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Fractal Dimension for Fractal Structures
This book provides a generalised approach to fractal dimension theory from the standpoint of asymmetric topology by employing the concept of a fractal structure. The fractal dimension is the main invariant of a fractal set, and provides useful information regarding the irregularities it presents when examined at a suitable level of detail. New theoretical models for calculating the fractal dimension of any subset with respect to a fractal structure are posed to generalise both the Hausdorff and box-counting dimensions. Some specific results for self-similar sets are also proved. Unlike classical fractal dimensions, these new models can be used with empirical applications of fractal dimension...
Distribution Models Theory
Distribution Models Theory is a revised edition of papers specially selected by the Scientific Committee for the Fifth Workshop of Spanish Scientific Association of Applied Economy on Distribution Models Theory held in Granada (Spain) in September 2005. The contributions offer a must-have point of reference on models theory.This book has been selected for coverage in: ? Index to Scientific & Technical Proceedings? (ISTP?/ISI Proceedings)? Index to Scientific & Technical Proceedings (ISTP CDROM version/ISI Proceedings)
Data Science in Theory and Practice
This comprehensive edited volume showcases the latest breakthroughs and innovative research in the rapidly evolving field of data science, and brings together contributions from leading experts and researchers who push the boundaries of the field, offering readers a deep insight into the diverse facets of this transformative discipline. Spanning a wide spectrum of topics, the chapters in this volume cover key areas such as machine learning, artificial intelligence, statistical analysis, and ethical considerations in data science. Each chapter is a testament to the ongoing quest for knowledge and the relentless pursuit of excellence in harnessing the power of data for meaningful insights and actionable intelligence. Whether you're an experienced data scientist, a researcher exploring the frontiers of the field, or a novice eager to grasp the fundamentals, this edited volume serves as a valuable resource. The compilation not only highlights the current state of data science but also anticipates future trends, paving the way for continued advancements and paradigm shifts in the way we approach, analyze, and leverage data.
Industrial Engineering, Computation and Information Technologies
Selected, peer reviewed papers from the 2014 2nd International Conference on Mechatronics and Information Technology (ICMIT 2014), October 18-19, 2014, Chongqing, China
Quantitative Methods for Economics and Finance
This book is a collection of papers for the Special Issue “Quantitative Methods for Economics and Finance” of the journal Mathematics. This Special Issue reflects on the latest developments in different fields of economics and finance where mathematics plays a significant role. The book gathers 19 papers on topics such as volatility clusters and volatility dynamic, forecasting, stocks, indexes, cryptocurrencies and commodities, trade agreements, the relationship between volume and price, trading strategies, efficiency, regression, utility models, fraud prediction, or intertemporal choice.
Applied topology: recent progress for computer science, fuzzy mathematics and economics.
En las últimas décadas, la Topología se ha revelado como una poderosa herramienta para acometer diferentes problemas relacionados con un amplio espectro de ciencias aplicadas más allá de las matemáticas, como Economía, Inteligencia Artificial, Ciencias de la Computación o Sistemas Dinámicos. El presente volumen recoge las ponencias del Workshop in Applied Topology WiAT¿12, celebrado en junio de 2012 en la Universitat Jaume I, en el que participaron diferentes grupos de investigación del área de la Topología General y sus Aplicaciones.
Analysis and Forecasting of Financial Time Series
This book brings together real-world cases illustrating how to analyse volatile financial time series in order to provide a better understanding of their past behavior and robust forecasting of their future behavioural patterns. Using time series data from diverse financial sectors, it shows how the concepts and techniques of statistical analysis, machine learning, and deep learning are applied to build robust predictive models, as well as the ways in which these models can be used for forecasting the future prices of stocks and constructing profitable portfolios of investments. All the concepts and methods used in the book have been implemented using Python and R languages on TensorFlow and Keras frameworks. The volume will be particularly useful for advanced postgraduate and doctoral students of finance, economics, econometrics, statistics, data science, computer science, and information technology.
Mathematical and Statistical Methods for Actuarial Sciences and Finance
This volume gathers selected peer-reviewed papers presented at the international conference "MAF 2016 – Mathematical and Statistical Methods for Actuarial Sciences and Finance”, held in Paris (France) at the Université Paris-Dauphine from March 30 to April 1, 2016. The contributions highlight new ideas on mathematical and statistical methods in actuarial sciences and finance. The cooperation between mathematicians and statisticians working in insurance and finance is a very fruitful field, one that yields unique theoretical models and practical applications, as well as new insights in the discussion of problems of national and international interest. This volume is addressed to academicians, researchers, Ph.D. students and professionals.
Third Congress on Intelligent Systems
This book is a collection of selected papers presented at the Third Congress on Intelligent Systems (CIS 2022), organized by CHRIST (Deemed to be University), Bangalore, India, under the technical sponsorship of the Soft Computing Research Society, India, during September 5–6, 2022. It includes novel and innovative work from experts, practitioners, scientists, and decision-makers from academia and industry. It covers topics such as the Internet of Things, information security, embedded systems, real-time systems, cloud computing, big data analysis, quantum computing, automation systems, bio-inspired intelligence, cognitive systems, cyber-physical systems, data analytics, data/web mining, d...
