Journal of Intelligent & Fuzzy Systems - Volume 29, issue 4

Authors: She, Yanhong | He, Xiaoli

Article Type: Research Article

Abstract: Equipping NM-algebras with a Brouwer-like negation ∼, we introduce a kind of algebra under the name BZNM-algebra in the present paper and investigate its algebraic properties in detail. By means of the Brouwer-like negation ∼ and the internal Kleene negation ¬ in NM-algebras, two types of modal operators μ and ν on BZNM-algebras are defined. For any element a of BZNM-algebra, μ  (a ) and ν  (a ) turn out to be the best approximation of a from the bottom and the top, respectively, with Boolean skeleton serving as the collection of sharp elements. It is …also shown that these two modal operators turn to have an S 5 behavior. Additionally, various types of sharp elements with respect to the negation operators including ∼, ¬, ♭ (an anti-intuitionistic negation) are defined, and the relationship between these sets and that of ⊗-idempotent (⊕-idempotent) elements are also investigated. It is then proved that the proposed BZNM-algebras are indeed equivalent to NM▵ algebras under a suitable transformation of operators. Furthermore, a special kind of BZNM-algebras, i.e., BZNM3 -algebras, is investigated and its equivalent characterizations are given. A new type of rough approximation operators are proposed, and it is shown that such a pair of approximation operators is equivalent to the defined operators μ and ν . Finally, two interesting examples of BZNM-algebras are presented. Show more

Keywords: Nilpotent minimum algebra, kleene negation, brouwer-like negation, rough set

DOI: 10.3233/IFS-141510

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 4, pp. 1367-1380, 2015

Authors: Zhou, Jian-Lan | Shia, Yuan-Biao | Sun, Zhi-Yu

Article Type: Research Article

Abstract: This paper focuses on a risk decision making problem in high-risk work system. A special risk decision-making problem with dynamic and risky characteristics needs to be considered in work system which involves many complex factors in safety risks and control measurements. Furthermore, taking into account the inherent imprecision and uncertainty of the available data, a method based on Fuzzy Fault Tree Analysis (FFTA) is proposed to solve the problem. Unlike conventional fuzzy fault tree analysis, the fuzzy analytic hierarchy process is applied to eliminate ambiguity and subjectivity in determining the weights of criteria. Furthermore, a more simple and effective method …for ranking fuzzy numbers is introduced to determine the relationships among the fuzzy results. Based on these methods, a hybrid approach is proposed for risk decision-making in accident emergency response of work system. Finally, a case study on the accident of crane hitting the high bent is given to demonstrate the proposed the validity and objectivity of the method. Compared with other available methods in the literature, the results reported here suggest that the hybrid method is more reasonable under the conditions of limited decision data and possible evolvement of emergency states. Show more

Keywords: Emergency response, risk decision-making, work system, fuzzy fault tree analysis, analytic hierarchy process

DOI: 10.3233/IFS-141512

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 4, pp. 1381-1393, 2015

Authors: Wang, Lijuan | Hao, Zhifeng | Cai, Ruichu | Wen, Wen

Article Type: Research Article

Abstract: Soft subspace clustering has attracted a lot of research efforts, due to the emergence of applications in high-dimensional clustering. To the best of our knowledge, most existing soft subspace clustering algorithms assign weights to features relying on Euclidean distance. Such schemes only allow soft subspace clustering algorithms to extend or shrink feature space with respect to feature weights. In this paper, we aim to break this limitation and facilitate feature space transformations directed by an enhanced soft subspace clustering algorithm through hybrid dissimilarity measure (ESCHD). The proposed hybrid dissimilarity measure assign weights to features based on Euclidean distance and Cosine …dissimilarity, which can extend, shrink and rotate feature space so that the performance of soft subspace clustering can be improved. In ESCHD, a new optimization objective function is designed, based on the goal of minimizing the hybrid dissimilarity and maximizing the weighted entropy. Using the new objective function, we derive new updating rules for the iterations in the clustering procedure. The proved promising convergence property of ESCHD also ensures the performance of ESCHD. Experimental results on both synthetic and UCI datasets demonstrate that ESCHD is superior to the four existing clustering algorithms, i.e. K-means, W-k-means, LAC and EWKM. In addition, ESCHD is more robust to handle the problems with noise and missing data than the four algorithms. Show more

