Time Series Models For Short Term Forecasting Performance Indicators

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Time Series Models for Short-Term Forecasting Performance Indicators

Author : Arno Palmrich
Publisher : GRIN Verlag
ISBN 13 : 3640435869
Total Pages : 86 pages
Book Rating : 4.6/5 (44 download)

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Book Synopsis Time Series Models for Short-Term Forecasting Performance Indicators by : Arno Palmrich

Download or read book Time Series Models for Short-Term Forecasting Performance Indicators written by Arno Palmrich and published by GRIN Verlag. This book was released on 2009-09-30 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt: Diploma Thesis from the year 2007 in the subject Business economics - Business Management, Corporate Governance, grade: highest grade (ausgezeichnet), University of Applied Sciences Kufstein Tirol, course: Economics Statistics, language: English, abstract: Managers use forecasting in budgeting time and resources. In this thesis, various advanced time series models are constructed, computed and tested for adequacy. This thesis serves as a practical guide to regression and time series analysis. It seeks to demonstrate how to approach problems according to scientific standards to students who are familiar with SPSS® but beginners in regression and time series analysis. Bibliographic notes of classical works and more recent academic advances in time series analysis are provided throughout the text. The research question that this thesis seeks to answer can be formulated in its shortest version as: “How can the management of Dalian Chemson Chemical Products Co; Ltd. use existing company data to make short-term predictions about net sales, Cost of Goods Sold (COGS), and net contribution?” More specifically, this thesis seeks to provide different tools (models) for forecasting the P&L entries net sales, COGS, and net contribution a few months ahead. This author’s approach is based on various versions of two models: One model will forecast net sales and the other model will predict COGS. The expected net contribution is simply defined as the difference between the predictions of these two models. In chapter 4.3 an ordinary least squares regression version of the two models has been computed. In chapter 4.6 a weighted least squares regression has been applied to the models. Autoregressions have been computed in chapter 4.7.1 and two Autoregressive Integrated Moving Average (ARIMA) versions have been constructed in chapter 4.7.6. The various versions of the models have then been compared against each other. The version that fits the data best will be used in forecasting. The statistical models in this thesis are computed using SPSS BaseTM, SPSS Regression ModelsTM and SPSS TrendsTM, versions 11.5.0. Each of the model versions constructed herein can be applied in a simple Excel spreadsheet. In the last chapter, a one-step-ahead forecast is produced via the in this thesis developed concept which consists of the most precise versions of the models to forecast net sales and COGS. The forecasting concept developed in this thesis is good in that it produces precise forecasts. Its simplified framework minimizes the effort and expertise required to obtain predictions.

Renewable Energy Forecasting

Author : Georges Kariniotakis
Publisher : Woodhead Publishing
ISBN 13 : 0081005059
Total Pages : 388 pages
Book Rating : 4.0/5 (81 download)

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Book Synopsis Renewable Energy Forecasting by : Georges Kariniotakis

Download or read book Renewable Energy Forecasting written by Georges Kariniotakis and published by Woodhead Publishing. This book was released on 2017-09-29 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: Renewable Energy Forecasting: From Models to Applications provides an overview of the state-of-the-art of renewable energy forecasting technology and its applications. After an introduction to the principles of meteorology and renewable energy generation, groups of chapters address forecasting models, very short-term forecasting, forecasting of extremes, and longer term forecasting. The final part of the book focuses on important applications of forecasting for power system management and in energy markets. Due to shrinking fossil fuel reserves and concerns about climate change, renewable energy holds an increasing share of the energy mix. Solar, wind, wave, and hydro energy are dependent on highly variable weather conditions, so their increased penetration will lead to strong fluctuations in the power injected into the electricity grid, which needs to be managed. Reliable, high quality forecasts of renewable power generation are therefore essential for the smooth integration of large amounts of solar, wind, wave, and hydropower into the grid as well as for the profitability and effectiveness of such renewable energy projects. - Offers comprehensive coverage of wind, solar, wave, and hydropower forecasting in one convenient volume - Addresses a topic that is growing in importance, given the increasing penetration of renewable energy in many countries - Reviews state-of-the-science techniques for renewable energy forecasting - Contains chapters on operational applications

Forecasting: principles and practice

Author : Rob J Hyndman
Publisher : OTexts
ISBN 13 : 0987507117
Total Pages : 380 pages
Book Rating : 4.9/5 (875 download)

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Book Synopsis Forecasting: principles and practice by : Rob J Hyndman

Download or read book Forecasting: principles and practice written by Rob J Hyndman and published by OTexts. This book was released on 2018-05-08 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. 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.

