Demystifying Numerical Models: Step-by Step Modeling of Engineering Systems is the perfect guide on the analytic concepts of engineering components and systems. In simplified terms, the book focuses on engineering characteristics and behaviors using numerical methods. Readers will learn how the computational aspects of engineering analysis can be applied to develop various engineering systems to a level that is fit for implementation. - Provides numerical examples and graphical representations of complex mathematical models - Includes downloadable spreadsheets of the numerical tools discussed that allow the reader to gain a hands-on understanding of how they work - Explains the engineering foundations behind the increasingly widespread and complex numerical models

This book demystifies the models we use to simulate present and future climates, allowing readers to better understand how to use climate model results. In order to predict the future trajectory of the Earth’s climate, climate-system simulation models are necessary. When and how do we trust climate model predictions? The book offers a framework for answering this question. It provides readers with a basic primer on climate and climate change, and offers non-technical explanations for how climate models are constructed, why they are uncertain, and what level of confidence we should place in them. It presents current results and the key uncertainties concerning them. Uncertainty is not a weakness but understanding uncertainty is a strength and a key part of using any model, including climate models. Case studies of how climate model output has been used and how it might be used in the future are provided. The ultimate goal of this book is to promote a better understanding of the structure and uncertainties of climate models among users, including scientists, engineers and policymakers.

This book presents an emerging new vision of the brain, which is essentially expressed in computational terms, for non-experts. As such, it presents the fundamental concepts of neuroscience in simple language, without overwhelming non-biologists with excessive biological jargon. In addition, the book presents a novel computational perspective on the brain for biologists, without resorting to complex mathematical equations. It addresses a comprehensive range of topics, starting with the history of neuroscience, the function of the individual neuron, the various kinds of neural network models that can explain diverse neural phenomena, sensory-motor function, language, emotions, and concluding with the latest theories on consciousness. The book offers readers a panoramic introduction to the “new brain” and a valuable resource for interdisciplinary researchers looking to gatecrash the world of neuroscience.

This book presents a selection of papers from the industrial track of ISMIS 2020. The selection emphasizes broad applicability of artificial intelligence (AI) technologies in various industrial fields. The aim of the book is to fertilize preliminary ideas of readers on the application of AI by means of already successfully implemented application examples. Furthermore, the development of new ideas and concepts shall be motivated by the variety of different application examples. The spectrum of the presented contributions ranges from education and training, industrial applications in production and logistics to the development of new approaches in basic research, which will further expand the possibilities of future applications of AI in industrial settings. This broad spectrum gives readers working in the industrial as well as the academic field a good overview of the state of the art in the field of methodologies for intelligent systems.

Engineering Principles of Unit Operations in Food Processing, volume 1 in the Woodhead Publishing Series, In Unit Operations and Processing Equipment in the Food Industry series, presents basic principles of food engineering with an emphasis on unit operations, such as heat transfer, mass transfer and fluid mechanics. - Brings new opportunities in the optimization of food processing operations - Thoroughly explores applications of food engineering to food processes - Focuses on unit operations from an engineering viewpoint

What is Economic Model An economic model is a theoretical construct representing economic processes by a set of variables and a set of logical and/or quantitative relationships between them. The economic model is a simplified, often mathematical, framework designed to illustrate complex processes. Frequently, economic models posit structural parameters. A model may have various exogenous variables, and those variables may change to create various responses by economic variables. Methodological uses of models include investigation, theorizing, and fitting theories to the world. How you will benefit (I) Insights, and validations about the following topics: Chapter 1: Economic model Chapter 2: Econometrics Chapter 3: Macroeconomics Chapter 4: Mathematical model Chapter 5: Neoclassical economics Chapter 6: Rational expectations Chapter 7: Index of economics articles Chapter 8: Lucas critique Chapter 9: Macroeconomic model Chapter 10: Bellman equation Chapter 11: Econometric model Chapter 12: Lars Peter Hansen Chapter 13: Applied economics Chapter 14: Economics education Chapter 15: Qualitative economics Chapter 16: Dynamic stochastic general equilibrium Chapter 17: Mathematical economics Chapter 18: Real business-cycle theory Chapter 19: Mathematical finance Chapter 20: Criticisms of econometrics Chapter 21: Causal inference (II) Answering the public top questions about economic model. (III) Real world examples for the usage of economic model in many fields. Who this book is for Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Economic Model.