The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON COMPUTERS
Transactions ID Number: 54-194
Full Name: Swati Aggarwal
Position: Assistant Professor
Age: ON
Sex: Female
Address: Department of Computer Science Engineering, ITM University, HUDA Sector 23-A
Country: INDIA
Tel:
Tel prefix:
Fax:
E-mail address: swati1178@gmail.com
Other E-mails:
Title of the Paper: Possible Neuro-Neutrosophic Integration
Authors as they appear in the Paper: A.Q.Ansari, Ranjit Biswas,Swati Aggarwal
Email addresses of all the authors: aqansari@ieee.org,ranjitbiswas@yahoo.com,swati1178@gmail.com
Number of paper pages: 11
Abstract: Quite recently, Neutrosophic Logic was proposed by Florentine Smarandache which is based on non-standard analysis that was given by Abraham Robinson in 1960s [1]. Neutrosophic Logic was developed to represent mathematical model of uncertainty, vagueness, ambiguity, imprecision, undefined, unknown, incompleteness, inconsistency, redundancy, contradiction. Neutrosophic logic is much more generalised and capable of handling and representing uncertainty, indeterminacy and gaps in information as compared to fuzzy logic. The advantage of neutrosophic logic is clearly evident in the systems developed that utilize neutrosophic logic. Further augmentation in the adaptation and learning capabilities of neutrosophic systems can be done using neural networks and genetic algorithms. Neural networks have been extensively researched and hybridised with the fuzzy systems so as to impart learning and adaptation abilities to the hybridised structures. As is evident that neutrosophic!
logic is an extension to fuzzy logic, so it is proposed in this paper to give extension to the existing neuro-fuzzy systems in the form of neuro-neutrosophic systems. It is expected that the proposed hybridisation models: neuro-neutrosophic systems would indeed inherit advantage of both the complementary techniques and they would be much more tolerant in it's working as compared to neuro-fuzzy systems.
Keywords: Neutrosophic -neural networks (NNN), neural-neutrosophic system (NNS), Neutrosophic inference system (NIS), Neuro-Neutrosophic integration, Mamdani neuro-neutrosophic system (MNNS), Sugeno neuro-neutrosophic system (SNNS).
EXTENSION of the file: .pdf
Special (Invited) Session: Applied Soft Computing
Organizer of the Session: Professor Les Sztandera
How Did you learn about congress: Neutrosophic logic ,Neural networks
IP ADDRESS: 203.115.107.71
