Log in

Relevant bibliographies by topics / Fuzzy Rule-based Systems / Journal articles

To see the other types of publications on this topic, follow the link: Fuzzy Rule-based Systems.

Journal articles on the topic 'Fuzzy Rule-based Systems'

Author: Grafiati

Published: 4 June 2021

Last updated: 26 July 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 journal articles for your research on the topic 'Fuzzy Rule-based Systems.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.

1

Lotfi, A., and M. Howarth. "Noninteractive fuzzy rule-based systems." Information Sciences 99, no. 3-4 (1997): 219–34. http://dx.doi.org/10.1016/s0020-0255(96)00271-x.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Su, Pan, and Xueying Ren. "Fuzzy Rule Interpolation Methods Based on Sparse Rule Bases." International Journal of Computer Science and Information Technology 5, no. 3 (2025): 83–91. https://doi.org/10.62051/ijcsit.v5n3.08.

Full text

Abstract:

Fuzzy rule interpolation algorithms have broad applications in computational fuzzy inference systems. This paper systematically introduces interpolation methods based on α-cuts. It focuses on two classical α-cut-based interpolation methods: the KH fuzzy rule interpolation method and the Lagrange fuzzy rule interpolation method. Through theoretical analysis and comparative studies, the fundamental principles, performance characteristics, and limitations of these two interpolation algorithms are explored in depth. Based on this, a fuzzy inference system for the "tip calculation problem" was cons

APA, Harvard, Vancouver, ISO, and other styles

3

Nozaki, K., H. Ishibuchi, and H. Tanaka. "Adaptive fuzzy rule-based classification systems." IEEE Transactions on Fuzzy Systems 4, no. 3 (1996): 238–50. http://dx.doi.org/10.1109/91.531768.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

Ishibuchi, H., and T. Yamamoto. "Rule weight specification in fuzzy rule-based classification systems." IEEE Transactions on Fuzzy Systems 13, no. 4 (2005): 428–35. http://dx.doi.org/10.1109/tfuzz.2004.841738.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

Starczewski, Janusz T., Piotr Goetzen, and Christian Napoli. "Triangular Fuzzy-Rough Set Based Fuzzification of Fuzzy Rule-Based Systems." Journal of Artificial Intelligence and Soft Computing Research 10, no. 4 (2020): 271–85. http://dx.doi.org/10.2478/jaiscr-2020-0018.

Full text

Abstract:

AbstractIn real-world approximation problems, precise input data are economically expensive. Therefore, fuzzy methods devoted to uncertain data are in the focus of current research. Consequently, a method based on fuzzy-rough sets for fuzzification of inputs in a rule-based fuzzy system is discussed in this paper. A triangular membership function is applied to describe the nature of imprecision in data. Firstly, triangular fuzzy partitions are introduced to approximate common antecedent fuzzy rule sets. As a consequence of the proposed method, we obtain a structure of a general (non-interval)

APA, Harvard, Vancouver, ISO, and other styles

6

Ravi, Chandrasekar, and Neelu Khare. "Review of Fuzzy Rule Based Classification systems." Research Journal of Pharmacy and Technology 9, no. 8 (2016): 1299. http://dx.doi.org/10.5958/0974-360x.2016.00247.x.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Babuska, R., A. Gegov, and H. B. Verbruggen. "Decoupling of Multivariable Rule-Based Fuzzy Systems." IFAC Proceedings Volumes 31, no. 29 (1998): 11. http://dx.doi.org/10.1016/s1474-6670(17)38319-2.

Full text

APA, Harvard, Vancouver, ISO, and other styles

8

Babuška, R., A. Gegov, and H. B. Verbruggen. "Decoupling of Multivariable Rule-Based Fuzzy Systems." IFAC Proceedings Volumes 31, no. 29 (1998): 13–16. http://dx.doi.org/10.1016/s1474-6670(17)38913-9.

Full text

APA, Harvard, Vancouver, ISO, and other styles

9

Henzgen, Sascha, Marc Strickert, and Eyke Hüllermeier. "Visualization of evolving fuzzy rule-based systems." Evolving Systems 5, no. 3 (2014): 175–91. http://dx.doi.org/10.1007/s12530-014-9110-4.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

Lotfi, A., H. C. Andersen, and A. C. Tsoi. "Matrix formulation of fuzzy rule-based systems." IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 26, no. 2 (1996): 332–40. http://dx.doi.org/10.1109/3477.485885.

