Modelling machine learning methods (26 Ergebnisse)

Zustand: New. In English.

Paperback. Zustand: Brand New. 336 pages. 6.18x0.71x9.25 inches. In Stock.

Zustand: New. In English.

Zustand: New.

Zustand: New. 2025. paperback. . . . . . Books ship from the US and Ireland.

Paperback. Zustand: Brand New. 336 pages. 6.18x0.71x9.25 inches. In Stock.

Taschenbuch. Zustand: Neu. Neuware - In an era where geo-located point data has become the backbone of socio-economic, environmental, and urban research, understanding spatial density is crucial. Yet the tools for analysing this data have remained scattered and incomplete. Modelling Spatial Density fills a significant gap by providing a comprehensive, practical, and user-friendly guide to modelling spatial density using cutting-edge quantitative methods. Bridging the worlds of spatial statistics, spatial econometrics, and spatial machine learning, Kopczewska introduces a range of established and novel techniques, made accessible through intuitive explanations, open data, and reproducible R code. Lesser and well-known methods are elegantly combined and discussed in non-mathematical language that is accessible to social scientists. The book makes a significant contribution to the synthesis, development, and application of spatial quantitative methods for spatial density in the social and environmental sciences. Writing for researchers, policymakers, and analysts, the author demystifies complex methods, making them accessible to non-mathematicians while maintaining the rigour expected by specialists. With a focus on practical applications, empirical examples, and actionable insights, this resource empowers readers to turn data into evidence for decision-making. Whether you are exploring urban dynamics, environmental challenges, or socio-economic phenomena, this book provides the essential tools for spatial analysis, bringing clarity and precision to your research.…

Zustand: New.

Paperback. Zustand: Brand New. 432 pages. 9.68x6.85x0.98 inches. In Stock.

Zustand: New. In English.

Zustand: New. In English.

Zustand: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | Mathematical modeling is routinely used in physical and engineering sciences to help understand complex systems and optimize industrial processes. Mathematical modeling differs from Artificial Intelligence because it does not exclusively use the collected data to describe an industrial phenomenon or process, but it is based on fundamental laws of physics or engineering that lead to systems of equations able to represent all the variables that characterize the process. Conversely, Machine Learning methods require a large amount of data to find solutions, remaining detached from the problem that generated them and trying to infer the behavior of the object, material or process to be examined from observed samples. Mathematics allows us to formulate complex models with effectiveness and creativity, describing nature and physics. Together with the potential of Artificial Intelligence and data collection techniques, a new way of dealing with practical problems is possible. The insertion of the equations deriving from the physical world in the data-driven models can in fact greatly enrich the information content of the sampled data, allowing to simulate very complex phenomena, with drastically reduced calculation times. Combined approaches will constitute a breakthrough in cutting-edge applications, providing precise and reliable tools for the prediction of phenomena in biological macro/microsystems, for biotechnological applications and for medical diagnostics, particularly in the field of precision medicine.…

Hardcover. Zustand: Very Good.

Taschenbuch. Zustand: Neu. Handbook of Computational Social Science, Volume 2 | Data Science, Statistical Modelling, and Machine Learning Methods | Uwe Engel (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2021 | Routledge | EAN 9781032077703 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu. …

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The book conclusively solves problems associated with the control and estimation of nonlinear and chaotic dynamics in financial systems when these are described in the form of nonlinear ordinary di erential equations. It then addresses problems associated with the control and estimation of financial systems governed by partial di erential equations (e.g. the Black-Scholes partial differential equation (PDE) and its variants). Lastly it an offers optimal solution to the problem of statistical validation of computational models and tools used to support financial engineers in decision making.The application of state-space models in financial engineering means that the heuristics and empirical methods currently in use in decision-making procedures for finance can be eliminated. It also allows methods of fault-free performance and optimality in the management of assets and capitals and methods assuring stability in the functioning of financial systems to be established.Coveringthe following key areas of financial engineering: (i) control and stabilization of financial systems dynamics, (ii) state estimation and forecasting, and (iii) statistical validation of decision-making tools, the book can be used for teaching undergraduate or postgraduate courses in financial engineering. It is also a useful resource for the engineering and computer science community.…

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The book conclusively solves problems associated with the control and estimation of nonlinear and chaotic dynamics in financial systems when these are described in the form of nonlinear ordinary di erential equations. It then addresses problems associated with the control and estimation of financial systems governed by partial di erential equations (e.g. the Black-Scholes partial differential equation (PDE) and its variants). Lastly it an offers optimal solution to the problem of statistical validation of computational models and tools used to support financial engineers in decision making.The application of state-space models in financial engineering means that the heuristics and empirical methods currently in use in decision-making procedures for finance can be eliminated. It also allows methods of fault-free performance and optimality in the management of assets and capitals and methods assuring stability in the functioning of financial systems to be established.Coveringthe following key areas of financial engineering: (i) control and stabilization of financial systems dynamics, (ii) state estimation and forecasting, and (iii) statistical validation of decision-making tools, the book can be used for teaching undergraduate or postgraduate courses in financial engineering. It is also a useful resource for the engineering and computer science community.…

Taschenbuch. Zustand: Neu. State-Space Approaches for Modelling and Control in Financial Engineering | Systems theory and machine learning methods | Gerasimos G. Rigatos | Taschenbuch | Intelligent Systems Reference Library | xxviii | Englisch | 2018 | Springer | EAN 9783319850047 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

Hardcover. Zustand: Brand New. 340 pages. 9.25x6.10x1.10 inches. In Stock.

Zustand: New. In English.

Zustand: New. 2021. 1st Edition. Paperback. . . . . . Books ship from the US and Ireland.

Hardcover. Zustand: Brand New. 200 pages. 9.19x6.13x0.75 inches. In Stock.

Hardcover. Zustand: Brand New. 336 pages. 6.14x0.75x9.21 inches. In Stock.

Zustand: New.

Zustand: New. In English.

Zustand: New.

Hardcover. Zustand: Brand New. 432 pages. 9.75x7.00x1.00 inches. In Stock.