Forecasting with Exponential Smoothing

Author : Rob Hyndman
Publisher : Springer Science & Business Media
ISBN 13 : 3540719180
Total Pages : 362 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Forecasting with Exponential Smoothing by : Rob Hyndman

Download or read book Forecasting with Exponential Smoothing written by Rob Hyndman and published by Springer Science & Business Media. This book was released on 2008-06-19 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exponential smoothing methods have been around since the 1950s, and are still the most popular forecasting methods used in business and industry. However, a modeling framework incorporating stochastic models, likelihood calculation, prediction intervals and procedures for model selection, was not developed until recently. This book brings together all of the important new results on the state space framework for exponential smoothing. It will be of interest to people wanting to apply the methods in their own area of interest as well as for researchers wanting to take the ideas in new directions. Part 1 provides an introduction to exponential smoothing and the underlying models. The essential details are given in Part 2, which also provide links to the most important papers in the literature. More advanced topics are covered in Part 3, including the mathematical properties of the models and extensions of the models for specific problems. Applications to particular domains are discussed in Part 4.

Introduction to Time Series and Forecasting

Author : Peter J. Brockwell
Publisher : Springer Science & Business Media
ISBN 13 : 1475725264
Total Pages : 429 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Introduction to Time Series and Forecasting by : Peter J. Brockwell

Download or read book Introduction to Time Series and Forecasting written by Peter J. Brockwell and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 429 pages. Available in PDF, EPUB and Kindle. Book excerpt: Some of the key mathematical results are stated without proof in order to make the underlying theory acccessible to a wider audience. The book assumes a knowledge only of basic calculus, matrix algebra, and elementary statistics. The emphasis is on methods and the analysis of data sets. The logic and tools of model-building for stationary and non-stationary time series are developed in detail and numerous exercises, many of which make use of the included computer package, provide the reader with ample opportunity to develop skills in this area. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Additional topics include harmonic regression, the Burg and Hannan-Rissanen algorithms, unit roots, regression with ARMA errors, structural models, the EM algorithm, generalized state-space models with applications to time series of count data, exponential smoothing, the Holt-Winters and ARAR forecasting algorithms, transfer function models and intervention analysis. Brief introducitons are also given to cointegration and to non-linear, continuous-time and long-memory models. The time series package included in the back of the book is a slightly modified version of the package ITSM, published separately as ITSM for Windows, by Springer-Verlag, 1994. It does not handle such large data sets as ITSM for Windows, but like the latter, runs on IBM-PC compatible computers under either DOS or Windows (version 3.1 or later). The programs are all menu-driven so that the reader can immediately apply the techniques in the book to time series data, with a minimal investment of time in the computational and algorithmic aspects of the analysis.

Short-Term Load Forecasting 2019

Author : Antonio Gabaldón
Publisher : MDPI
ISBN 13 : 303943442X
Total Pages : 324 pages
Book Rating : 4.0/5 (394 download)

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Book Synopsis Short-Term Load Forecasting 2019 by : Antonio Gabaldón

Download or read book Short-Term Load Forecasting 2019 written by Antonio Gabaldón and published by MDPI. This book was released on 2021-02-26 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: Short-term load forecasting (STLF) plays a key role in the formulation of economic, reliable, and secure operating strategies (planning, scheduling, maintenance, and control processes, among others) for a power system and will be significant in the future. However, there is still much to do in these research areas. The deployment of enabling technologies (e.g., smart meters) has made high-granularity data available for many customer segments and to approach many issues, for instance, to make forecasting tasks feasible at several demand aggregation levels. The first challenge is the improvement of STLF models and their performance at new aggregation levels. Moreover, the mix of renewables in the power system, and the necessity to include more flexibility through demand response initiatives have introduced greater uncertainties, which means new challenges for STLF in a more dynamic power system in the 2030–50 horizon. Many techniques have been proposed and applied for STLF, including traditional statistical models and AI techniques. Besides, distribution planning needs, as well as grid modernization, have initiated the development of hierarchical load forecasting. Analogously, the need to face new sources of uncertainty in the power system is giving more importance to probabilistic load forecasting. This Special Issue deals with both fundamental research and practical application research on STLF methodologies to face the challenges of a more distributed and customer-centered power system.