Full text

APA, Harvard, Vancouver, ISO, and other styles

11

Requena, Ignacio, Armando Blanco, and Miguel Delgado. "A Constructive Method for Building Fuzzy Rule-Based Systems." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 11, no. 02 (2003): 217–33. http://dx.doi.org/10.1142/s0218488503002028.

Full text

Abstract:

This paper proposes a new method for identifying unknown systems with Fuzzy Rule-Based Systems (FRBSs). The method employs different methodologies from the discipline of Soft Computing (Artificial Neural Networks, Fuzzy Clustering) and follows a three-stage process. Firstly, the structure of the FRBS rules is determined using a feature selection process. A fuzzy clustering procedure is then used to establish the number of fuzzy rules. In the third step, the fuzzy membership functions are constructed for the linguistic labels. Finally, the empirical performance of the algorithm is studied by ap

APA, Harvard, Vancouver, ISO, and other styles

12

YAMAMOTO, Takashi, and Hisao ISHIBUCHI. "Heuristic Rule Weight Specification for Fuzzy Rule-Based Classification Systems." Journal of Japan Society for Fuzzy Theory and Intelligent Informatics 16, no. 5 (2004): 441–51. http://dx.doi.org/10.3156/jsoft.16.441.

Full text

APA, Harvard, Vancouver, ISO, and other styles

13

Riid, Andri, and Ennu Rüstern. "Adaptability, interpretability and rule weights in fuzzy rule-based systems." Information Sciences 257 (February 2014): 301–12. http://dx.doi.org/10.1016/j.ins.2012.12.048.

Full text

APA, Harvard, Vancouver, ISO, and other styles

14

Ishibuchi, H., and T. Nakashima. "Effect of rule weights in fuzzy rule-based classification systems." IEEE Transactions on Fuzzy Systems 9, no. 4 (2001): 506–15. http://dx.doi.org/10.1109/91.940964.

Full text

APA, Harvard, Vancouver, ISO, and other styles

15

Chen, Shyi-Ming, and Yu-Chuan Chang. "Weighted fuzzy interpolative reasoning for sparse fuzzy rule-based systems." Expert Systems with Applications 38, no. 8 (2011): 9564–72. http://dx.doi.org/10.1016/j.eswa.2011.01.138.

Full text

APA, Harvard, Vancouver, ISO, and other styles

16

Agarwal, Dr Shivani. "Rule Based Analysis of Disease Detection." International Journal for Research in Applied Science and Engineering Technology 11, no. 5 (2023): 4991–96. http://dx.doi.org/10.22214/ijraset.2023.52709.

Full text

Abstract:

Abstract: We employ fuzzy sets and fuzzy logic for illness diagnosis. By utilizing a fuzzy logic framework, uncertainty in data and decision-making processes may be made up for. Diagnostic models that can manage enormous volumes of complex and raw medical data may be made using fuzzy logic. Fuzzy logic has a number of advantages when it comes to disease detection, having the ability to deal with incomplete and inaccurate data, the ability to incorporate expert knowledge and feedback, the potential to improve diagnostic accuracy and decrease the number of false positives and false negatives, as

APA, Harvard, Vancouver, ISO, and other styles

17

Takács, Marta. "g-Calculus-Based Compositional Rule of Inference." Journal of Advanced Computational Intelligence and Intelligent Informatics 10, no. 4 (2006): 534–41. http://dx.doi.org/10.20965/jaciii.2006.p0534.

Full text

Abstract:

We review a specific case, in which the investigated structure is a real semi-ring with pseudo-operations as a step toward investigating the problem of approximate reasoning in fuzzy systems. We focus on special-type fuzzy sets, i.e. <I>g</I> -generated quasi-triangular fuzzy numbers, and special <I>g</I> -generated t-norms and implication in fuzzy approximate reasoning.

APA, Harvard, Vancouver, ISO, and other styles

18

Shyi-Ming Chen. "A fuzzy reasoning approach for rule-based systems based on fuzzy logics." IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics) 26, no. 5 (1996): 769–78. http://dx.doi.org/10.1109/3477.537318.

Full text

APA, Harvard, Vancouver, ISO, and other styles

19

Tiwari, Rajdev, Anubhav Tiwari, and Manu Pratap Singh. "Fuzzy-Rule Based Adaptive Data Warehouse." International Journal of Applied Evolutionary Computation 3, no. 1 (2012): 47–65. http://dx.doi.org/10.4018/jaec.2012010103.

