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A novel computation for predicting time series using fuzzy logical distance connectivity function and visibility graph theory
2020
Mathematical Modeling and Computing
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The visibility graph is a set of locations that lie in a line that can be interpreted as a graph-theoretical representation of a time series, while the fuzzy graph speaks about the connection between the ...
Therefore, to find the real values exactly, this paper introduces the Visibility graph by time series values (x t , y t ), (x u , y u ) along with the Fuzzy node values f 1 , f 2 , . . . , f n . ...
The depicted method is based on the multi-resolution analysis of the time-series by means of Wavelet decomposition and artificial neural networks. ...
doi:10.23939/mmc2020.01.014
fatcat:ma4ze7etazefnp4klknxuhkjzq
Time Series Forecasting Based on Complex Network Analysis
2019
IEEE Access
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In this paper, based on the analysis of complex network, a novel method is proposed for more accurate time series predictions. First, time series data are mapped into a network by visibility graph. ...
Time series forecasting, especially from the perspective of the network, has been a hot research topic. ...
In this paper, we propose a novel method for time series forecasting based on complex network analysis. Specifically, a time series is first transformed into a network by visibility graph. ...
doi:10.1109/access.2019.2906268
fatcat:txruoivbjjfspifgaf7iy5zdeq
Development of Temperature-based Weather Forecasting Models Using Neural Networks and Fuzzy Logic
2014
International Journal of Multimedia and Ubiquitous Engineering
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We propose computer-based models for weather forecasting based on temperature to predict the daily temperature using two techniques, artificial neural networks and fuzzy logic. ...
Dynamic modeling is used to represent a system over a time. ...
A novel method was developed to forecast temperature and the Taiwan Futures Exchange (TAIFEX), based on the two-factor high-order fuzzy time series [27] . ...
doi:10.14257/ijmue.2014.9.12.31
fatcat:awkwyrfnlfgmtjlkx6xj2h6hxe
Forecasting Production Values using Fuzzy Logic Interval based Partitioning in Different Intervals
2017
International Journal of Advanced Computer Science and Applications
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In the current paper, we use a fuzzy time series model and provide a more accurate result than the methods already existent. ...
have proposed a novel algorithm to make predictions easy. ...
Li, [30] put forth a generalised method for forecasting based on fuzzy time series model. Fuzzy time series concepts and definitions were invented and presented by Song & Chissom. ...
doi:10.14569/ijacsa.2017.080536
fatcat:xkleeaqtcbexrhm4auwekozpta
Application of Weighted Fuzzy Time Series Model to Forecast Epidemic Injuries
2020
Current Journal of Applied Science and Technology
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Methodology: We propose the use of weighted fuzzy time series techniques (WFTS) and weighted non-stationary fuzzy time series techniques (WNSFTS) to be compared with the classical Auto-Regressive Integrated ...
Conclusion: The use of Weighted Non Stationary Fuzzy Time Series (WNSFTS) in forecasting epidemic injuries problem can provide significantly better results because it is able to predict the infected cases ...
Fuzzy Time Series Forecasting Corona Statistics around the world and My health statistic to directly monitor cases globally and locally are modeled by a simple visibility graph. ...
doi:10.9734/cjast/2020/v39i2430875
fatcat:bwl5tpxfzbc4ligtjbtvs5yyiq
A Comparative Study and Analysis of Time Series Forecasting Techniques
2020
SN Computer Science
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The present paper covers and compares various forecasting algorithmic approaches and explores their limitations and usefulness for different types of time series data in different domains. ...
Time series data abound in many realistic domains. The proper study and analysis of time series data help to make important decisions. ...
There are three major stages in the analysis of the fuzzy logic-based time series forecasting. ...
doi:10.1007/s42979-020-00180-5
fatcat:xp6c5ek43zgtxkaqkgcgkobmdq
A Forecasting Model Based On Multi-Valued Neutrosophic Sets And Two-Factor, Third-Order Fuzzy Fluctuation Logical Relationships
2018
Zenodo
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In this paper, we propose a novel forecasting model based on multi-valued neutrosophic sets to find fluctuation rules and patterns of a time series. ...
Consequently, finding the inherent rules and patterns of a time series by eliminating disturbances without losing important details has long been a research hotspot. ...
A Novel Forecasting Model Based on Multi-Valued Neutrosophic Logical Relationships In this section, we present a novel fuzzy forecasting method based on multi-valued neutrosophic logical relationships ...
doi:10.5281/zenodo.1412407
fatcat:pmo6et3wnrdwvizjoccdqd47pe
A Forecasting Model Based on Multi-Valued Neutrosophic Sets and Two-Factor, Third-Order Fuzzy Fluctuation Logical Relationships
2018
Symmetry
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In this paper, we propose a novel forecasting model based on multi-valued neutrosophic sets to find fluctuation rules and patterns of a time series. ...
