Special Issue on Monte Carlo Methods and Applications

Monte Carlo method is the method of constructing probabilistic models for real processes to estimate certain average characteristics, such as mathematical expectations, variances and covariance. Many real-world data analysis tasks involve estimating unknown quantities from some given observations. Monte Carlo methods offer some of the most powerful approaches to computation. It is widely applied in the fields of physical sciences, engineering, weather forecasting, computational biology, computer sciences and economics.   

In this special issue, we intend to invite front-line researchers and authors to submit original research and review articles on exploring Monte Carlo methods and applications. Potential topics include, but are not limited to:

• Monte Carlo and random numbers
• Monte Carlo simulation and optimization
• Monte Carlo methods
• Conditional Monte Carlo
• Applications

Authors should read over the journal’s For Authors carefully before submission. Prospective authors should submit an electronic copy of their complete manuscript through the journal’s Paper Submission System.

Please kindly specify the “Special Issue” under your manuscript title. The research field “Special Issue - Monte Carlo Methods and Applications” should be selected during your submission.

Special Issue timetable:

Guest Editor:

For further questions or inquiries

Please contact Editorial Assistant at

am@scirp.org