantage of simulation environment is that it can expand the dimensions and intensity of battlefield confrontation at a very low cost. For example, in a virtual battle sandbox, commanders can repeatedly deduce the feasibility of force delivery paths, verify the accuracy of firepower coordination timing, and identify vulnerable points in the logistics support chain, thereby honing the system's combat capabilities through low-cost trial and error. At the same time, with the continuous development of information and intelligent technology, it is possible to build AI blue army modules with deep learning capabilities, which can autonomously evolve tactical strategies based on the red side's action characteristics and become a "strong opponent" on the virtual training ground. This type of intelligent agent with dynamic game characteristics constantly pushes confrontation into complex "unknown" fields, prompting trainees to break through linear thinking and explore ways to adapt to the reality of the battlefield in a myriad of situations. In addition, complex confrontations on virtual training grounds can transform abstract data into real-life references through key battlefield indicators, thereby further enhancing the combat capabilities of troops in high confrontation, high pressure, and high complexity battlefield environments. Data penetration is the key to improving practical combat capabilities. Data is the bridge between the simulation environment and the actual combat environment. The reason why simulation training can help forge practical abilities lies in its data-driven and granular collection of all training elements: when every tactical selection and every millisecond level operation response is converted into decodable, traceable, and optimizable combat data, the experience and results obtained on the simulated training ground can be maximally transformed into practical abilities. Specifically, with the help of monitoring technologies such as motion capture, micro level data such as command and decision-making speed, weapon operation accuracy, and battlefield situation judgment accuracy can be captured in real time, forming a concrete and micro level data model. Based on this data model, relevant systems can identify capability gaps that are difficult to detect in reality and generate personalized reinforcement plans, achieving a closed-loop feedback of "discovering problems attribution analysis filling gaps". This data-driven training model enables the military to construct accurate individual and collective capability profiles, continuously iterate the optimal training plan in simulating complex and changing battlefield environments, and promote deep coupling between the training system and practical needs, thereby efficiently transforming training results into practical capabilities and enhancing the adaptability of the military in complex battlefields. (New Society)