To improve the analysis effect of e-sports competitions, this paper studies the intelligent analysis methods of e-sports, compares the advantages and disadvantages of various multi-classification methods, and innovatively designs a two-layer SVM classifier structure for four types of motor imagery EEG signals. Moreover, this paper uses the competition data set to test the classification accuracy of the designed double-layer SVM classifier structure and compares it with the DAG-SVM multi-classification method. The research results show that the e-sports competition analysis system based on the intelligent analysis system proposed in this paper has a good e-sports competition analysis effect, and has a good effect in e-sports competition prediction.

One of the important reasons for the repeated occurrence of the same type of accidents in the group company over the years is the insufficient utilization of accident resources. This paper introduces barrier theory and establishes an accident analysis method system based on barrier theory. Barrier theory changes the traditional accident analysis mode, and adjusts the object of accident analysis from consequence to barrier, which provides a new perspective for the analysis of accident law. This paper develops a HSE text semantic recognition model which can automatically extract the production operation link, production stage and type of failed barriers of the accidents from the accident investigation report, finds out the cause factors leading to the failures of these barriers and establishes a direct relationship with the HSE(Health, Safety and Environment) management system, in a way to find out some common laws of the accidents and reveal the defects and shortcomings in business management.

In order to improve the effect of e-sports training, this paper combines the intelligent gesture recognition technology to construct an e-sports training system and judges the training effect of players through the recognition of players’ gestures. Moreover, this paper studies the commonly used feature extraction algorithms and proposes an improved SLC-Harris feature extraction algorithm, and the feasibility of this algorithm is verified by the experimental results on the EUROC data set. In addition, this paper uses the KLT optical flow algorithm to track the extracted feature points and calculates the pure visual pose through epipolar geometry, triangulation, and PnP algorithms. The experimental research results show that the electronic economic training system based on intelligent gesture recognition proposed in this paper has certain effects.

A major safety accident will be triggered when the A-annular pressure value of high pressure, high productivity and high sulfur gas well exceeded the maximum allowable value. The A-annular pressure value of high pressure high productivity and high sulfur gas well once exceeded the allowable value will trigger a major safety accident. Therefore, this paper proposed a data mining based the gas well early warning strategy by analyzing the annular pressure mechanism and the change in the pattern of instantaneous gas volume, well temperature, and annular pressure in various conditions. To summarize, the law of gas well abnormal A-annular pressure is aimed at constructing a gas well safety warning rule for gas well stable production stage and shutdown period where the initial parameters setting in the early warning rule and adjustment optimization mechanism is also determined. Lastly, with the use of historical abnormal samples, the gas well early warning strategy bought up in this paper was verified. The example shown that compared with the traditional DCS system warning strategy, the gas well safety early warning strategy can identify the abnormal A-annular pressure phenomenon 82 h in advance thus achieving production safety management.