All human activities, including mental activities, are governed by physical laws and are essentially thermodynamic processes. However, current economic theories are not established on these foundations. This pioneering book seeks to develop an analytical theory of economics on the foundation of thermodynamic laws. A unified understanding of economic and social phenomena is presented, an understanding that is much simpler than what mainstream economic theory has to offer. Its aim is to revolutionize thinking in economics and transform social sciences into an integral part of the physical and biological sciences.
All human activities, including mental activities, are governed by physical laws and are essentially thermodynamic processes. However, current economic theories are not established on these foundations. This pioneering book seeks to develop an analytical theory of economics on the foundation of thermodynamic laws. A unified understanding of economic and social phenomena is presented, an understanding that is much simpler than what mainstream economic theory has to offer. Its aim is to revolutionize thinking in economics and transform social sciences into an integral part of the physical and biological sciences.
This book presents a new economic theory developed from physical and biological principles. It explains how technology, social systems and economic values are intimately related to resources. Many people have recognized that mainstream (neoclassical) economic theories are not consistent with physical laws and often not consistent with empirical patterns, but most feel that economic activities are too complex to be described by a simple and coherent mathematical theory. While social systems are indeed complex, all life systems, including social systems, satisfy two principles. First, all systems need to extract resources from the external environment to compensate for their consumption. Second, for a system to be viable, the amount of resource extraction has to be no less than the level of consumption. From these two principles, we derive a quantitative theory of major factors in economic activities, such as fixed cost, variable cost, discount rate, uncertainty and duration. The mathematical theory enables us to systematically measure the effectiveness of different policies and institutional structures at varying levels of resource abundance and cost.The theory presented in this book shows that there do not exist universally optimal policies or institutional structures. Instead, the impacts of different policies or social structures have to be measured within the context of existing levels of resource abundance. As the physical costs of extracting resources rise steadily, many policy assumptions adopted in mainstream economic theories, and workable in times of cheap and abundant energy supplies and other resources, need to be reconsidered. In this rapidly changing world, the theory presented here provides a solid foundation for examining the long-term impacts of today's policy decisions.
Since the introduction of the information measure widely known as Shannon entropy, quantifiers based on information theory and concepts such as entropic forms and statistical complexities have proven to be useful in diverse scientific research fields. This book contains introductory tutorials suitable for the general reader, together with chapters dedicated to the basic concepts of the most frequently employed information measures or quantifiers and their recent applications to different areas, including physics, biology, medicine, economics, communication and social sciences. As these quantifiers are powerful tools for the study of general time and data series independently of their sources, this book will be useful to all those doing research connected with information analysis. The tutorials in this volume are written at a broadly accessible level and readers will have the opportunity to acquire the knowledge necessary to use the information theory tools in their field of interest.
The 4th International Conference on Economic Management and Big Data Applications was successfully held in Tianjin, China from October 27th to 29th, 2023. This conference served as a platform for researchers, scholars, and industry professionals to exchange knowledge and insights in the field of economic management and the application of big data. The conference held great significance in advancing the understanding and application of economic management and big data. By bringing together experts from around the globe, the conference facilitated the exchange of innovative ideas and research findings, contributing to the development of these fields. The topics covered during the conference showcased the latest advancements and trends in enterprise economic statistics, information evaluation, blockchain technology, industrial structure optimization, information retrieval, data regression analysis, intelligent Internet of Things platforms, and data encryption. The discussions and presentations during the conference allowed participants to explore new methodologies, strategies, and technologies that can enhance economic management practices and leverage the potential of big data. The conference provided a platform for scholars and practitioners to share their experiences, insights, and best practices, fostering collaboration and networking opportunities. Furthermore, the proceedings were published, ensuring the dissemination of valuable research findings to a wider audience. The collective knowledge and research presented at the conference will contribute to the academic community, industry professionals, and policymakers, enabling them to make informed decisions and develop effective strategies in the fields of economic management and big data applications. Overall, the 4th International Conference on Economic Management and Big Data Applications played a pivotal role in promoting knowledge exchange, fostering innovation, and shaping the future of economic management by harnessing the power of big data.
