# A Comprehensive Review of Mechanisms, Predictive Techniques, and Control Strategies of Rockburst
## 7 Conclusions  
The failure of rock masses is a major concern in underground excavation. As the depth of excavation increases, so does the likelihood of rock mass failure. Excavation increases tangential stress and decreases radial stress, leading to rockbursts as a common failure process in brittle and hard rock. In underground excavations, spalling and slabbing forms of rockburst are frequently encountered. There have been extensive efforts to understand the causes of rockbursts and how to control them under high in-situ stress. A comprehensive review of research conducted between 1965 and 2021 on the use of various methods to predict rockbursts in underground engineering has been conducted. This review covers elaborate and simplified engineering empirical criteria or graph methods, numerical simulation and physics model tests, mathematical algorithms models, artificial intelligence and support vector machines, and is organized based on the approach type, source of data sets and variables used, and the comparative performance of strategies in terms of prediction accuracy. The failure of rock masses during underground excavation is a major concern and becomes more prevalent as the depth of the excavation increases. The increased tangential stress and decreased radial stress resulting from excavation can lead to rockbursts as a primary failure process in brittle and hard rock. Research has been conducted to understand the causes and develop control methods for rockbursts under high in situ stress, and various approaches have been used, such as empirical criteria, numerical simulations, physical model tests, and artificial intelligence algorithms. Although these approaches have been widely accepted and used, there are still limitations due to the complexity of rockburst behavior. In-situ monitoring is an effective method for acquiring real-time parameters to evaluate and predict rockburst danger, using techniques such as microseismic monitoring, microgravity, infrared thermal imaging, and more. Numerical simulations and physical model tests are also effective, but the choice of the ideal model depends on the level of accuracy and data availability. Further research is necessary to develop a complete and unified understanding of rockburst mechanisms. The mechanisms of rockburst are a topic of numerous theories, yet there is no agreement on what constitutes rockburst. Its occurrence is affected by rock mass qualities and the overall stress condition of the system. The rigidity theory is limited in accurately describing the dynamic process and mechanisms of rockburst. The intensity and damage caused by rockbursts are influenced by factors such as seismic events, geology, geotechnical issues, and the type of mining activity, including the sequence, span, and rock support system used. The significance of effective rock support systems in preventing rockbursts is widely acknowledged. Despite extensive research, a unified hypothesis for rockburst mechanisms remains elusive. The intensity of rockbursts can vary greatly depending on the prediction model used. Empirical approaches rely on one or two stress indices, each with its own unique formula. Energy and stress approaches have shown to be effective in predicting rockbursts. The ideal model for rockburst prediction is determined by the available data and level of accuracy. Numerical and intelligent procedures can help solve many technical and scientific problems. To forecast rockbursts, researchers often use fuzzy mathematics, rough set theory, mathematical attribute theory, cloud theory, and grey systems theory. Some even employ machine learning techniques. For example, a fuzzy mathematics and neural network model with an improved BP algorithm has been developed for potential assessment. Seismic events can also provide insight into rockbursts and be used for prediction. The burst support design tool considers seismic events, ground motion, rock mass quality, and mining-induced pressures to enhance rockburst risk management.