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Special issue on "Genetic Fuzzy Systems: Recent Developments and Future Directions"

Jorge Casillas, Brian Carse
2008 Soft Computing - A Fusion of Foundations, Methodologies and Applications  
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

Yanbin Li, Gang Lei, Gerd Bramerdorfer, Sheng Peng, Xiaodong Sun, Jianguo Zhu
2021 Applied Sciences  
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

Nusrat Rouf, Majid Bashir Malik, Tasleem Arif, Sparsh Sharma, Saurabh Singh, Satyabrata Aich, Hee-Cheol Kim
2021 Electronics  
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

Ankit Thakkar, Kinjal Chaudhari
2020 Information Fusion  
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]

S. Chakraverty, Deepti Moyi Sahoo
2016 Computational Methods in Applied Sciences  
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

Yasar Becerikli
2004 Neural computing & applications (Print)  
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

Adrian Rubio Solis, George Panoutsos
2013 Applied Soft Computing  
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

Mohammad Khaleel, Rahib Abiyev, Idoko John
2017 International Journal of Advanced Computer Science and Applications  
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

Pejman Niksaz, Ali mohammad Latif
2014 International Journal of Information Technology and Computer Science  
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]

Fan Liu, Meng Joo
2010 New Trends in Technologies: Control, Management, Computational Intelligence and Network Systems  
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

Jie Hu, Akshi Kumar
2022 Computational Intelligence and Neuroscience  
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

Amit Kumar Batar, Teiji Watanabe
2021 ISPRS International Journal of Geo-Information  
(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]

Alexandr A. Ezhov, Dan Ventura
2000 Studies in Fuzziness and Soft Computing  
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

Bram Bulte, Arda Tezcan
2019 Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics  
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

Philippe Vroman, Ludovic Koehl, Xianyi Zeng, Ting Chen
2008 International Journal of Computational Intelligence Systems  
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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