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. ...
A Novel Forecasting Model Based on Multi-Valued Neutrosophic Logical Relationships In this section, we present a novel fuzzy forecasting method based on multi-valued neutrosophic logical relationships ...
doi:10.3390/sym10070245
fatcat:aum74bjntrefzi4b3igjtnfusu
A visibility graph averaging aggregation operator
2014
Physica A: Statistical Mechanics and its Applications
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2013 pre-print arXiv:1311.4166v1 fatcat:4s6xyx7nijfmvmsaabdy4x6vsi
This proposed operator is based on the visibility graph which can convert a time series into a graph. The weights are obtained according to the importance of the data in the visibility graph. ...
In this paper, a new type of operator called visibility graph averaging (VGA) aggregation operator is proposed. ...
The proposed visibility graph averaging (VGA) operator is based on the visibility graph, hence, it conserves the time information likewise. ...
doi:10.1016/j.physa.2014.02.015
fatcat:l77dvhojn5ajjozvei667zhtgi
Numerical and Linguistic Prediction of Time Series With the Use of Fuzzy Cognitive Maps
2008
IEEE transactions on fuzzy systems
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INTRODUCTORY COMMENTS AND MOTIVATION T HIS paper proposes a novel application of fuzzy cognitive maps (FCMs) to time-series analysis. ...
Index Terms-Fuzzy cognitive maps (FCMs), fuzzy systems, linguistic prediction, prediction methods, time series. I. ...
Section II gives a brief survey of fuzzy-set-based methods for time-series prediction problems. ...
doi:10.1109/tfuzz.2007.902020
fatcat:7ecgtkazgfftnixdqy3efhmldu
Attacker Behaviour Forecasting Using Methods of Intelligent Data Analysis: A Comparative Review and Prospects
2020
Information
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Early detection of the security incidents and correct forecasting of the attack development is the basis for the efficient and timely response to cyber threats. ...
Usually, the "attacker profile" is a set of attacker's attributes—both inner such as motives and skills, and external such as existing financial support and tools used. ...
Techniques based on attack graph analysis.
2. Techniques based on hidden Markov model. 3 . Techniques based on fuzzy inference. 4 . ...
doi:10.3390/info11030168
fatcat:hhgj7dspynfwblsmblweq6bznm
Financial Time Series Forecasting with Deep Learning : A Systematic Literature Review: 2005-2019
[article]
2019
arXiv
pre-print
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Hence, our motivation in this paper is to provide a comprehensive literature review on DL studies for financial time series forecasting implementations. ...
Even though there is a growing interest in developing models for financial time series forecasting research, there is a lack of review papers that were solely focused on DL for finance. ...
Also, we decided to include algorithmic trading papers that were based on financial forecasting, but ignore the ones that did not have a time series forecasting component. ...
arXiv:1911.13288v1
fatcat:npvyhewuvvcvri4e43jwj3c45y
Fuzzy Cognitive Maps Optimization for Decision Making and Prediction
2020
Mathematics
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In the present paper, the main idea is to systematically create a nested structure, based on a fuzzy cognitive map (FCM), in which each element/concept at a higher map level is decomposed into another ...
as well as to determine the weights of these relationships on the basis of the available time series. ...
In Reference [10] , a novel approach based on FCMs and a granular fuzzy set-based model of inputs were proposed for realizing time series prediction at the linguistic and numerical levels. ...
doi:10.3390/math8112059
fatcat:2evdeefshbdrxaf7vo3du22cb4
ANN based method for improving gold price forecasting accuracy through modified gradient descent methods
2020
IAES International Journal of Artificial Intelligence (IJ-AI)
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The results of our study suggest that the forecasting efficiency improves considerably on applying the modified methods proposed by us. ...
Various local, global, political, psychological and economic factors make such a forecast a complex problem. ...
In our work we have proposed a few novel methods based on the classical GDM approach belonging to the ANN class and developed algorithms based on them on MATLAB platform. ...
doi:10.11591/ijai.v9.i1.pp46-57
fatcat:eqc3httiencazmtsqhntubq5va
A neuro-fuzzy modeling for the hydrological time series of floods of river indus of Pakistan
2019
International Journal of Hydrology
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A neuro-fuzzy modeling for the hydrological time series of floods of river indus of Pakistan. Int J Hydro. ...
Nowadays, Adaptive Neuro-Fuzzy Inference System (ANFIS) model which is widely used to analyze these hydrological time series data sets obtained from different gauge stations. ...
Non-linear time series forecasting These forecasting are to be made with the help of Neuro-fuzzy. ...
doi:10.15406/ijh.2019.03.00175
fatcat:ycnhj66nv5gwlcumwflaitnc74
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