FUNDAMENTALS OF STOCHASTIC MODELS (HB 2023) Hardcover

Stochastic modeling is a set of quantitative methods used to analyze systems influenced by random factors. While this field is typically technical and developed by mathematicians, most existing resources require advanced mathematical knowledge. This book aims to simplify the topics, making them more accessible without extensive mathematical training. "Fundamentals of Stochastic Models" offers practical examples and applications, bridging the gap between basic stochastic process theory and more advanced concepts. It covers both performance evaluation and optimization of stochastic systems, introducing modern analytical techniques such as matrix methods and diffusion/fluid limit approaches. The book also explores the connection between stochastic models, machine learning, and artificial intelligence, emphasizing intuitive methods over traditional theoretical ones. The goal is to minimize the need for a strong mathematical background, making it suitable for professionals and students in industrial engineering, business, economics, computer science, and applied mathematics.