Time-Series Forecasting

Author : Chris Chatfield
Publisher : CRC Press
ISBN 13 : 1420036203
Total Pages : 281 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Time-Series Forecasting by : Chris Chatfield

Download or read book Time-Series Forecasting written by Chris Chatfield and published by CRC Press. This book was released on 2000-10-25 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the author of the bestselling "Analysis of Time Series," Time-Series Forecasting offers a comprehensive, up-to-date review of forecasting methods. It provides a summary of time-series modelling procedures, followed by a brief catalogue of many different time-series forecasting methods, ranging from ad-hoc methods through ARIMA and state-space

Introduction to Time Series Forecasting With Python

Author : Jason Brownlee
Publisher : Machine Learning Mastery
ISBN 13 :
Total Pages : 359 pages
Book Rating : 4./5 ( download)

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Book Synopsis Introduction to Time Series Forecasting With Python by : Jason Brownlee

Download or read book Introduction to Time Series Forecasting With Python written by Jason Brownlee and published by Machine Learning Mastery. This book was released on 2017-02-16 with total page 359 pages. Available in PDF, EPUB and Kindle. Book excerpt: Time series forecasting is different from other machine learning problems. The key difference is the fixed sequence of observations and the constraints and additional structure this provides. In this Ebook, finally cut through the math and specialized methods for time series forecasting. Using clear explanations, standard Python libraries and step-by-step tutorials you will discover how to load and prepare data, evaluate model skill, and implement forecasting models for time series data.

Nonlinear Modeling of Economic and Financial Time-Series

Author : Fredj Jawadi
Publisher : Emerald Group Publishing
ISBN 13 : 0857244892
Total Pages : 224 pages
Book Rating : 4.8/5 (572 download)

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Book Synopsis Nonlinear Modeling of Economic and Financial Time-Series by : Fredj Jawadi

Download or read book Nonlinear Modeling of Economic and Financial Time-Series written by Fredj Jawadi and published by Emerald Group Publishing. This book was released on 2010-12-17 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents researches in linear and nonlinear modelling of economic and financial time-series. This book provides a comprehensive understanding of financial and economic dynamics in various aspects using modern financial econometric methods. It also presents and discusses research findings and their implications.

Short-Term Forecasting for Empirical Economists

Author : Maximo Camacho
Publisher :
ISBN 13 : 9781601987426
Total Pages : 74 pages
Book Rating : 4.9/5 (874 download)

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Book Synopsis Short-Term Forecasting for Empirical Economists by : Maximo Camacho

Download or read book Short-Term Forecasting for Empirical Economists written by Maximo Camacho and published by . This book was released on 2013-11-01 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt: Short-term Forecasting for Empirical Economists seeks to close the gap between research and applied short-term forecasting. The authors review some of the key theoretical results and empirical findings in the recent literature on short-term forecasting, and translate these findings into economically meaningful techniques to facilitate their widespread application to compute short-term forecasts in economics, and to monitor the ongoing business cycle developments in real time.

Deep Learning for Time Series Forecasting

Author : Jason Brownlee
Publisher : Machine Learning Mastery
ISBN 13 :
Total Pages : 572 pages
Book Rating : 4./5 ( download)

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Book Synopsis Deep Learning for Time Series Forecasting by : Jason Brownlee

Download or read book Deep Learning for Time Series Forecasting written by Jason Brownlee and published by Machine Learning Mastery. This book was released on 2018-08-30 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning methods offer a lot of promise for time series forecasting, such as the automatic learning of temporal dependence and the automatic handling of temporal structures like trends and seasonality. With clear explanations, standard Python libraries, and step-by-step tutorial lessons you’ll discover how to develop deep learning models for your own time series forecasting projects.

Conference Proceedings of the 2023 3rd International Joint Conference on Energy, Electrical and Power Engineering

Author : Cungang Hu
Publisher : Springer Nature
ISBN 13 : 9819739403
Total Pages : 822 pages
Book Rating : 4.8/5 (197 download)

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Book Synopsis Conference Proceedings of the 2023 3rd International Joint Conference on Energy, Electrical and Power Engineering by : Cungang Hu

Download or read book Conference Proceedings of the 2023 3rd International Joint Conference on Energy, Electrical and Power Engineering written by Cungang Hu and published by Springer Nature. This book was released on with total page 822 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Deep Learning with Python

Author : Francois Chollet
Publisher : Simon and Schuster
ISBN 13 : 1638352046
Total Pages : 597 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Deep Learning with Python by : Francois Chollet