Students and researchers from all fields of mathematics are invited to read and treasure this special Proceedings. A conference was held 25 –29 September 2017 at Noah’s On the Beach, Newcastle, Australia, to commemorate the life and work of Jonathan M. Borwein, a mathematician extraordinaire whose untimely passing in August 2016 was a sorry loss to mathematics and to so many members of its community, a loss that continues to be keenly felt. A polymath, Jonathan Borwein ranks among the most wide ranging and influential mathematicians of the last 50 years, making significant contributions to an exceptional diversity of areas and substantially expanding the use of the computer as a tool of the research mathematician. The contributions in this commemorative volume probe Dr. Borwein's ongoing legacy in areas where he did some of his most outstanding work: Applied Analysis, Optimization and Convex Functions; Mathematics Education; Financial Mathematics; plus Number Theory, Special Functions and Pi, all tinged by the double prisms of Experimental Mathematics and Visualization, methodologies he championed.
Information and Entropy Econometrics - A Review and Synthesis summarizes the basics of information theoretic methods in econometrics and the connecting theme among these methods. The sub-class of methods that treat the observed sample moments as stochastic is discussed in greater details. I Information and Entropy Econometrics - A Review and Synthesis -focuses on inter-connection between information theory, estimation and inference. -provides a detailed survey of information theoretic concepts and quantities used within econometrics and then show how these quantities are used within IEE. -pays special attention for the interpretation of these quantities and for describing the relationships between information theoretic estimators and traditional estimators. Readers need a basic knowledge of econometrics, but do not need prior knowledge of information theory. The survey is self contained and interested readers can replicate all results and examples provided. Whenever necessary the readers are referred to the relevant literature. Information and Entropy Econometrics - A Review and Synthesis will benefit researchers looking for a concise introduction to the basics of IEE and to acquire the basic tools necessary for using and understanding these methods. Applied researchers can use the book to learn improved new methods, and applications for extracting information from noisy and limited data and for learning from these data.
This Is The First Comprehensive Book About Maximum Entropy Principle And Its Applications To A Diversity Of Fields Like Statistical Mechanics, Thermo-Dynamics, Business, Economics, Insurance, Finance, Contingency Tables, Characterisation Of Probability Distributions (Univariate As Well As Multivariate, Discrete As Well As Continuous), Statistical Inference, Non-Linear Spectral Analysis Of Time Series, Pattern Recognition, Marketing And Elections, Operations Research And Reliability Theory, Image Processing, Computerised Tomography, Biology And Medicine. There Are Over 600 Specially Constructed Exercises And Extensive Historical And Bibliographical Notes At The End Of Each Chapter.The Book Should Be Of Interest To All Applied Mathematicians, Physicists, Statisticians, Economists, Engineers Of All Types, Business Scientists, Life Scientists, Medical Scientists, Radiologists And Operations Researchers Who Are Interested In Applying The Powerful Methodology Based On Maximum Entropy Principle In Their Respective Fields.
This book features high-quality research papers presented at the 4th International Conference on Computational Intelligence in Pattern Recognition (CIPR 2022), held at Indian Institute of Engineering Science and Technology, Shibpur, Howrah, West Bengal, India, during 23 – 24 April 2022. It includes practical development experiences in various areas of data analysis and pattern recognition, focusing on soft computing technologies, clustering and classification algorithms, rough set and fuzzy set theory, evolutionary computations, neural science and neural network systems, image processing, combinatorial pattern matching, social network analysis, audio and video data analysis, data mining in dynamic environments, bioinformatics, hybrid computing, big data analytics and deep learning. It also provides innovative solutions to the challenges in these areas and discusses recent developments.
Entropies and entropy-like quantities play an increasing role in modern non-linear data analysis. Fields that benefit from this application range from biosignal analysis to econophysics and engineering. This issue is a collection of papers touching on different aspects of entropy measures in data analysis, as well as theoretical and computational analyses. The relevant topics include the difficulty to achieve adequate application of entropy measures and the acceptable parameter choices for those entropy measures, entropy-based coupling, and similarity analysis, along with the utilization of entropy measures as features in automatic learning and classification. Various real data applications are given.
