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Publication date: 6 September 2019

Vivian M. Evangelista and Rommel G. Regis

Machine learning methods have recently gained attention in business applications. We will explore the suitability of machine learning methods, particularly support vector…

Abstract

Machine learning methods have recently gained attention in business applications. We will explore the suitability of machine learning methods, particularly support vector regression (SVR) and radial basis function (RBF) approximation, in forecasting company sales. We compare the one-step-ahead forecast accuracy of these machine learning methods with traditional statistical forecasting techniques such as moving average (MA), exponential smoothing, and linear and quadratic trend regression on quarterly sales data of 43 Fortune 500 companies. Moreover, we implement an additive seasonal adjustment procedure on the quarterly sales data of 28 of the Fortune 500 companies whose time series exhibited seasonality, referred to as the seasonal group. Furthermore, we prove a mathematical property of this seasonal adjustment procedure that is useful in interpreting the resulting time series model. Our results show that the Gaussian form of a moving RBF model, with or without seasonal adjustment, is a promising method for forecasting company sales. In particular, the moving RBF-Gaussian model with seasonal adjustment yields generally better mean absolute percentage error (MAPE) values than the other methods on the sales data of 28 companies in the seasonal group. In addition, it is competitive with single exponential smoothing and better than the other methods on the sales data of the other 15 companies in the non-seasonal group.

Details

Advances in Business and Management Forecasting
Type: Book
ISBN: 978-1-78754-290-7

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Book part
Publication date: 6 September 2019

Abstract

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Advances in Business and Management Forecasting
Type: Book
ISBN: 978-1-78754-290-7

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Article
Publication date: 1 July 1943

THE beginning of a new volume is necessarily a time for reflection. Our journal is now forty‐four years old and has appeared without intermission, always with the purpose…

Abstract

THE beginning of a new volume is necessarily a time for reflection. Our journal is now forty‐four years old and has appeared without intermission, always with the purpose, enunciated by its founder, James Duff Brown—to furnish librarians of all kinds and ages with a thought‐exchange and a medium of expression independent of any other control than the editor's conviction that what was published was sincere in intention and likely to be of use to the profession. This does not mean, as our pages to‐day witness, that matters of controversy or even of severe criticism of those who lead the profession officially are excluded. On the contrary, we believe that the best spur to advance is a critical vigilance. Thus it has occurred occasionally that our writers have been at variance with some current policy of the Library Association, some phases of its examinations or its conference policy. Occasionally, too, there have been criticisms of library authorities which an official journal might hesitate to make because those authorities may be in membership of the Library Association. Such criticism was never more necessary than now. The library movement has to be kept alive under the greatest strain in history; indeed, it should progress.

Details

New Library World, vol. 46 no. 1
Type: Research Article
ISSN: 0307-4803

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