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Special issue on "Genetic Fuzzy Systems: Recent Developments and Future Directions"
2008
Soft Computing - A Fusion of Foundations, Methodologies and Applications
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We sincerely thank Vincenzo Loia, Co-Editor-in-Chief of the Soft Computing journal, and Francisco Herrera, Area Editor of ''Genetic Algorithms and Genetic Fuzzy Systems'' in this journal, for providing ...
This edition process has been developed under the support of the EUSFLAT working group on ''Genetic Fuzzy Systems'' coordinated by the guest editors. ...
are proposed by successfully revisiting some open issues and some future directions are shown as examples of the imminent new issues that are coming. ...
doi:10.1007/s00500-008-0358-0
fatcat:vi6stqg3urffbpayassamgsdh4
Machine Learning for Design Optimization of Electromagnetic Devices: Recent Developments and Future Directions
2021
Applied Sciences
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as future directions for design optimization of electromagnetic devices. ...
First, the recent advances in multi-objective, multidisciplinary, multilevel, topology, fuzzy, and robust design optimization of electromagnetic devices are overviewed. ...
Fuzzy programming has been developed and widely used to handle optimization problems with fuzzy parameters and constraints [117, 118] . ...
doi:10.3390/app11041627
fatcat:jtijw5lngzhcpbqvs47qc5htuq
Stock Market Prediction Using Machine Learning Techniques: A Decade Survey on Methodologies, Recent Developments, and Future Directions
2021
Electronics
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Many analysts and researchers have developed tools and techniques that predict stock price movements and help investors in proper decision-making. ...
The study would be helpful for emerging researchers to understand the basics and advancements of this emerging area, and thus carry-on further research in promising directions. ...
The FIS (Fuzzy Inference Systems) apply rules to fuzzy sets and then apply de-fuzzification to give crisp outputs for decision making [26] . ...
doi:10.3390/electronics10212717
fatcat:cfvbgrcnn5hpfo276fquqwsfxa
Fusion in stock market prediction: A decade survey on the necessity, recent developments, and potential future directions
2020
Information Fusion
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Based on our surveyed articles, we provide potential future directions and concluding remarks on the significance of applying fusion in stock market. ...
Investment in a financial market is aimed at getting higher benefits; this complex market is influenced by a large number of events wherein the prediction of future market dynamics is challenging. ...
Thakkar and K. ...
doi:10.1016/j.inffus.2020.08.019
pmid:32868979
pmcid:PMC7448965
fatcat:ji7va4kekjh4tgclotgg7na7sa
Fuzzy Neural Network Based Response of Uncertain System Subject to Earthquake Motions
[chapter]
2016
Computational Methods in Applied Sciences
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The primary background for the present study is to model Interval Artificial Neural Network (IANN) and to compute structural response of a structural system by training the model for Indian earthquakes ...
The above may give an idea about the safety of the structural system in case of future earthquakes. ...
Figs. 8(a) and 8
CONCLUSION This paper uses the powerful soft computing technique viz Interval Artificial Neural Network (IANN) to compute interval structural response of structural system subject ...
doi:10.1007/978-3-319-47798-5_13
fatcat:ldhavltmingefhrtfxvmu43tsa
On three intelligent systems: dynamic neural, fuzzy, and wavelet networks for training trajectory
2004
Neural computing & applications (Print)
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Intelligent systems, including neural networks (NNs), fuzzy logic (FL), and wavelet techniques, utilize the concepts of biological systems and human cognitive capabilities. ...
connectivity and dynamic neural, fuzzy, and wavelet processing units, called "neurons", "feurons", and "wavelons", respectively. ...
In only algebraic/feedforward neural, fuzzy, and wavelet networks, identification of its parameters is easy to compute [13, 39, 45, 50, 52, 69] . ...
doi:10.1007/s00521-004-0429-9
fatcat:6z4xyx5fprh2xobhozecctosqm
Granular computing neural-fuzzy modelling: A neutrosophic approach
2013
Applied Soft Computing
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such as Fuzzy Logic and Rough Sets. ...
In this paper we present a new framework for creating Granular Computing Neural-Fuzzy modelling structures via the use of Neutrosophic Logic to address the issue of uncertainty during the data granulation ...
Acknowledgements The authors would like to thank TATA Steel, Yorkshire UK for their help and in providing the heat treatment data. ...
doi:10.1016/j.asoc.2012.09.002
fatcat:67bo7vdcibfgnnygcrhm76tuuq
Intelligent Classification of Liver Disorder using Fuzzy Neural System
2017
International Journal of Advanced Computer Science and Applications
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For this purpose, fuzzy system and neural networks (FNS) are explored for the detection of liver disorders. The structure and learning algorithm of the FNS are described. ...
In this study, designed an intelligent model for liver disorders based on Fuzzy Neural System (FNS) models is considered. ...