Download or read book Deep Learning with Python written by Francois Chollet and published by Simon and Schuster. This book was released on 2017-11-30 with total page 597 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-human accuracy. We went from machines that couldn't beat a serious Go player, to defeating a world champion. Behind this progress is deep learning—a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications. About the Book Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects. What's Inside Deep learning from first principles Setting up your own deep-learning environment Image-classification models Deep learning for text and sequences Neural style transfer, text generation, and image generation About the Reader Readers need intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required. About the Author François Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does deep-learning research, with a focus on computer vision and the application of machine learning to formal reasoning. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others. Table of Contents PART 1 - FUNDAMENTALS OF DEEP LEARNING What is deep learning? Before we begin: the mathematical building blocks of neural networks Getting started with neural networks Fundamentals of machine learning PART 2 - DEEP LEARNING IN PRACTICE Deep learning for computer vision Deep learning for text and sequences Advanced deep-learning best practices Generative deep learning Conclusions appendix A - Installing Keras and its dependencies on Ubuntu appendix B - Running Jupyter notebooks on an EC2 GPU instance

Time Series for Data Scientists

Author : Juana Sanchez
Publisher : Cambridge University Press
ISBN 13 : 1108950175
Total Pages : 478 pages
Book Rating : 4.1/5 (89 download)

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Book Synopsis Time Series for Data Scientists by : Juana Sanchez

Download or read book Time Series for Data Scientists written by Juana Sanchez and published by Cambridge University Press. This book was released on 2023-05-11 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn by doing with this user-friendly introduction to time series data analysis in R. This book explores the intricacies of managing and cleaning time series data of different sizes, scales and granularity, data preparation for analysis and visualization, and different approaches to classical and machine learning time series modeling and forecasting. A range of pedagogical features support students, including end-of-chapter exercises, problems, quizzes and case studies. The case studies are designed to stretch the learner, introducing larger data sets, enhanced data management skills, and R packages and functions appropriate for real-world data analysis. On top of providing commented R programs and data sets, the book's companion website offers extra case studies, lecture slides, videos and exercise solutions. Accessible to those with a basic background in statistics and probability, this is an ideal hands-on text for undergraduate and graduate students, as well as researchers in data-rich disciplines

Operations Research Proceedings 2012

Author : Stefan Helber
Publisher : Springer Science & Business Media
ISBN 13 : 3319007955
Total Pages : 577 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Operations Research Proceedings 2012 by : Stefan Helber

Download or read book Operations Research Proceedings 2012 written by Stefan Helber and published by Springer Science & Business Media. This book was released on 2013-11-27 with total page 577 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains selected papers presented at the "International Annual Conference of the German Operations Research Society (OR2012)" which was held September 4 -7, 2012 at the Leibniz Universität Hannover, Germany. The international conference, which also serves as the annual meeting of the German Operations Research Society (GOR), attracted more than 500 participants from more than 39 countries. Special attention at the conference was given to the three topics "Energy, Markets and Mobility". The OR2012 conference has addressed these topics from an OR perspective, treating them not only in isolation, but also with respect to their numerous and exciting interconnections, such as new energy for new mobility concepts and new market mechanisms for sustainable energy production to name but a few. The proceedings show that this conference topic is an important and promising area to apply Operations Research. The book also contains numerous papers addressing the full scope of fields in Operations Research.

Forecasting

Author : Spyros G. Makridakis
Publisher : John Wiley & Sons
ISBN 13 :
Total Pages : 748 pages
Book Rating : 4.:/5 (89 download)

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Book Synopsis Forecasting by : Spyros G. Makridakis

Download or read book Forecasting written by Spyros G. Makridakis and published by John Wiley & Sons. This book was released on 1978 with total page 748 pages. Available in PDF, EPUB and Kindle. Book excerpt: "A Wiley/Hamilton publication." Includes bibliographies and index.

Modeling and Dynamics of Infectious Diseases

Author : Zhien Ma
Publisher : World Scientific
ISBN 13 : 9814261254
Total Pages : 355 pages
Book Rating : 4.8/5 (142 download)

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Book Synopsis Modeling and Dynamics of Infectious Diseases by : Zhien Ma

Download or read book Modeling and Dynamics of Infectious Diseases written by Zhien Ma and published by World Scientific. This book was released on 2009 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a systematic introduction to the fundamental methods and techniques and the frontiers of ? along with many new ideas and results on ? infectious disease modeling, parameter estimation and transmission dynamics. It provides complementary approaches, from deterministic to statistical to network modeling; and it seeks viewpoints of the same issues from different angles, from mathematical modeling to statistical analysis to computer simulations and finally to concrete applications.