Utilizing mathematical algorithms is an important aspect of
recreating real-world problems in order to make important
decisions. By generating a randomized algorithm that produces
statistic patterns, it becomes easier to find solutions to
countless situations. Stochastic Methods for Estimation and Problem
Solving in Engineering provides emerging research on the role of
random probability systems in mathematical models used in various
fields of research. While highlighting topics, such as random
probability distribution, linear systems, and transport profiling,
this book explores the use and behavior of uncertain probability
methods in business and science. This book is an important resource
for engineers, researchers, students, professionals, and
practitioners seeking current research on the challenges and
opportunities of non-deterministic probability models.
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