Welcome to our book review site go-pdf.online!
You may have to Search all our reviewed books and magazines, click the sign up button below to create a free account.
The Computer Simulation of Monté Carlo Methods and Random Phenomena
This book includes algorithms that illustrate the famous Monté Carlo Methods and the computer simulation of stochastic experiments in the areas of random numbers generation, the simulation of random phenomena, the computation of Pi and e (the base of logarithms), both simple and multiple integration, the computation of areas and volumes, probability and statistical distributions, in addition to an introduction to the novel Complex Probability Paradigm. As such, it will be of interest to all scholars, researchers, and undergraduate and graduate students in mathematics, computer science, and science in general.
Forecasting in Mathematics
Mathematical probability and statistics are an attractive, thriving, and respectable part of mathematics. Some mathematicians and philosophers of science say they are the gateway to mathematics’ deepest mysteries. Moreover, mathematical statistics denotes an accumulation of mathematical discussions connected with efforts to most efficiently collect and use numerical data subject to random or deterministic variations. Currently, the concept of probability and mathematical statistics has become one of the fundamental notions of modern science and the philosophy of nature. This book is an illustration of the use of mathematics to solve specific problems in engineering, statistics, and science in general.
Fault Detection, Diagnosis and Prognosis
This book presents the main concepts, state of the art, advances, and case studies of fault detection, diagnosis, and prognosis. This topic is a critical variable in industry to reach and maintain competitiveness. Therefore, proper management of the corrective, predictive, and preventive politics in any industry is required. This book complements other subdisciplines such as economics, finance, marketing, decision and risk analysis, engineering, etc. The book presents real case studies in multiple disciplines. It considers the main topics using prognostic and subdiscipline techniques. It is essential to link these topics with the areas of finance, scheduling, resources, downtime, etc. to inc...
The Monte Carlo Methods
In applied mathematics, the name Monte Carlo is given to the method of solving problems by means of experiments with random numbers. This name, after the casino at Monaco, was first applied around 1944 to the method of solving deterministic problems by reformulating them in terms of a problem with random elements, which could then be solved by large-scale sampling. But, by extension, the term has come to mean any simulation that uses random numbers. Monte Carlo methods have become among the most fundamental techniques of simulation in modern science. This book is an illustration of the use of Monte Carlo methods applied to solve specific problems in mathematics, engineering, physics, statistics, and science in general.
The Analysis of Selected Algorithms for the Stochastic Paradigm
This book analyses selected algorithms for random and stochastic phenomena in the areas of basic probability, random variables, mathematical expectation, special probability and statistical distributions, random processes, and Markov chains. It also presents a novel approach, titled the “Complex Probability Paradigm”, and applies it to the Brownian motion. As such, the book will be of interest to all scholars, researchers, and undergraduate and graduate students in mathematics, computer science, and science in general.
Simulation Modeling - Recent Advances, New Perspectives, and Applications
A simulation is the imitation of the operation of a real-world process or system over time. Simulations require the use of models in which a model represents the key characteristics or behaviors of the selected system or process and the simulation represents the evolution of the model over time. Computers are often used to execute simulations. This book provides a comprehensive overview of simulation modeling and explores its use to solve a large set of problems. It is a useful resource for scholars, researchers, and undergraduate and graduate students in pure and applied mathematics, physical sciences, engineering and technology, computer science, numerical analysis, scientific computing, and science in general.
Introduction to Probability
This classroom-tested textbook is an introduction to probability theory, with the right balance between mathematical precision, probabilistic intuition, and concrete applications. Introduction to Probability covers the material precisely, while avoiding excessive technical details. After introducing the basic vocabulary of randomness, including events, probabilities, and random variables, the text offers the reader a first glimpse of the major theorems of the subject: the law of large numbers and the central limit theorem. The important probability distributions are introduced organically as they arise from applications. The discrete and continuous sides of probability are treated together to emphasize their similarities. Intended for students with a calculus background, the text teaches not only the nuts and bolts of probability theory and how to solve specific problems, but also why the methods of solution work.
Doing Business 2019
Sixteenth in a series of annual reports comparing business regulation in 190 economies, Doing Business 2019 measures aspects of regulation affecting 10 areas of everyday business activity:•Starting a business•Dealing with construction permits•Getting electricity•Registering property•Getting credit•Protecting minority investors•Paying taxes•Trading across borders•Enforcing contracts•Resolving insolvencyThese areas are included in the distance to frontier score and ease of doing business ranking. Doing Business also measures features of labor market regulation, which is not included in these two measures. This edition also presents the findings of the pilot indicator entitl...
Knowledge Science, Engineering and Management
This two-volume set of LNAI 11775 and LNAI 11776 constitutes the refereed proceedings of the 12th International Conference on Knowledge Science, Engineering and Management, KSEM 2019, held in Athens, Greece, in August 2019. The 77 revised full papers and 23 short papers presented together with 10 poster papers were carefully reviewed and selected from 240 submissions. The papers of the first volume are organized in the following topical sections: Formal Reasoning and Ontologies; Recommendation Algorithms and Systems; Social Knowledge Analysis and Management ; Data Processing and Data Mining; Image and Video Data Analysis; Deep Learning; Knowledge Graph and Knowledge Management; Machine Learning; and Knowledge Engineering Applications. The papers of the second volume are organized in the following topical sections: Probabilistic Models and Applications; Text Mining and Document Analysis; Knowledge Theories and Models; and Network Knowledge Representation and Learning.
