More than half of the energy sources in China are provided by combustion of coal from thermal power stations. By lowering the risk of excavating coal mines, we can decrease the price of the energy. This paper stresses the danger of coal mine gas explosions and constructs a gas explosion risk prediction system based on standard Hypo-Variance by using Brain Storms Optimization implemented with MATLAB simulation software. Hypo-Variance is the new concept built on the basis of Gauss Variance and can be used to make more precise risk assessments. By analyzing the multiple connections among gas density, temperature, humidity, pressure, air velocity, we can predict the trend of the gas event and propose the most safely timed schedule: operating three shifts in a day starting from a particular hour right after the gas peaking is over.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.