A Neutrosophic Forecasting Model For Time Series Based On First Order State And Information Entropy Of High Order Fluctuation PDF Download
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Author | : Hongjun Guan |
Publisher | : Infinite Study |
Total Pages | : 18 |
Release | : |
Genre | : Mathematics |
ISBN | : |
Download A Neutrosophic Forecasting Model for Time Series Based on First-Order State and Information Entropy of High-Order Fluctuation Book in PDF, ePub and Kindle
In time series forecasting, information presentation directly affects prediction efficiency. Most existing time series forecasting models follow logical rules according to the relationships between neighboring states, without considering the inconsistency of fluctuations for a related period. In this paper, we propose a new perspective to study the problem of prediction, in which inconsistency is quantified and regarded as a key characteristic of prediction rules. First, a time series is converted to a fluctuation time series by comparing each of the current data with corresponding previous data.
Author | : Hongjun Guan |
Publisher | : Infinite Study |
Total Pages | : 15 |
Release | : |
Genre | : Mathematics |
ISBN | : |
Download A Forecasting Model Based on High-Order Fluctuation Trends and Information Entropy Book in PDF, ePub and Kindle
Most existing high-order prediction models abstract logical rules that are based on historical discrete states without considering historical inconsistency and fluctuation trends. In fact, these two characteristics are important for describing historical fluctuations. This paper proposes a model based on logical rules abstracted from historical dynamic fluctuation trends and the corresponding inconsistencies. In the logical rule training stage, the dynamic trend states of up and down are mapped to the two dimensions of truth-membership and false-membership of neutrosophic sets, respectively. Meanwhile, information entropy is employed to quantify the inconsistency of a period of history, which is mapped to the indeterminercy-membership of the neutrosophic sets. In the forecasting stage, the similarities among the neutrosophic sets are employed to locate the most similar left side of the logical relationship. Therefore, the two characteristics of the fluctuation trends and inconsistency assist with the future forecasting. The proposed model extends existing high-order fuzzy logical relationships (FLRs) to neutrosophic logical relationships (NLRs). When compared with traditional discrete high-order FLRs, the proposed NLRs have higher generality and handle the problem caused by the lack of rules. The proposed method is then implemented to forecast Taiwan Stock Exchange CapitalizationWeighted Stock Index and Heng Seng Index. The experimental conclusions indicate that the model has stable prediction ability for different data sets. Simultaneously, comparing the prediction error with other approaches also proves that the model has outstanding prediction accuracy and universality.
Author | : Mohamed Abdel-Basset |
Publisher | : Infinite Study |
Total Pages | : 23 |
Release | : |
Genre | : Mathematics |
ISBN | : |
Download A Refined Approach for Forecasting Based on Neutrosophic Time Series Book in PDF, ePub and Kindle
This research introduces a neutrosophic forecasting approach based on neutrosophic time series (NTS). Historical data can be transformed into neutrosophic time series data to determine their truth, indeterminacy and falsity functions. The basis for the neutrosophication process is the score and accuracy functions of historical data. In addition, neutrosophic logical relationship groups (NLRGs) are determined and a deneutrosophication method for NTS is presented. The objective of this research is to suggest an idea of first-and high-order NTS. By comparing our approach with other approaches, we conclude that the suggested approach of forecasting gets better results compared to the other existing approaches of fuzzy, intuitionistic fuzzy, and neutrosophic time. series.
Author | : Hongjun Guan |
Publisher | : Infinite Study |
Total Pages | : 18 |
Release | : |
Genre | : |
ISBN | : |
Download A Forecasting Model Based on Multi-Valued Neutrosophic Sets and Two-Factor, Third-Order Fuzzy Fluctuation Logical Relationships Book in PDF, ePub and Kindle
Making predictions according to historical values has long been regarded as common practice by many researchers. However, forecasting solely based on historical values could lead to inevitable over-complexity and uncertainty due to the uncertainties inside, and the random influence outside, of the data.