Full text

Abstract:

Data Warehouses (DWs) are aimed to empower the knowledge workers with information and knowledge which helps them in decision making. Technically, the DW is a large reservoir of integrated data that does not provide the intelligence or the knowledge demanded by users. The burden of data analysis and extraction of information and knowledge from integrated data still lies upon the analyst’s shoulder. The overhead of analysts can be taken off by architecting a new generation data warehouses systems those shall be capable of capturing, organizing and representing knowledge along with the data and i

APA, Harvard, Vancouver, ISO, and other styles

20

Lin, Jinle, Changjing Shang, and Qiang Shen. "Towards Dynamic Fuzzy Rule Interpolation via Density-Based Rule Promotion from Interpolated Outcomes." Mathematics 12, no. 3 (2024): 402. http://dx.doi.org/10.3390/math12030402.

Full text

Abstract:

Traditional fuzzy rule-based systems struggle with scenarios where knowledge gaps exist in the problem domain, due to limited data or experience. Fuzzy rule interpolation (FRI) effectively addresses the challenge of inference in fuzzy systems when faced with unmatched observations, due to the employment of an incomplete or sparse rule base. It generates temporary, interpolated rules for the unmatched observations, ensuring continued inference capability. However, the resultant valuable interpolated rules are conventionally discarded. This paper introduces a formal approach for dynamic fuzzy ru

APA, Harvard, Vancouver, ISO, and other styles

21

CHEN, SHYI-MING, YU-CHUAN CHANG, ZE-JIN CHEN, and CHIA-LING CHEN. "MULTIPLE FUZZY RULES INTERPOLATION WITH WEIGHTED ANTECEDENT VARIABLES IN SPARSE FUZZY RULE-BASED SYSTEMS." International Journal of Pattern Recognition and Artificial Intelligence 27, no. 05 (2013): 1359002. http://dx.doi.org/10.1142/s0218001413590027.

Full text

Abstract:

This paper presents a new method for multiple fuzzy rules interpolation with weighted antecedent variables in sparse fuzzy rule-based systems based on polygonal membership functions. First, the proposed method calculates the normalized weighting vector of each closest fuzzy rule. Then, it calculates the composite weight of each closest fuzzy rule. Then, it calculates the left normal point [Formula: see text] and the right normal point [Formula: see text] of the fuzzy interpolative reasoning result [Formula: see text], respectively. Finally, it calculates the characteristic points [Formula: see

APA, Harvard, Vancouver, ISO, and other styles

22

LEE, KEON-MYUNG, and HYUNG LEE-KWANG. "FUZZY INFORMATION PROCESSING FOR EXPERT SYSTEMS." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 03, no. 01 (1995): 93–109. http://dx.doi.org/10.1142/s0218488595000098.

Full text

Abstract:

This paper investigates the problems incurred when fuzzy values and certainty factors are used in rule-based knowledge representation. It proposes several measures for evaluating the satisfaction degree of fuzzy matching, fuzzy comparison and interval inclusion occurring in the course of inference for such knowledge representation. It introduces an inference method for such knowledge representation. In addition, it suggests a strategy for flexibly using and managing both conventional rules and fuzzy production rules in rule-based systems. Finally a fuzzy expert system shell, called FOPS5, desi

APA, Harvard, Vancouver, ISO, and other styles

23

Surmann, H., and A. P. Ungering. "Fuzzy rule-based systems on general-purpose processors." IEEE Micro 15, no. 4 (1995): 40–48. http://dx.doi.org/10.1109/40.400641.

Full text

APA, Harvard, Vancouver, ISO, and other styles

24

Aurélio Stumpf González, Marco, and Carlos Torres Formoso. "Mass appraisal with genetic fuzzy rule‐based systems." Property Management 24, no. 1 (2006): 20–30. http://dx.doi.org/10.1108/02637470610643092.

Full text

APA, Harvard, Vancouver, ISO, and other styles

25

Lim, M. H., and Y. Takefuji. "Implementing fuzzy rule-based systems on silicon chips." IEEE Expert 5, no. 1 (1990): 31–45. http://dx.doi.org/10.1109/64.50855.

Full text

APA, Harvard, Vancouver, ISO, and other styles

26

Pomares, H., I. Rojas, J. Gonzalez, and A. Prieto. "Structure identification in complete rule-based fuzzy systems." IEEE Transactions on Fuzzy Systems 10, no. 3 (2002): 349–59. http://dx.doi.org/10.1109/tfuzz.2002.1006438.

