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Modeling and Management of Stochastic Systems

Stochastic control deals with the uncertainties in data observation playing a crucial role in data evolution. Stochastic control plays a;

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Stochastic Modeling of Scientific Data

Stochastic Modeling of Scientific Data combines stochastic modeling and statistical inference in a variety of standard and less common;

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Stochastic Modeling of Scientific Data

Stochastic Modeling of Scientific Data combines stochastic modeling and statistical inference in a variety of standard and less common;

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Stochastic Modeling of Microstructures

This book is for a general scientific and engineering audience as a guide to current ideas, methods, and models for stochastic modeling;

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Proceedings of the 5th International Symposium on Uncertainty Quantification and Stochastic Modelling

) of the AFM (French Society of Mechanical Sciences), the Scientific Committee on Stochastic Modeling and Uncertainty Quantification of the ABCM;

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Applied Modeling Techniques and Data Analysis 2 - Financial, Demographic, Stochastic and Statistical Models and Methods

BIG DATA, ARTIFICIAL INTELLIGENCE AND DATA ANALYSIS SET Coordinated by Jacques Janssen Data analysis is a scientific field that;

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Recent Advances In Stochastic Modeling And Data Analysis

This volume presents the most recent applied and methodological issues in stochastic modeling and data analysis. The contributions cover;

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Stochastic Volatility Modeling

Packed with insights, Lorenzo Bergomi's Stochastic Volatility Modeling explains how stochastic volatility is used to address issues arising;

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Data-Driven Computational Methods

Modern scientific computational methods are undergoing a transformative change; big data and statistical learning methods now have the;

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Quantitative Analysis and Modeling of Earth and Environmental Data

considers the synthesis of scientific theory-based methods (stochastic modeling, modern geostatistics) and data-driven techniques (machine learning;

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Stochastic Modeling in Physical and Biological Sciences

of Markov Chains. This book elaborates continuous time stochastic processes for modeling purpose explaining in detail with examples and includes an;

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Data-Driven Modeling of Cyber-Physical Systems using Side-Channel Analysis

aid the first-principle approach in capturing the stochastic phenomena affecting the CPS. The authors provide practical use cases of the data;

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Data-Driven Modeling of Cyber-Physical Systems using Side-Channel Analysis

aid the first-principle approach in capturing the stochastic phenomena affecting the CPS. The authors provide practical use cases of the data;

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Introduction to Computational Earthquake Engineering

solid continuum mechanics, finite element method and stochastic modeling comprehensively, with the second and third chapters explaining the;

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Comparison Methods for Stochastic Models and Risks

collect meaningful comparative data. Application areas include queueing systems, actuarial and financial risk, decision making and stochastic;

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Handbook of High-Frequency Trading and Modeling in Finance

quantitative tools that address growing concerns relating to high-frequency data such as stochastic volatility and volatility tracking; stochastic jump;

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Probability and Stochastic Modeling

Probability and Stochastic Modeling not only covers all the topics found in a traditional introductory probability course, but also;

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Probability and Stochastic Modeling

Probability and Stochastic Modeling not only covers all the topics found in a traditional introductory probability course, but also;

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An Introduction To Stochastic Modeling

Serving as the foundation for a one-semester course in stochastic processes for students familiar with elementary probability theory and;

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Applications of Stochastic Programming

Research on algorithms and applications of stochastic programming, the study of procedures for decision making under uncertainty over time;

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Statistical Modeling for Biological Systems

research interests including stochastic modeling and the analysis of micro-array data, and throughout the book it emphasizes applications of the;

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Statistical Modeling for Biological Systems

research interests including stochastic modeling and the analysis of micro-array data, and throughout the book it emphasizes applications of the;

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Applied Modeling Techniques and Data Analysis 1 - Computational Data Analysis Methods and Tools

BIG DATA, ARTIFICIAL INTELLIGENCE AND DATA ANALYSIS SET Coordinated by Jacques Janssen Data analysis is a scientific field that;

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Stochastic Modeling and Analysis of Telecom Networks

This book addresses the stochastic modeling of telecommunication networks, introducing the main mathematical tools for that purpose, such;

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Mathematical Modeling in Economics and Finance

the tools of probability theory, difference and differential equations, numerical simulation, data analysis, and mathematical analysis;

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Statistical Methods Of Spatio-Temporal Systems

uses stochastic models, such as point process models, to provide the probabilistic backbone that facilitates statistical inference from data;

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Stochastic Optimization

Stochastic programming is the study of procedures for decision making under the presence of uncertainties and risks. Stochastic;

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