A Neutrosophic Forecasting Model For Time Series Based On First Order State And Information Entropy Of High Order Fluctuation
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A Neutrosophic Forecasting Model For Time Series Based On First Order State And Information Entropy Of High Order Fluctuation
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Author : Hongjun Guan
language : en
Publisher: Infinite Study
Release Date :
A Neutrosophic Forecasting Model For Time Series Based On First Order State And Information Entropy Of High Order Fluctuation written by Hongjun Guan and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with Mathematics categories.
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.
A Forecasting Model Based On High Order Fluctuation Trends And Information Entropy
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Author : Hongjun Guan
language : en
Publisher: Infinite Study
Release Date :
A Forecasting Model Based On High Order Fluctuation Trends And Information Entropy written by Hongjun Guan and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with Mathematics categories.
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.
Entropy Application For Forecasting
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Author : Ana Jesus Lopez-Menendez
language : en
Publisher: MDPI
Release Date : 2020-12-29
Entropy Application For Forecasting written by Ana Jesus Lopez-Menendez and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-29 with Technology & Engineering categories.
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.
Forecasting Model Based On Neutrosophic Logical Relationship And Jaccard Similarity
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Author : Hongjun Guan
language : en
Publisher: Infinite Study
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Forecasting Model Based On Neutrosophic Logical Relationship And Jaccard Similarity written by Hongjun Guan and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with Mathematics categories.
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.
Symmetry Vol 9 Issue 10 2007 Special Issue Neutrosophic Theories Applied In Engineering
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Author : Florentin Smarandache
language : en
Publisher: Infinite Study
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Symmetry Vol 9 Issue 10 2007 Special Issue Neutrosophic Theories Applied In Engineering written by Florentin Smarandache and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
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.
A Forecasting Model Based On High Order Fluctuation Trends And Information Entropy
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Author : Hongjun Guan
language : en
Publisher: Infinite Study
Release Date :
A Forecasting Model Based On High Order Fluctuation Trends And Information Entropy written by Hongjun Guan and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with Mathematics categories.
This paper proposes a model based on logical rules abstracted from historical dynamic fluctuation trends and the corresponding inconsistencies.
A Refined Approach For Forecasting Based On Neutrosophic Time Series
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Author : Mohamed Abdel-Basset
language : en
Publisher: Infinite Study
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A Refined Approach For Forecasting Based On Neutrosophic Time Series written by Mohamed Abdel-Basset and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with Mathematics categories.
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.
Developments Of Artificial Intelligence Technologies In Computation And Robotics Proceedings Of The 14th International Flins Conference Flins 2020
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Author : Zhong Li
language : en
Publisher: World Scientific
Release Date : 2020-08-04
Developments Of Artificial Intelligence Technologies In Computation And Robotics Proceedings Of The 14th International Flins Conference Flins 2020 written by Zhong Li and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-04 with Technology & Engineering categories.
FLINS, an acronym introduced in 1994 and originally for Fuzzy Logic and Intelligent Technologies in Nuclear Science, is now extended into a well-established international research forum to advance the foundations and applications of computational intelligence for applied research in general and for complex engineering and decision support systems.The principal mission of FLINS is bridging the gap between machine intelligence and real complex systems via joint research between universities and international research institutions, encouraging interdisciplinary research and bringing multidiscipline researchers together.FLINS 2020 is the fourteenth in a series of conferences on computational intelligence systems.
A Novel Multi Criteria Decision Making Model For Building Material Supplier Selection Based On Entropy Ahp Weighted Topsis
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Author : Chun-Ho Chen
language : en
Publisher: Infinite Study
Release Date :
A Novel Multi Criteria Decision Making Model For Building Material Supplier Selection Based On Entropy Ahp Weighted Topsis written by Chun-Ho Chen and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with Mathematics categories.
The TOPSIS method is extended with entropy-AHP weights, and entropy-AHP weights are used instead of subjective weights. A novel decision-making model of TOPSIS integrated entropy-AHP weights is proposed to select the appropriate supplier. Finally, we take the selection of building material suppliers as an example and use sensitivity analysis to show that the combination of the TOPSIS method based on entropy-AHP weights can effectively select the appropriate supplier.