Full text

APA, Harvard, Vancouver, ISO, and other styles

27

Botta, Alessio, Beatrice Lazzerini, and Francesco Marcelloni. "Context adaptation of mamdani fuzzy rule based systems." International Journal of Intelligent Systems 23, no. 4 (2008): 397–418. http://dx.doi.org/10.1002/int.20273.

Full text

APA, Harvard, Vancouver, ISO, and other styles

28

Chang, Te-Chuan, C. William Ibbs, and Keith C. Crandall. "A fuzzy logic system for expert systems." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 2, no. 3 (1988): 183–93. http://dx.doi.org/10.1017/s0890060400000640.

Full text

Abstract:

Using the theory of fuzzy sets, this paper develops a fuzzy logic reasoning system as an augmentation to a rule-based expert system to deal with fuzzy information. First, fuzzy set theorems and fuzzy logic principles are briefly reviewed and organized to form a basis for the proposed fuzzy logic system. These theorems and principles are then extended for reasoning based on knowledge base with fuzzy production rules. When an expert system is augmented with the fuzzy logic system, the inference capability of the expert system is greatly expanded; and the establishment of a rule-based knowledge b

APA, Harvard, Vancouver, ISO, and other styles

29

Nakashima, Tomoharu, Yasuyuki Yokota, Hisao Ishibuchi, Gerald Schaefer, Aleš Drastich, and Michal Závišek. "Constructing Cost-Sensitive Fuzzy-Rule-Based Systems for Pattern Classification Problems." Journal of Advanced Computational Intelligence and Intelligent Informatics 11, no. 6 (2007): 546–53. http://dx.doi.org/10.20965/jaciii.2007.p0546.

Full text

Abstract:

We evaluate the performance of cost-sensitive fuzzy-rule-based systems for pattern classification problems. We assume that a misclassification cost is given a priori for each training pattern. The task of classification thus becomes to minimize both classification error and misclassification cost. We examine the performance of two types of fuzzy classification based on fuzzy if-then rules generated from training patterns. The difference is whether or not they consider misclassification costs in rule generation. In our computational experiments, we use several specifications of misclassificatio

APA, Harvard, Vancouver, ISO, and other styles

30

Shofakirova, Nazarshoev, and Tojiniso Khorg. "Advancements in Optimizing Fuzzy Grid Partition for Enhanced Rule Generation Performance: Algorithms, Interpretability, and Scalability." International Journal of Enterprise Modelling 13, no. 3 (2019): 99–108. http://dx.doi.org/10.35335/emod.v13i3.13.

Full text

Abstract:

This research focuses on optimizing fuzzy grid partitioning to enhance rule generation performance in fuzzy rule-based systems. A novel mathematical formulation is proposed, aiming to minimize the number of fuzzy grid cells while considering coverage, regularity, and overlap constraints. The study demonstrates the effectiveness of the approach through a case example in credit risk assessment. The optimized fuzzy grid partitioning scheme generates concise and interpretable fuzzy rules, improving the accuracy and interpretability of the rule-based system. The research highlights the significance

APA, Harvard, Vancouver, ISO, and other styles

31

Son, Chang-S., Hwan-M. Chung, and Soon-H. Kwon. "Selection Method of Fuzzy Partitions in Fuzzy Rule-Based Classification Systems." Journal of Korean Institute of Intelligent Systems 18, no. 3 (2008): 360–66. http://dx.doi.org/10.5391/jkiis.2008.18.3.360.

Full text

APA, Harvard, Vancouver, ISO, and other styles

32

Daniachew, Adeola Azy, Averey Barack Clevon, Abimelech Keita Avram, and Dodavah Tesseman Chislon. "Hybrid Grid Partition and Rought Set Methods for Generating Fuzzy Rules in Data Set Classification." International Journal of Enterprise Modelling 13, no. 3 (2019): 156–73. http://dx.doi.org/10.35335/emod.v13i3.73.

Full text

Abstract:

This research aims to address the issue of exponential rule generation in fuzzy rule-based classification systems by developing a hybrid grid partition and rough set method. Fuzzy rule-based classification systems have the potential to construct linguistically understandable models, but a major constraint is the significant increase in the number of rules with a high number of attributes, which can diminish interpretation and classification accuracy. In this study, the grid partition method is utilized to generate fuzzy rules with adaptively adjusted grid structures, thus avoiding exponential

APA, Harvard, Vancouver, ISO, and other styles

33

Huang, Y. L., and L. T. Fan. "A fuzzy-logic-based approach to building efficient fuzzy rule-based expert systems." Computers & Chemical Engineering 17, no. 2 (1993): 181–92. http://dx.doi.org/10.1016/0098-1354(93)80013-d.

