This two-volume set constitutes the refereed post-conference proceedings of the 12th International Conference on Simulation Tools and Techniques, SIMUTools 2020, held in Guiyang, China, in August 2020. Due to COVID-19 pandemic the conference was held virtually. The 125 revised full papers were carefully selected from 354 submissions. The papers focus on simulation methods, simulation techniques, simulation software, simulation performance, modeling formalisms, simulation verification and widely used frameworks.

This proceedings constitutes the refereed post-conference proceedings of the 13th International Conference on Simulation Tools and Techniques, SIMUTools 2021, held in November 2021. Due to COVID-19 pandemic the conference was held virtually. The 63 revised full papers were carefully selected from 143 submissions. The papers focus on new results in the field of system modeling and simulation, software simulation, communication networks’ modeling and analysis, AI system simulation and performance analysis, big data simulation analysis, addressing current and future trends in simulation techniques. They are grouped in thematic aspects on wireless communication, big data, modeling and simulation, deep learning, network simulation and life and medical sciences.

The design of communication systems has grown too complicated for the traditional design tools--mathematical analysis and laboratory breadboards. Enter the computer simulation, a powerful and versatile tool that is becoming essential for anyone who designs signal transmission or storage systems. This volume explains in detail how to use simulation programs as a software breadboard to analyze and evaluate the performance of data communications links. It describes the engineering principles of signal transmission and its simulation, explores programming issues, and provides a comprehensive reference for models of signal processes. The book clearly demonstrates how simulation techniques can be used to: * Create valid models of signal processes * Provide exibility through the use of modules * Simulate various elements of communications systems, from filters and modulators to test instruments * Explore alternative models for a given system * Circumvent the mathematical intractability of modern transmission links * Plan and construct a computer model in a matter of hours or days, versus the weeks or months needed for laboratory breadboards * Make parameter changes in minutes once a link has been modeled * Provide engineers and students with complete training on the elements of simulation A must have for designers, practicing engineers, and graduate students, this volume presents real-world techniques that can be used with the authors' ST?DT program (a companion work also published by Wiley), or independently with other commercially available simulators.

This user’s reference is a companion to the separate book also titled “Guide to Modelling and Simulation of Systems of Systems.” The principal book explicates integrated development environments to support virtual building and testing of systems of systems, covering in some depth the MS4 Modelling EnvironmentTM. This user’s reference provides a quick reference and exposition of the various concepts and functional features covered in that book. The topics in the user’s reference are grouped in alignment with the workflow displayed on the MS4 Modeling EnvironmentTM launch page, under the headings Atomic Models, System Entity Structure, Pruning SES, and Miscellaneous. For each feature, the reference discusses why we use it, when we should use it, and how to use it. Further comments and links to related features are also included.

Taking the topics of a quantitative methodology course and illustrating them through Monte Carlo simulation, this book examines abstract principles, such as bias, efficiency, and measures of uncertainty in an intuitive, visual way. Instead of thinking in the abstract about what would happen to a particular estimator "in repeated samples," the book uses simulation to actually create those repeated samples and summarize the results. The book includes basic examples appropriate for readers learning the material for the first time, as well as more advanced examples that a researcher might use to evaluate an estimator he or she was using in an actual research project. The book also covers a wide range of topics related to Monte Carlo simulation, such as resampling methods, simulations of substantive theory, simulation of quantities of interest (QI) from model results, and cross-validation. Complete R code from all examples is provided so readers can replicate every analysis presented using R.