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Subject index to volume 2

1988 International Journal of Approximate Reasoning  
uncertainty and temporal relationships in, 337 Autonomous agents, centrality of, in theories of action under uncertainty, 303-326 Backward chaining, with fuzzy goals and rules, 108 Bayes belief network  ...  , construction of, 337 Bayes' rule of conditioning, 328 Bayesian analysis, decision tree induction system and, 330 Bayesian approach, heuristic, to knowledge acquisition, application to analysis of tissuetype  ...  systems, 273-278 Knowledge networks, combined and adaptive, hidden patterns in, 377-393 Learning concepts, logical aspects of, 349-364 in knowledge-based systems, with imperfect teacher, 111-112  ... 
doi:10.1016/0888-613x(88)90114-4 fatcat:rj373wy2pzff3d3otqdhxs2gca

Subject index, volume 13, 1995

1995 International Journal of Approximate Reasoning  
weight averaging operators, 13:359 Fuzzy logic, neural nets, soft computing, preface to spcial issue on conference on, 13:247 Fuzzy modeling, truth space approach, 13:249 International Journal  ...  Stability, neurofuzzy controller design, 13:269 Symbolic approximate reasoning, resolution-based system for, 13:201 Symbolic probabilistic inference, 13:61 Truth space approach, 13:249 Uncertainty reasoning  ... 
doi:10.1016/0888-613x(95)90015-w fatcat:vboipj22q5ayxgq5iuoe3jx6de

Philippe Smets (1938–2005)

Hughes Bersini, Thierry Denœux, Didier Dubois, Henri Prade
2006 International Journal of Approximate Reasoning  
IEEE Transactions on Fuzzy Systems, the International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, the Journal of Applied Non Classical Logics, and Mathware and Soft Computing.  ...  He served on the editorial boards of many journals including the International Journal of Approximate Reasoning, the Journal of Logic and Computation, Information Sciences, Fuzzy Sets and Systems, the  ... 
doi:10.1016/j.ijar.2006.02.002 fatcat:3lrpvot3krhp7bfwm6s3xt2gc4

ROBUST FUZZY NEURO SYSTEM FOR BIG DATA ANALYTICS

Aman Taneja
2017 International Journal of Advanced Research in Computer Science  
tendency to get the results by relating knowledge representation, uncertainty and modelling the key feature of big data to provide a superlative solution.  ...  It also presents uncertainty issues related to Big Data for which the solution we provided by combining fuzzy and neural network concepts to assemble a new intelligent system ANFIS that has brought together  ...  CONCLUSION Fuzzy Inference system is a framework based on if-then rules and fuzzy reasoning. Neural network is based on feed forward and approximation method.  ... 
doi:10.26483/ijarcs.v8i7.4164 fatcat:wfmn5s2vwjcfvfgw2sqn4wujkq

Fuzzy Logic Model for the Prediction of Traffic Volume in Week Days

Bharti Sharma, Vinod Kumar Katiyar, Arvind Kumar Gupta
2014 International Journal of Computer Applications  
Prediction results show that the proposed fuzzy logic system produces more accurate and stable traffic volume predictions.  ...  In this paper, 'day' of a week and 'time' of a day are taken as inputs for proposed model and the output will be the predicted the traffic volume.  ...  [12] , Neuro-Fuzzy Systems [13] and Fuzzy [14] .The accuracy of the mathematical forecasting method cannot satisfactorily meet the demand of real-time traffic control systems [15] because the  ... 
doi:10.5120/18840-0026 fatcat:khhmjjcqlvcvdlxpotzavgkbfe

A Fuzzy Ontology-Driven Approach to Semantic Interoperability in e-Government Big Data

Andreiwid Sh. Corrêa, Cleverton Borba, Daniel Lins da Silva, Pedro Corrêa
2015 International Journal of Social Science and Humanity  
We propose the use of fuzzy mechanisms to deal with natural language terms and present some related works found in this area.  ...  With this, it is possible to take advantage of the large volume of information generated from e-Government initiatives and use it to benefit society Index Terms-E-government, semantic interoperability,  ...  International Journal of Social Science and Humanity, Vol.5, No. 2, February 2015  ... 
doi:10.7763/ijssh.2015.v5.448 fatcat:omqa5fpho5e4hluvi2pooglnc4

Decision-making system based on a Fuzzy Hierarchical Analysis Process and an Artificial Neural Network for Flow Shop machine scheduling model under uncertainty

L. F. Villanueva-Jimenez, Jose A. Vazquez-Lopez, Javier Yanez-Mendiola, Valentin Calzada-Ledesma, Juan De Anda-Suarez
2021 IEEE Access  
The system is based on the combination of the Fuzzy Hierarchical Analysis Process, a membership analysis, and an Artificial Neural Network (ANN).  ...  The system allows to concentrate the experience of experts in machine scheduling and generalize their knowledge.  ...  uncertainty of influential internal and external variables directly and indirectly when creating a final processing sequencing.  ... 
doi:10.1109/access.2021.3099342 fatcat:q2flfwu2xjc4xoz7y7gm3pvpkm

Optimum Selection of "Number of Seats/Cargo Volume" for Transports in Uncertain Business Environment

M. A. Shahi Ashtiani, S. M. B. Malaek
2008 Journal of Aircraft  
Fuzzy systems are among knowledge-based systems constructed from human knowledge which manifest themselves by IF-THEN statements.  ...  Generally, a fuzzy system consists of four components: fuzzy rule base, fuzzy inference engine, fuzzifier, and defuzzifier as shown in Fig. 2.  ... 
doi:10.2514/1.27865 fatcat:qjkmd5hsdngnbchtglpsxujvlq