Author | : Ana Jesus Lopez-Menendez |
Publisher | : MDPI |
Total Pages | : 200 |
Release | : 2020-12-29 |
Genre | : Technology & Engineering |
ISBN | : 3039364871 |
Download Entropy Application for Forecasting Book in PDF, ePub and Kindle
This book shows the potential of entropy and information theory in forecasting, including both theoretical developments and empirical applications. The contents cover a great diversity of topics, such as the aggregation and combination of individual forecasts, the comparison of forecasting performance, and the debate concerning the tradeoff between complexity and accuracy. Analyses of forecasting uncertainty, robustness, and inconsistency are also included, as are proposals for new forecasting approaches. The proposed methods encompass a variety of time series techniques (e.g., ARIMA, VAR, state space models) as well as econometric methods and machine learning algorithms. The empirical contents include both simulated experiments and real-world applications focusing on GDP, M4-Competition series, confidence and industrial trend surveys, and stock exchange composite indices, among others. In summary, this collection provides an engaging insight into entropy applications for forecasting, offering an interesting overview of the current situation and suggesting possibilities for further research in this field.
Author | : Hongjun Guan |
Publisher | : Infinite Study |
Total Pages | : 16 |
Release | : |
Genre | : Mathematics |
ISBN | : |
Download Forecasting Model Based on Neutrosophic Logical Relationship and Jaccard Similarity Book in PDF, ePub and Kindle
The daily fluctuation trends of a stock market are illustrated by three statuses: up, equal, and down. These can be represented by a neutrosophic set which consists of three functions—truth-membership, indeterminacy-membership, and falsity-membership. In this paper, we propose a novel forecasting model based on neutrosophic set theory and the fuzzy logical relationships between the status of historical and current values.
Author | : Hongjun Guan |
Publisher | : Infinite Study |
Total Pages | : 21 |
Release | : |
Genre | : Mathematics |
ISBN | : |
Download Neutrosophic soft sets forecasting model for multi-attribute time series Book in PDF, ePub and Kindle
Traditional time series forecasting models mainly assume a clear and definite functional relationship between historical values and current/future values of a dataset. In this paper, we extended current model by generating multi-attribute forecasting rules based on consideration of combining multiple related variables. In this model, neutrosophic soft sets (NSSs) are employed to represent historical statues of several closely related attributes in stock market such as volumes, stock market index and daily amplitudes.
Author | : Hongjun Guan |
Publisher | : Infinite Study |
Total Pages | : 16 |
Release | : |
Genre | : |
ISBN | : |
Download Forecasting Model Based on Neutrosophic Logical Relationship and Jaccard Similarity Book in PDF, ePub and Kindle
The daily fluctuation trends of a stock market are illustrated by three statuses: up, equal, and down. These can be represented by a neutrosophic set which consists of three functions—truth-membership, indeterminacy-membership, and falsity-membership.
Author | : Florentin Smarandache |
Publisher | : Infinite Study |
Total Pages | : 210 |
Release | : |
Genre | : |
ISBN | : |
Download Symmetry, vol. 9, issue 10 / 2007 - Special Issue: Neutrosophic Theories Applied in Engineering Book in PDF, ePub and Kindle
This Special Issue presents original research papers that report on state-of-the-art and recent advancements in neutrosophic sets and logic in soft computing, artificial intelligence, big and small data mining, decision making problems, and practical achievements.
Author | : Kamil Feridun Turkman |
Publisher | : Springer |
Total Pages | : 255 |
Release | : 2014-09-29 |
Genre | : Mathematics |
ISBN | : 3319070282 |
Download Non-Linear Time Series Book in PDF, ePub and Kindle
This book offers a useful combination of probabilistic and statistical tools for analyzing nonlinear time series. Key features of the book include a study of the extremal behavior of nonlinear time series and a comprehensive list of nonlinear models that address different aspects of nonlinearity. Several inferential methods, including quasi likelihood methods, sequential Markov Chain Monte Carlo Methods and particle filters, are also included so as to provide an overall view of the available tools for parameter estimation for nonlinear models. A chapter on integer time series models based on several thinning operations, which brings together all recent advances made in this area, is also included. Readers should have attended a prior course on linear time series, and a good grasp of simulation-based inferential methods is recommended. This book offers a valuable resource for second-year graduate students and researchers in statistics and other scientific areas who need a basic understanding of nonlinear time series.