Time series analysis via network science: Concepts and algorithms
There is nowadays a constant flux of data being generated and collected in all types of real
world systems. These data sets are often indexed by time, space, or both requiring …
world systems. These data sets are often indexed by time, space, or both requiring …
Visibility graph for time series prediction and image classification: a review
The analysis of time series and images is significant across different fields due to their
widespread applications. In the past few decades, many approaches have been developed …
widespread applications. In the past few decades, many approaches have been developed …
A new crude oil price forecasting model based on variational mode decomposition
Crude oil price prediction helps to get a better understanding of the global economic
situation. Recently, variational mode decomposition (VMD) is introduced into the field of …
situation. Recently, variational mode decomposition (VMD) is introduced into the field of …
A combined prediction model based on secondary decomposition and intelligence optimization for carbon emission
H Yang, M Wang, G Li - Applied Mathematical Modelling, 2023 - Elsevier
Accurate prediction of carbon emission is critical for the development of low-carbon
economy. However, most carbon emission prediction studies use a single model with low …
economy. However, most carbon emission prediction studies use a single model with low …
Identifying influential nodes in complex networks from global perspective
How to identify influential nodes in complex networks is an open issue. Several centrality
measures have been proposed to address this. But these studies concentrate only on only …
measures have been proposed to address this. But these studies concentrate only on only …
GMM: A generalized mechanics model for identifying the importance of nodes in complex networks
How to assess the importance of nodes in the network is an open question. There are many
ways to identify the importance of nodes in complex networks. However, these methods …
ways to identify the importance of nodes in complex networks. However, these methods …
Identifying node importance based on evidence theory in complex networks
H Mo, Y Deng - Physica A: Statistical Mechanics and its Applications, 2019 - Elsevier
How to identify influential nodes in complex networks is still an open issue. In this paper, a
new multi-evidence centrality is proposed based on evidence theory. The existing measures …
new multi-evidence centrality is proposed based on evidence theory. The existing measures …
Combination of evidential sensor reports with distance function and belief entropy in fault diagnosis
Y Dong, J Zhang, Z Li, Y Hu, Y Deng - International Journal of …, 2019 - univagora.ro
Although evidence theory has been applied in sensor data fusion, it will have unreasonable
results when handling highly conflicting sensor reports. To address the issue, an improved …
results when handling highly conflicting sensor reports. To address the issue, an improved …
A fuzzy interval time-series energy and financial forecasting model using network-based multiple time-frequency spaces and the induced-ordered weighted averaging …
Forecasting time series is an emerging topic in operational research. Existing time-series
models have limited prediction accuracy when faced with the characteristics of nonlinearity …
models have limited prediction accuracy when faced with the characteristics of nonlinearity …
Probability transform based on the ordered weighted averaging and entropy difference
L Pan, Y Deng - International Journal of Computers Communications & …, 2020 - univagora.ro
Dempster-Shafer evidence theory can handle imprecise and unknown information, which
has attracted many people. In most cases, the mass function can be translated into the …
has attracted many people. In most cases, the mass function can be translated into the …