Full text

APA, Harvard, Vancouver, ISO, and other styles

34

Qin, Hua Ni, and Da Rong Luo. "Rule Extraction Based on Interval-Valued Rough Fuzzy Sets." Applied Mechanics and Materials 665 (October 2014): 668–73. http://dx.doi.org/10.4028/www.scientific.net/amm.665.668.

Full text

Abstract:

A model of interval-valued rough fuzzy set combining interval-valued fuzzy set and rough set is investigated in this paper. Firstly, considering the deficiency of general sorting method between any interval-valued fuzzy numbers, an improved sorting method and a pair of new approximation operators about minimum and maximum are presented. Based on the improved operators, a model of interval-valued rough fuzzy set is established. At last, by using the modified model of interval-valued rough fuzzy set, a method of knowledge discovery in interval-valued fuzzy information systems is investigated.

APA, Harvard, Vancouver, ISO, and other styles

35

TRAWIŃSKI, KRZYSZTOF, OSCAR CORDÓN, and ARNAUD QUIRIN. "ON DESIGNING FUZZY RULE-BASED MULTICLASSIFICATION SYSTEMS BY COMBINING FURIA WITH BAGGING AND FEATURE SELECTION." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 19, no. 04 (2011): 589–633. http://dx.doi.org/10.1142/s0218488511007155.

Full text

Abstract:

In this work, we conduct a study considering a fuzzy rule-based multiclassification system design framework based on Fuzzy Unordered Rule Induction Algorithm (FURIA). This advanced method serves as the fuzzy classification rule learning algorithm to derive the component classifiers considering bagging and feature selection. We develop an exhaustive study on the potential of bagging and feature selection to design a final FURIA-based fuzzy multiclassifier dealing with high dimensional data. Several parameter settings for the global approach are tested when applied to twenty one popular UCI data

APA, Harvard, Vancouver, ISO, and other styles

36

Klepiszewski, K., and T. G. Schmitt. "Comparison of conventional rule based flow control with control processes based on fuzzy logic in a combined sewer system." Water Science and Technology 46, no. 6-7 (2002): 77–84. http://dx.doi.org/10.2166/wst.2002.0665.

Full text

Abstract:

While conventional rule based, real time flow control of sewer systems is in common use, control systems based on fuzzy logic have been used only rarely, but successfully. The intention of this study is to compare a conventional rule based control of a combined sewer system with a fuzzy logic control by using hydrodynamic simulation. The objective of both control strategies is to reduce the combined sewer overflow volume by an optimization of the utilized storage capacities of four combined sewer overflow tanks. The control systems affect the outflow of four combined sewer overflow tanks depen

APA, Harvard, Vancouver, ISO, and other styles

37

Tuan, Tran Manh, Nguyen Thanh Duc, Pham Van Hai, and Le Hoang Son. "Dental Diagnosis from X-Ray Images using Fuzzy Rule-Based Systems." International Journal of Fuzzy System Applications 6, no. 1 (2017): 1–16. http://dx.doi.org/10.4018/ijfsa.2017010101.

Full text

Abstract:

In practical dentistry, dentists use their experience to examine dental X-ray images and to derive symptoms from patients for concluding possible diseases. This method is based solely on the own dentists' experience. Dental diagnosis from X-Ray images is proposed to support for dentists in their decision making. This paper presents an application of consultant system for dental diagnosis from X-Ray images based on fuzzy rule. Fuzzy rule was applied in many applications and has important role in computational intelligence, data mining, machine learning, etc. Based on a dental X-ray image datase

APA, Harvard, Vancouver, ISO, and other styles

38

Oladipupo, Olufunke O., Charles O. Uwadia, and Charles K. Ayo. "Improving medical rule-based expert systems comprehensibility: fuzzy association rule mining approach." International Journal of Artificial Intelligence and Soft Computing 3, no. 1 (2012): 29. http://dx.doi.org/10.1504/ijaisc.2012.048179.

Full text

APA, Harvard, Vancouver, ISO, and other styles

39

Hu, Xingchen, Witold Pedrycz, and Xianmin Wang. "Random ensemble of fuzzy rule-based models." Knowledge-Based Systems 181 (October 2019): 104768. http://dx.doi.org/10.1016/j.knosys.2019.05.011.

