Application Of Arima And Garch Models In Forecasting Crude Oil Prices
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| Author | : Chris Chatfield |
| Publisher | : CRC Press |
| Total Pages | : 281 |
| Release | : 2000-10-25 |
| Genre | : Business & Economics |
| ISBN | : 1420036203 |
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
| Author | : Jiuping Xu |
| Publisher | : Springer |
| Total Pages | : 1752 |
| Release | : 2018-06-25 |
| Genre | : Technology & Engineering |
| ISBN | : 3319933515 |
This proceedings book is divided in 2 Volumes and 8 Parts. Part I is dedicated to Decision Support System, which is about the information system that supports business or organizational decision-making activities; Part II is on Computing Methodology, which is always used to provide the most effective algorithm for numerical solutions of various modeling problems; Part III presents Information Technology, which is the application of computers to store, study, retrieve, transmit and manipulate data, or information in the context of a business or other enterprise; Part IV is dedicated to Data Analysis, which is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making; Part V presents papers on Operational Management, which is about the plan, organization, implementation and control of the operation process; Part VI is on Project Management, which is about the initiating, planning, executing, controlling, and closing the work of a team to achieve specific goals and meet specific success criteria at the specified time in the field of engineering; Part VII presents Green Supply Chain, which is about the management of the flow of goods and services based on the concept of “low-carbon”; Part VIII is focused on Industry Strategy Management, which refers to the decision-making and management art of an industry or organization in a long-term and long-term development direction, objectives, tasks and policies, as well as resource allocation.
| Author | : Wei-Chiang Hong |
| Publisher | : MDPI |
| Total Pages | : 262 |
| Release | : 2020-04-01 |
| Genre | : Computers |
| ISBN | : 3039283642 |
Accurate energy forecasting is important to facilitate the decision-making process in order to achieve higher efficiency and reliability in power system operation and security, economic energy use, contingency scheduling, the planning and maintenance of energy supply systems, and so on. In recent decades, many energy forecasting models have been continuously proposed to improve forecasting accuracy, including traditional statistical models (e.g., ARIMA, SARIMA, ARMAX, multi-variate regression, exponential smoothing models, Kalman filtering, Bayesian estimation models, etc.) and artificial intelligence models (e.g., artificial neural networks (ANNs), knowledge-based expert systems, evolutionary computation models, support vector regression, etc.). Recently, due to the great development of optimization modeling methods (e.g., quadratic programming method, differential empirical mode method, evolutionary algorithms, meta-heuristic algorithms, etc.) and intelligent computing mechanisms (e.g., quantum computing, chaotic mapping, cloud mapping, seasonal mechanism, etc.), many novel hybrid models or models combined with the above-mentioned intelligent-optimization-based models have also been proposed to achieve satisfactory forecasting accuracy levels. It is important to explore the tendency and development of intelligent-optimization-based modeling methodologies and to enrich their practical performances, particularly for marine renewable energy forecasting.
| Author | : Abd-Razak Ahmad |
| Publisher | : Springer |
| Total Pages | : 317 |
| Release | : 2016-11-24 |
| Genre | : Education |
| ISBN | : 9811027722 |
This proceedings volume consists of refereed papers presented at the Second International Conference on Computing, Mathematics and Statistics (iCMS 2015) held in Langkawi, Malaysia in November 2015. Divided into three sections - Computer Science, Mathematics and Statistics - the book includes both quantitative and qualitative research that confronts current societal issues. Within the main sections, the book also covers education based research works and the applications of computer and mathematical sciences in social science, business, industries and the life and hard sciences. Drawing on the theme Bridging Research Endeavor on Computing, Mathematics and Statistics, each of the conference papers are carefully selected and edited to cater to readers from diverse applied and social sciences backgrounds. The book allows for the contemplation and reflection on the possibility of the knowledge growth and knowledge sharing in building a better world for future generations.
| Author | : Rob Hyndman |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 362 |
| Release | : 2008-06-19 |
| Genre | : Mathematics |
| ISBN | : 3540719180 |
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.
| Author | : Fernando Sánchez Lasheras |
| Publisher | : MDPI |
| Total Pages | : 148 |
| Release | : 2020-12-29 |
| Genre | : Technology & Engineering |
| ISBN | : 303936619X |
Due to the increased capabilities of microprocessors and the advent of graphics processing units (GPUs) in recent decades, the use of machine learning methodologies has become popular in many fields of science and technology. This fact, together with the availability of large amounts of information, has meant that machine learning and Big Data have an important presence in the field of Energy. This Special Issue entitled “Predicting the Future—Big Data and Machine Learning” is focused on applications of machine learning methodologies in the field of energy. Topics include but are not limited to the following: big data architectures of power supply systems, energy-saving and efficiency models, environmental effects of energy consumption, prediction of occupational health and safety outcomes in the energy industry, price forecast prediction of raw materials, and energy management of smart buildings.
| Author | : Paulo Sérgio Abreu Freitas |
| Publisher | : EWG-DSS |
| Total Pages | : 265 |
| Release | : 2019-05-27 |
| Genre | : Business & Economics |
| ISBN | : 9898805447 |
| Author | : Aida Binti Mustapha |
| Publisher | : Springer Nature |
| Total Pages | : 464 |
| Release | : 2022-06-28 |
| Genre | : Science |
| ISBN | : 9811689032 |
This book presents peer-reviewed articles and recent advances on the potential applications of Science and Mathematics for future technologies, from the 7th International Conference on the Applications of Science and Mathematics (SCIEMATHIC 2021), held in Malaysia. It provides an insight about the leading trends in sustainable Science and Technology. The world is looking for sustainable solutions to problems more than ever. The synergistic approach of mathematicians, scientists and engineers has undeniable importance for future technologies. With this viewpoint, SCIEMATHIC 2021 has the theme “Quest for Sustainable Science and Mathematics for Future Technologies”. The conference brings together physicists, mathematicians, statisticians and data scientists, providing a platform to find sustainable solutions to major problems around us. The works presented here are suitable for professionals and researchers globally in making the world a better and sustainable place.
| Author | : Wei-Chiang Hong |
| Publisher | : MDPI |
| Total Pages | : 187 |
| Release | : 2018-10-22 |
| Genre | : Technology & Engineering |
| ISBN | : 3038972924 |
This book is a printed edition of the Special Issue "Kernel Methods and Hybrid Evolutionary Algorithms in Energy Forecasting" that was published in Energies
| Author | : James D. Hamilton |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 267 |
| Release | : 2013-06-29 |
| Genre | : Business & Economics |
| ISBN | : 3642511821 |
This book is a collection of state-of-the-art papers on the properties of business cycles and financial analysis. The individual contributions cover new advances in Markov-switching models with applications to business cycle research and finance. The introduction surveys the existing methods and new results of the last decade. Individual chapters study features of the U. S. and European business cycles with particular focus on the role of monetary policy, oil shocks and co movements among key variables. The short-run versus long-run consequences of an economic recession are also discussed. Another area that is featured is an extensive analysis of currency crises and the possibility of bubbles or fads in stock prices. A concluding chapter offers useful new results on testing for this kind of regime-switching behaviour. Overall, the book provides a state-of-the-art over view of new directions in methods and results for estimation and inference based on the use of Markov-switching time-series analysis. A special feature of the book is that it includes an illustration of a wide range of applications based on a common methodology. It is expected that the theme of the book will be of particular interest to the macroeconomics readers as well as econometrics professionals, scholars and graduate students. We wish to express our gratitude to the authors for their strong contributions and the reviewers for their assistance and careful attention to detail in their reports.