Keywords: Soft subspace clustering, dissimilarity measure, feature weighting, high dimensional clustering

DOI: 10.3233/IFS-141517

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 4, pp. 1395-1405, 2015

Authors: Zhang, Fu | Ma, ZM | Chen, Xu

Article Type: Research Article

Abstract: Full implementation of the Semantic Web requires widespread availability of (fuzzy) ontologies. In this paper, we develop a complete approach and an automated tool for formalizing fuzzy object-oriented database (FOOD) models using fuzzy ontologies (i.e., constructing fuzzy ontologies from FOOD models), and investigate how to apply the constructed fuzzy ontologies to reason on FOOD models. Firstly, we propose a complete formal definition of FOOD models, which considers most features of FOOD models. On this basis, we propose an approach for constructing fuzzy ontologies from FOOD models. The approach can transform FOOD models (including schema and object instance information) into fuzzy …ontologies. We also give full proof of correctness of the construction approach, and provide a full construction example. Furthermore, we implement a prototype tool called FOOD2FOnto, which can automatically construct fuzzy ontologies from FOOD models. Some tests demonstrate that our approach actually works. Finally, the constructed fuzzy ontologies are used to reason on the FOOD models, and some reasoning rules and a reasoning example are provided. Show more

Keywords: Fuzzy object-oriented database (FOOD) model, fuzzy ontology, formalization, construction, reasoning

DOI: 10.3233/IFS-151532

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 4, pp. 1407-1420, 2015

Authors: Ouncharoen, Rujira | Kreinovich, Vladik | Nguyen, Hung T.

Article Type: Research Article

Abstract: To take into account that expert’s degrees of certainty are not always comparable, researchers have used partially ordered set of degrees instead of the more traditional linearly (totally) ordered interval [0, 1]. In most cases, it is assumed that this partially ordered set is a lattice, i.e., every two elements have the greatest lower bound and the least upper bound. In this paper, we prove a theorem explaining why it is reasonable to require that the set of degrees is a lattice.

Keywords: Lattice-valued fuzzy logic, L-fuzzy

DOI: 10.3233/IFS-151558

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 4, pp. 1421-1425, 2015

Authors: Wang, Yong | Ma, Xiaolei | Xu, Maozeng | Wang, Yinhai | Liu, Yong

Article Type: Research Article

Abstract: Vehicle routing problem (VRP) is a combinatorial optimization and integer programming problem seeking to service a number of customers with a fleet of vehicles. Customer characteristics are neglected in traditional VRPs in the past due to the heterogeneity and ambiguousness. This study presents a vehicle route optimization model in consideration of customer characteristics with three major components: (1) A hierarchical analysis structure is developed to convert customers’ characteristics into linguistic variables, and fuzzy integration method is used to map the sub-criteria into higher hierarchical criteria based on the trapezoidal fuzzy numbers; (2) A fuzzy clustering algorithm based on Axiomatic Fuzzy …Set is proposed to group the customers into multiple clusters; (3) The fuzzy technique for order preference by similarity to ideal solution (TOPSIS) approach is integrated into the dynamic programming approach to optimize vehicle routes in each cluster. A numerical case study in Anshun, China demonstrates the advantages of the proposed method by comparing with the other two prevailing algorithms. In addition, a sensitivity analysis is conducted to capture the impacts of various evaluation criteria weights. The results indicate our approach performs very well to identify similar customer groups and incorporate individual customer’s service priority into VRP. Show more

Keywords: Vehicle routing problem, axiomatic fuzzy set, fuzzy clustering algorithm, dynamic programming approach, technique for order preference by similarity to ideal solution (TOPSIS)

DOI: 10.3233/IFS-151578

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 4, pp. 1427-1442, 2015

Authors: Wang, Chang

Article Type: Research Article

Abstract: A vague soft set is a combination of a vague set and a soft set. In this paper, we first discuss the properties of the entropy on vague soft sets. We also propose the cross-entropy of vague soft sets, and investigate the relationship between entropy and cross-entropy. Furthermore, some numerical examples are presented to illustrate the applications of the entropy and cross-entropy of vague soft sets to decision making and pattern recognition.