Recently, Lale Ozyilmaz et al. explored a framework to examine hepatitis infections utilizing RBF Neural system and MLP in [4] . R. ...
doi:10.14569/ijacsa.2017.081204
fatcat:imrq3vmmgbamzfyolnzue5c6cy
Rainfall Events Evaluation Using Adaptive Neural-Fuzzy Inference System
2014
International Journal of Information Technology and Computer Science
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We are interested in rainfall events evaluation by applying adaptive neural-fuzzy inference System. ...
Four parameters: Temperature, relative humidity, total cloud cover and due point are the input variables for our model, each has 121 membership functions. ...
Artificial intelligence includes several branches like Expert Systems (ESs), Artificial Neural Networks (ANNs), Adaptive Neural-Fuzzy Inference System (ANFIS), Genetic Algorithms (GA) and Fuzzy Logic ( ...
doi:10.5815/ijitcs.2014.09.06
fatcat:ilfs2sivr5dd5ceepw37mxfuxm
Development of Fuzzy Neural Networks: Current Framework and Trends
[chapter]
2010
New Trends in Technologies: Control, Management, Computational Intelligence and Network Systems
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Fuzzy neural network (FNN) system is one of the most successful and visible directions of that effort. ...
Conclusions and future work In this chapter, the development of fuzzy neural networks has been reviewed and the main issues for designing fuzzy neural networks including growing and pruning criteria and ...
The widespread development and distribution of electricity and clean water, automobiles and airplanes, radio and television, spacecraft and lasers, antibiotics and medical imaging, computers and the Internet ...
doi:10.5772/10409
fatcat:xtye5ruiibcybhbwnqsgojnkki
Research on Robot Fuzzy Neural Network Motion System Based on Artificial Intelligence
2022
Computational Intelligence and Neuroscience
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fuzzy neural network online, and the stability of the system is proved by using Lyapunov's stability theorem. ...
This controller has a parallel structure and contains an interval type-II fuzzy neural network and a conventional PD controller. ...
Fuzzy Neural Network Motion System for Robot with Artificial Intelligence
Robot Motion System Design. ...
doi:10.1155/2022/4347772
pmid:35186062
pmcid:PMC8849933
fatcat:esnng4xbmfhs5efsanpjazwrju
Landslide Susceptibility Mapping and Assessment Using Geospatial Platforms and Weights of Evidence (WoE) Method in the Indian Himalayan Region: Recent Developments, Gaps, and Future Directions
2021
ISPRS International Journal of Geo-Information
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(GIS) environment at the district level; and (3) to provide a comprehensive understanding of recent developments, gaps, and future directions related to landslide inventory, susceptibility mapping, and ...
landslide inventory map using geospatial platforms in the data-scarce environment; (2) to evaluate the landslide susceptibility map using weights of evidence (WoE) method in the Geographical Information System ...
This study contributes to the Global Land Programme (GLP), a global research project of Future Earth.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/ijgi10030114
fatcat:nefoau474bef3lixqafkfmc2em
Quantum Neural Networks
[chapter]
2000
Studies in Fuzziness and Soft Computing
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This chapter outlines the research, development and perspectives of quantum neural networks -a burgeoning new field which integrates classical neurocomputing with quantum computation [1] . ...
It is argued that the study of quantum neural networks may give us both new undestanding of brain function as well as unprecedented possibilities in creating new systems for information processing, including ...
We also acknowledge useful discussions with Mitja Perus, Tony Martinez, Ron Chrisley, Dan Cutting, Elizabeth Behrman, and Subhash Kak on various aspects of quantum neural computation. ...
doi:10.1007/978-3-7908-1856-7_11
fatcat:p3oyz5ansra4xhvtpv6tfekpyi
Neural Fuzzy Repair: Integrating Fuzzy Matches into Neural Machine Translation
2019
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
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We propose and test two methods for augmenting NMT training data with fuzzy TM matches. ...
Tests on the DGT-TM data set for two language pairs show consistent and substantial improvements over a range of baseline systems. ...
More recently, with the rise of NMT, researchers focused on ways to incorporate TM information in neural MT architectures. ...
doi:10.18653/v1/p19-1175
dblp:conf/acl/BulteT19
fatcat:o2wgka2t25bnjavzi2olzwzhue
Designing Structural Parameters of Nonwovens Using Fuzzy Logic and Neural Networks
2008
International Journal of Computational Intelligence Systems
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In this paper, a computer aided system for designing nonwoven materials is presented. ...
In this criterion, fuzzy logic is used to establish a good compromise or a fusion between these two uncertain and incomplete information sources. ...
The aim of our project is to develop a design support system for product designers using fuzzy logic and neural networks. ...
doi:10.2991/ijcis.2008.1.4.5
fatcat:gweyae6jk5eota3j2deff37o2q
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