Nonsynaptic Backpropagation Learning of Interval-valued Long-term Cognitive Networks

Author(s):  
Mabel Frias ◽  
Gonzalo Napoles ◽  
Koen Vanhoof ◽  
Yaima Filiberto ◽  
Rafael Bello
2021 ◽  
Vol 548 ◽  
pp. 461-478 ◽  
Author(s):  
Gonzalo Nápoles ◽  
Agnieszka Jastrzębska ◽  
Yamisleydi Salgueiro

2021 ◽  
pp. 1-17
Author(s):  
Shunsheng Guo ◽  
Yuji Gao ◽  
Jun Guo ◽  
Zhijie Yang ◽  
Baigang Du ◽  
...  

With the aggravation of market competition, strategic supplier is becoming more and more critical for the success of manufacturing enterprises. Suppler selection, being the critical and foremost activity must ensure that selected suppliers are capable of supporting the long-term development of organizations. Hence, strategic supplier selection must be restructures considering the long-term relationships and prospects for sustainable cooperation. This paper proposes a novel multi-stage multi-attribute group decision making method under an interval-valued q-rung orthopair fuzzy linguistic set (IVq-ROFLS) environment considering the decision makers’ (DMs) psychological state in the group decision-making process. First, the initial comprehensive fuzzy evaluations of DMs are represented as IVq-ROFLS. Subsequently, two new operators are proposed for aggregating different stages and DMs’ preferences respectively by extending generalized weighted averaging (GWA) to IVq-ROFLS context. Later, a new hamming distance based linear programming method based on entropy measure and score function is introduced to evaluate the unknown criteria weights. Additionally, the Euclidean distance is employed to compute the gain and loss matrix, and objects are prioritized by extending the popular Prospect theory (PT) method to the IVq-ROFLS context. Finally, the practical use of the proposed decision framework is validated by using a strategic supplier selection problem, as well as the effectiveness and applicability of the framework are discussed by using comparative analysis with other methods.


Telecom ◽  
2021 ◽  
Vol 2 (4) ◽  
pp. 518-535
Author(s):  
Aaron Chen ◽  
Jeffrey Law ◽  
Michal Aibin

Much research effort has been conducted to introduce intelligence into communication networks in order to enhance network performance. Communication networks, both wired and wireless, are ever-expanding as more devices are increasingly connected to the Internet. This survey introduces machine learning and the motivations behind it for creating cognitive networks. We then discuss machine learning and statistical techniques to predict future traffic and classify each into short-term or long-term applications. Furthermore, techniques are sub-categorized into their usability in Local or Wide Area Networks. This paper aims to consolidate and present an overview of existing techniques to stimulate further applications in real-world networks.


2020 ◽  
Vol 31 (3) ◽  
pp. 865-875 ◽  
Author(s):  
Gonzalo Nopoles ◽  
Frank Vanhoenshoven ◽  
Rafael Falcon ◽  
Koen Vanhoof
Keyword(s):  

2020 ◽  
Vol 206 ◽  
pp. 106372 ◽  
Author(s):  
Gonzalo Nápoles ◽  
Isel Grau ◽  
Yamisleydi Salgueiro

2021 ◽  
Author(s):  
G. Nápoles ◽  
I. Grau ◽  
L. Concepción ◽  
Yamisleydi Salgueiro
Keyword(s):  

Symmetry ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 881
Author(s):  
István Á. Harmati

Fuzzy-rough cognitive networks (FRCNs) are interpretable recurrent neural networks, primarily designed for solving classification problems. Their structure is simple and transparent, while the performance is comparable to the well-known black-box classifiers. Although there are many applications on fuzzy cognitive maps and recently for FRCNS, only a very limited number of studies discuss the theoretical issues of these models. In this paper, we examine the behaviour of FRCNs viewing them as discrete dynamical systems. It will be shown that their mathematical properties highly depend on the size of the network, i.e., there are structural differences between the long-term behaviour of FRCN models of different size, which may influence the performance of these modelling tools.


Author(s):  
Richar Sosa ◽  
Alejandro Alfonso ◽  
Gonzalo Napoles ◽  
Rafael Bello ◽  
Koen Vanhoof ◽  
...  

Author(s):  
Yadong Hao ◽  
Shurong Jiang ◽  
Fusheng Yu ◽  
Wenyi Zeng ◽  
Xiao Wang ◽  
...  

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