Keywords: Vague set, soft set, vague soft set, entropy, cross-entropy

DOI: 10.3233/IFS-151608

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 4, pp. 1443-1452, 2015

Authors: Nithya, NS | Duraiswamy, K

Article Type: Research Article

Abstract: Healthcare data need an accurate diagnosis of diseases with the low computation time. Fuzzy association rule mining converts quantitative attributes to fuzzy attributes which maintain the integrity of information. Fuzzy association rule mining is most effective among various classification methods used for diagnosing health care data. The major challenge in the fuzzy association rule mining is to reduce the exponential growth of rules produced by fuzzy partitioning of attributes. The proposed method uses the correlation and gain ratio based average ranking feature selection followed by fuzzy weighted association rule mining classifier to diagnose the medical data set. The average ranking …feature selection method improves classification accuracy and reduces the number of rules by ranking the proper potential attribute. The computation time is also minimized by reducing number of rules. The performance of fuzzy weighted association rule mining classifiers based on correlation and gain ratio average ranking feature selection is evaluated by comparing the classification accuracy with three classifiers and five benchmark data set collected from UCI repository. Show more

Keywords: Gain ratio, correlation, average ranking based fuzzy weight, fuzzy weighted association rule mining, fuzzy weighted support

DOI: 10.3233/IFS-151614

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 4, pp. 1453-1464, 2015

Authors: Longlong, Li | Garibaldi, Jonathan M. | Dongjian, He

Article Type: Research Article

Abstract: Multiple features such as the margin, the shape and the texture of plant leaves are of great importance for classification of plant species, as they are often regarded as the unique features to identify plants. In this paper, we study the performance of a recently proposed semi-supervised fuzzy clustering algorithm with feature discrimination for leaf classification, based on features generated by principal component analysis of color images. The method outlines a basic framework for judging the weights of different features by adopting multiple feature matrixes obtained from the initial images as input data and the clustering results of the proposed …clustering algorithm as output data to distinguish dissimilarities between various leaves. Real leaf images are employed to evaluate its performance and the experiment demonstrates that these results suggest that the margin feature, the shape feature and combination feature especially the margin feature and combination feature may be the best choice for leaf classification. Show more

Keywords: Semi-supervised clustering, leaf classification, multiple features, performance analysis, pairwise constraints

DOI: 10.3233/IFS-151626

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 4, pp. 1465-1477, 2015

Authors: Khorramnia, Reza | Akbarizadeh, Mohammad-Reza | Jahromi, Mohsen Ketabi | Khorrami, Soroush Karimi | Kavusifard, Farzaneh

Article Type: Research Article

Abstract: In the modern power system analysis, the investigation on the impacts of growing wind power generation can be mentioned as an inseparable part of power grids. The development of wind-thermal coordination economic dispatch leads to an optimal dispatch scheme and a mature wind power efficiency. Adding further uncertainties to the study of power systems is one of the effects of intermittent nature of wind energy which is apart from random nature of realistic power grids. Now in order to inspect these uncertainties, an efficient probabilistic method is needed to comfort the issue. In this paper a novel optimization method based …on Social Spider Optimization (SSO) is presented to meet large non-convex Economic Dispatch (ED) problems and uncertainties in the network caused by wind turbines, simultaneously. To provide a more realistic model, following constrains have been included in the proposed Probabilistic ED (PED) formulation: ramp rate limits, Prohibited Operating Zones (POZs), system spinning reserve, valve loading consequences, and multiple fuel choice. Unscented Transform (UT) approach is utilized in this paper to model the uncertainty in wind speed and thereupon solve the PED. In order to show the efficiency of the presented algorithm, it is successfully tested on different systems and compared with several of the most recently published ED methods. Show more

Keywords: Probabilistic economic dispatch, social spider optimization, unscented transform

DOI: 10.3233/IFS-151627

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 4, pp. 1479-1491, 2015