Fuzzy Multi-Criterial Choice of Geological and Technical Measures

Oleg Yuryevich Panischev, Yuri Vladimirovich Davydov, Igor Vyacheslavovich Anikin, Dina Vladimirovna Kataseva, Alexey Sergeevich Katasev, Amir Muratovich Akhmetvaleev
2020 International journal of engineering research and technology  
Based on the knowledge of experts, a knowledge base has been formed that includes fuzzy production rules for choosing 81 different geological and technical measures at production wells using the restrictions  ...  The work solves the problem of automating the process planning of assigning geological and technical measures (GTM) at oil fields in conditions of uncertainty.  ...  ISSN 0974-3154, Volume 13, Number 11 (2020), pp. 3605-3610 © International Research Publication House. http://www.irphouse.com  ... 
doi:10.37624/ijert/13.11.2020.3605-3610 fatcat:gn4tn2a5ifewblfm4nsqm3v7rq

A CLASSIFIED REVIEW ON THE COMBINATION FUZZY LOGIC–GENETIC ALGORITHMS BIBLIOGRAPHY: 1989–1995 [chapter]

O. Cordón, F. Herrera, M. Lozano
1997 Advances in Fuzzy Systems — Applications and Theory  
Fifth International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems (IPMU'94), pages 665{670. Paris. 39.  ...  the optimization of fuzzy rules. In Proc. Fifth International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems (IPMU'94), pages 671{674. Paris. 25.  ... 
doi:10.1142/9789814261296_0012 fatcat:emq37i6lfjbi3pnp72fzr5wss4

Developing of Fuzzy Logic Decision Support for Management of Breast Cancer

Sameh Mohamed, Wael Mohamed
2016 International Journal of Computer Applications  
This paper aims to describe an intelligent procedure based on fuzzy logic techniques and medical model to detect and diagnose Breast.  ...  The system has 7 input parameters and 1 output, in which the inputs are Age, Genetic Factor, Menarche Age, First Pregnancy, Menopause Age, Nutrition Habit, Life Style and the output parameter which is  ...  1 15 18 21 25 27 30 33 36 40 normal late International Journal of Computer Applications (0975 -8887) Volume 147 -No.1, August 2016 3 0 0.5 1 0.1 0.2 0.3 0.4 0.5 0.6  ... 
doi:10.5120/ijca2016910585 fatcat:kalnxrlxmjdmrhrdo32srait7e

Improved Fuzzy Modeling of Thyroid Disease Detection using Interval Type-2 Fuzzy Techniques

2020 International Journal of Engineering and Advanced Technology  
Type 1 fuzzy systems are much interpretable but less accurate than the type 2 and Interval Type 2 Fuzzy Systems (IT2FS).  ...  Fuzzy Systems are the managers for the modeling environment uncertainty for real time decision making.  ...  Mamdani Type FRBS is composed of Fuzzification Interface, Defuzzification Interface and Knowledge Base.  ... 
doi:10.35940/ijeat.c5931.089620 fatcat:57em64x2u5dbtcuivgzj4tfhom

Comparative Study of Type-1 Fuzzy Logic and Type-2 Fuzzy Logic

Neeru Lalka, Sushma Jain
2015 International Journal of Computer Applications  
Medical diagnosis is a complex process which can be attributed to the complexities, uncertainties and vagueness of the symptoms involved, and sometimes also because of their complex relationship with the  ...  Maintaining good Fuzzifier Inference Engine Disease domain knowledge Type-1 Fuzzy rule base Knowledge base Defuzzifier International Journal of Computer Applications (0975 -8887) Volume  ...  Type-2 diabetes knowledge base: The knowledge base has domain specific knowledge and the corresponding fuzzy values. Besides this, it also has a fuzzy rule base as shown in figure 1 .  ... 
doi:10.5120/ijca2015905802 fatcat:hmd7fljnpfdizovpfp6ib4rihe

A Novel Financial Decision Support Systems Based on Mendel Type-2 Fuzzy Set Theory

Ng Geok See
2015 International Journal on Perceptive and Cognitive Computing  
This is based on the knowledge that type-2 fuzzy set is a good alternative in reducing uncertainty in input data.  ...  FNN exploits the autonomy power of neural network, and therefore frees itself from the time-consuming process of knowledge base building.  ...  Thus, it is proposed to implement Mendel Type-II fuzzy logic as the base of the fuzzy neural system. The resulting FNN based on Type-II fuzzy logic is able to handle uncertainties.  ... 
doi:10.31436/ijpcc.v1i1.5 fatcat:4hmra4mnxnd6vnkpz3vbhtemgm

Sugeno-Type Fuzzy Inference Model for Stock Price Prediction

Uduak A.Umoh, Alfred A. Udosen
2014 International Journal of Computer Applications  
Knowledge Base, Fuzzification, Inference Engine and Defuzzification are the essential components of our model. We explore Sugeno-type fuzzy inference engine to optimize the estimated result.  ...  The development of this system is based on the selection of stock data history which are studied and used for training the system.  ...  The knowledge base design of the Sugeno-type fuzzy inference system for stock price prediction comprises of database model and mathematical model.  ... 
doi:10.5120/18051-8957 fatcat:qmgcbgktyveaxp3x4ykyvqkyla
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