The.Hottest

David L. Olson ... 173 pages - Publisher: Business Expert Press; (June, 2016) ... Language: English - ISBN-10: 9781631575488 - ISBN-13: 978-1631575488 ...

Data mining has become the fastest growing topic of interest in business programs in the past decade. This book is intended to describe the benefits of data mining in business, the process and typical business applications, the workings of basic data mining models, and demonstrate each with widely available free software. The book focuses on demonstrating common business data mining applications. It provides exposure to the data mining process, to include problem identification, data management, and available modeling tools. The book takes the approach of demonstrating typical business data sets with open source software. KNIME is a very easy-to-use tool, and is used as the primary means of demonstration. R is much more powerful and is a commercially viable data mining tool. We also demonstrate WEKA, which is a highly useful academic software, although it is difficult to manipulate test sets and new cases, making it problematic for commercial use.

Nilanjan Dey ... 335 pages - Publisher: IGI Global; 1st edition (November, 2017) ... Language: English - ISBN-10: 9781522541516 - ISBN-13: 978-1522541516 ...

Metaheuristic algorithms are present in various applications for different domains. Recently, researchers have conducted studies on the effectiveness of these algorithms in providing optimal solutions to complicated problems. Advancements in Applied Metaheuristic Computing is a crucial reference source for the latest empirical research on methods and approaches that include metaheuristics for further system improvements, and it offers outcomes of employing optimization algorithms. Featuring coverage on a broad range of topics such as manufacturing, genetic programming, and medical imaging, this publication is ideal for researchers, academicians, advanced-level students, and technology developers seeking current research on the use of optimization algorithms in several applications.

Deep Freeze v8.55.220.5505 [Size: 55.8 MB] ... Deep Freeze instantly protects and preserves baseline computer configurations. No matter what changes a user makes to a workstation, simply restart to eradicate all changes and reset the computer to its original state – right down to the last byte. Expensive computer assets are kept running at 100% capacity and technical support time is reduced or eliminated completely. The result is consistent trouble-free computing on a truly protected and parallel network, completely free of harmful viruses and unwanted programs.

Rob J. Hyndman, George Athanasopoulos ... 382 pages - Publisher: OTexts; 2nd edition (May, 2018) ... Language: English - ISBN-10: 0987507117 - ISBN-13: 978-0987507112 ...

Forecasting is required in many situations. Deciding whether to build another power generation plant in the next five years requires forecasts of future demand. Scheduling staff in a call centre next week requires forecasts of call volumes. Stocking an inventory requires forecasts of stock requirements. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly. Examples use R with many data sets taken from the authors' own consulting experience. In this second edition, all chapters have been updated to cover the latest research and forecasting methods. Three new chapters have been added on dynamic regression forecasting, hierarchical forecasting and practical forecasting issues.

Xiaofeng Wang, Yu Ryan Yue, Julian J. Faraway ... 324 pages - Publisher: Chapman and Hall/CRC; Language: English - ISBN-10: 1498727255 - ISBN-13: 978-1498727259 ...

INLA stands for Integrated Nested Laplace Approximations, which is a new method for fitting a broad class of Bayesian regression models. No samples of the posterior marginal distributions need to be drawn using INLA, so it is a computationally convenient alternative to Markov chain Monte Carlo (MCMC), the standard tool for Bayesian inference. Bayesian Regression Modeling with INLA covers a wide range of modern regression models and focuses on the INLA technique for building Bayesian models using real-world data and assessing their validity. A key theme throughout the book is that it makes sense to demonstrate the interplay of theory and practice with reproducible studies. Complete R commands are provided for each example, and a supporting website holds all of the data described in the book. An R package including the data and additional functions in the book is available to download. The book is aimed at readers who have a basic knowledge of statistical theory and Bayesian methodology. It gets readers up to date on the latest in Bayesian inference using INLA and prepares them for sophisticated, real-world work.

Andreas Kappos ... 388 pages - Publisher: CRC Press; 1st edition (November, 2001) ... Language: English - ISBN-10: 0419229302 - ISBN-13: 978-0419229308 ...

Until now, information on the dynamic loading of structures has been widely scattered. No other book has examined the different types of loading in a comprehensive and systematic manner, and looked at their signficance in the design process. The book begins with a survey of the probabilistic background to all forms of loads, which is particularly important to dynamic loads, and then looks at the main types in turn: wind, earthquake, wave, blast and impact loading. The relevant code provisions (Eurocode and UBC American) are detailed and a number of examples are used to illustrate the principles. A final section covers the analysis for dynamic loading, drawing out the concepts underlying the treatment of all dynamic loads, and the corresponding modelling techniques. Throughout there is a focus on the modelling of structures, rather than on classical structural dynamics.

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