Soft Computing Approach for Mathematical Modeling of Engineering Problems

This book discusses mathematical modeling with soft computing and the implementations of uncertain mathematical models, helping readers become familiar with soft numerical methods to simulate the solution functions behavior.

\n Format: Hardback
\n Length: 204 pages
\n Publication date: 01 September 2021
\n Publisher: Taylor & Francis Ltd
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Dynamic models play a crucial role in understanding the complex processes of the world around us. These models are based on the fundamental concept that time is a fundamental element in the structure of the model, the data used to train it, and the understanding of how a process unfolds. Mathematical modeling, a branch of mathematics that involves the use of computers to solve problems, is a powerful tool for developing dynamic models. One of the key aspects of mathematical modeling is the use of soft computing techniques, which are a subset of artificial intelligence. Soft computing techniques are designed to handle complex problems that traditional mathematical methods cannot solve. They are often used in uncertain mathematical models, which are models that include uncertain state, uncertain state space, and uncertain states transition functions.

Uncertain dynamic systems models are a type of mathematical model that is used to describe systems that are subject to uncertainty. These models include uncertain state, uncertain state space, and uncertain states transition functions. They are used to analyze and predict the behavior of these systems, which can be useful in a wide range of applications, including engineering, finance, and healthcare.

To assist readers in becoming familiar with many soft numerical methods to simulate the solution functions behavior, this article will examine how uncertain dynamic systems models include uncertain state, uncertain state space, and uncertain states transition functions. It will also discuss mathematical modeling with soft computing and the implementations of uncertain mathematical models.

In conclusion, dynamic models are a powerful tool for understanding the complex processes of the world around us. Mathematical modeling, with the use of soft computing techniques, is a key aspect of developing these models. Uncertain dynamic systems models are a type of mathematical model that is used to describe systems that are subject to uncertainty. By understanding the principles of these models, readers can gain a deeper understanding of the world and develop more effective solutions to complex problems.

\n Weight: 482g\n
Dimension: 163 x 241 x 22 (mm)\n
ISBN-13: 9780367685997\n \n