Full text

APA, Harvard, Vancouver, ISO, and other styles

40

Camastra, Francesco, Angelo Ciaramella, Giuseppe Salvi, Salvatore Sposato, and Antonino Staiano. "On the interpretability of fuzzy knowledge base systems." PeerJ Computer Science 10 (December 3, 2024): e2558. https://doi.org/10.7717/peerj-cs.2558.

Full text

Abstract:

In recent years, fuzzy rule-based systems have been attracting great interest in interpretable and eXplainable Artificial Intelligence as ante-hoc methods. These systems represent knowledge that humans can easily understand, but since they are not interpretable per se, they must remain simple and understandable, and the rule base must have a compactness property. This article presents an algorithm for minimizing the fuzzy rule base, leveraging rough set theory and a greedy strategy. Reducing fuzzy rules simplifies the rule base, facilitating the construction of interpretable inference systems

APA, Harvard, Vancouver, ISO, and other styles

41

Chen, Shyi-Ming, and Li-Wei Lee. "Fuzzy interpolative reasoning for sparse fuzzy rule-based systems based on interval type-2 fuzzy sets." Expert Systems with Applications 38, no. 8 (2011): 9947–57. http://dx.doi.org/10.1016/j.eswa.2011.02.035.

Full text

APA, Harvard, Vancouver, ISO, and other styles

42

Yu-Chuan Chang, Shyi-Ming Chen, and Churn-Jung Liau. "Fuzzy Interpolative Reasoning for Sparse Fuzzy-Rule-Based Systems Based on the Areas of Fuzzy Sets." IEEE Transactions on Fuzzy Systems 16, no. 5 (2008): 1285–301. http://dx.doi.org/10.1109/tfuzz.2008.924340.

Full text

APA, Harvard, Vancouver, ISO, and other styles

43

Chen, Shyi-Ming, Wen-Chyuan Hsin, Szu-Wei Yang, and Yu-Chuan Chang. "Fuzzy interpolative reasoning for sparse fuzzy rule-based systems based on the slopes of fuzzy sets." Expert Systems with Applications 39, no. 15 (2012): 11961–69. http://dx.doi.org/10.1016/j.eswa.2012.03.065.

Full text

APA, Harvard, Vancouver, ISO, and other styles

44

ISHIBUCHI, Hisao, and Takehiko MORISAWA. "Adjusting Membership Functions in Fuzzy Rule-Based Classification Systems." Transactions of the Institute of Systems, Control and Information Engineers 10, no. 5 (1997): 223–35. http://dx.doi.org/10.5687/iscie.10.223.

Full text

APA, Harvard, Vancouver, ISO, and other styles

45

Ammar, Salwa, William Duncombe, Yilin Hou, and Ronald Wright. "Evaluating City Financial Management Using Fuzzy Rule-Based Systems." Public Budgeting Finance 21, no. 4 (2001): 70–90. http://dx.doi.org/10.1111/0275-1100.00059.

Full text

APA, Harvard, Vancouver, ISO, and other styles

46

Pota, Marco, Massimo Esposito, and Giuseppe De Pietro. "Designing rule-based fuzzy systems for classification in medicine." Knowledge-Based Systems 124 (May 2017): 105–32. http://dx.doi.org/10.1016/j.knosys.2017.03.006.

Full text

APA, Harvard, Vancouver, ISO, and other styles

47

Luengo, Julián, José A. Sáez, and Francisco Herrera. "Missing data imputation for fuzzy rule-based classification systems." Soft Computing 16, no. 5 (2011): 863–81. http://dx.doi.org/10.1007/s00500-011-0774-4.

Full text

APA, Harvard, Vancouver, ISO, and other styles

48

Lotfi, A., M. Howarth, and J. B. Hull. "Orthogonal Fuzzy Rule-Based Systems: Selection of Optimum Rules." Neural Computing & Applications 9, no. 1 (2000): 4–11. http://dx.doi.org/10.1007/s005210070029.

Full text

APA, Harvard, Vancouver, ISO, and other styles

49

Yixin Chen and J. Z. Wang. "Support vector learning for fuzzy rule-based classification systems." IEEE Transactions on Fuzzy Systems 11, no. 6 (2003): 716–28. http://dx.doi.org/10.1109/tfuzz.2003.819843.

Full text

APA, Harvard, Vancouver, ISO, and other styles

50

Seyed, Shahram, and P. A. Ramamoorthy. "A new concept of fuzzy rule-based expert systems." International Journal of Approximate Reasoning 2, no. 2 (1988): 108–9. http://dx.doi.org/10.1016/0888-613x(88)90096-5.

Full text

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!