Journal of Intelligent & Fuzzy Systems - Volume 34, issue 1

Authors: Ma, Xueling | Zhan, Jianming

Article Type: Research Article

Abstract: Combining rough sets and soft sets, we apply rough soft sets to BL -algebras. Some new operations of the lower and upper soft approximations are obtained. In particular, rough soft (implicative, positive implicative, fantastic) filters with respect to a filter over BL -algebras are also investigated. In particular, we propose two kinds of decision making methods for rough soft BL -algebras. Finally, the numerical experimentation program is written for given by MATLAB, which supports the above decision making methods.

Keywords: BL-algebra, filter, rough soft (implicative, positive implicative, fantastic) filter, decision making

DOI: 10.3233/JIFS-17945

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 1, pp. 645-658, 2018

Authors: Vidhya, K.A. | Geetha, T.V.

Article Type: Research Article

Abstract: Entity Resolution (ER) is the method of resolving two similar entities used in the process of data cleaning and data integration. However, existing ER Framework lead to exhaustive pairwise comparisons. The most efficient ER method is blocking, inherently uses exponential pair-wise comparisons for the large databases, leading to poor efficiency in resolving the entities. The real world data can either be homogeneous or heterogeneous, generally of two forms, clean-clean ER which does not have any duplicates or dirty-ER which have duplicates within the dataset. Entity Resolution framework is associated with two phases namely the block building phase which construct the …blocks where the similar entities are grouped into a single block for effective indexing, while the aim of block processing phase is to reduce the number of redundant pair-wise comparisons. Another perspective is handling of the entity associated with heterogeneous data, in the proposed work the block building phase aims to gather related entities with different representations into a single block with an approximation space. For this purpose semantic-dominance rough set has been used to cluster the attributes of related entities having a varied schema. The similarity between the entities associated with the clustered attributes is determined using a rough-Jaccard similarity measure, grouped to form blocks of varied, but limited size. The pair-wise comparisons between the blocks of entities are carried out only when the lower approximation of the blocks are same, determined by the proposed multi-criteria Pareto optimality, else the entities are not compared, which signifies, the overall number of pair-wise comparisons is reduced. A performance analysis of the proposed technique has been tested on four real-world, highly heterogeneous datasets, and the validation of these algorithms has yielded 99.98% effectiveness and 98.3% efficiency in block comparison when compared to token blocking and attribute clustering methods. Show more

Keywords: Entity resolution, blocking, rough set, heterogeneous data, linked open data

DOI: 10.3233/JIFS-17946

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 1, pp. 659-675, 2018

Authors: Mondal, Sankar Prasad

Article Type: Research Article

Abstract: The paper presents an adaptation of Interval valued intuitionistic fuzzy number. The arithmetic operation of interval-valued intuitionistic fuzzy number (IVIFN) is addressed here. The differentiability of IVIFN valued function is also addressed here. Demonstration of intuitionistic fuzzy solutions of differential equation is carried out with the said numbers. Additionally, a illustrative application is also undertaken with the useful graph for usefulness for attained to the proposed approaches.

Keywords: Interval valued intuitionistic fuzzy number, differential equation, Drug concentration problem

DOI: 10.3233/JIFS-161898

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 1, pp. 677-687, 2018

Authors: Aydin, Ilhan | Karakose, Mehmet | Karakose, Ebru | Akin, Erhan

Article Type: Research Article

Abstract: Condition monitoring of induction motors has become an important issue of researchers in recent years. The detection of broken rotor bar faults is one of the most difficult problems and many methods have been proposed for accurate detection of these faults. In recent years, some studies have been proposed to improve the diagnostic performance by combining different signal processing techniques. However, the proposed methods require high computational complexity. The contribution of this study is threefold. The first one is a new feature extraction method to distinguish different motor conditions by analyzing one phase of induction motor steady-state current. The phase …space of the feature signal is constructed by using determined time delay and embedding dimension. The second contribution is to optimize the detectors of the negative selection algorithm by clonal selection. The proposed clonal selection algorithm minimizes the overlap between the detectors and maximizes the coverage of the anomalous data. Because the feature extraction method and test stage of the negative selection algorithm have low computational complexity, the last contribution is Field-Programmable-Gate-Array (FPGA) implementation for online detection of rotor related faults. The obtained results indicate that the proposed methodology demonstrates a high performance for diagnosis of rotor faults in induction motors. Show more

Keywords: Negative selection algorithm, clonal selection, FPGA, induction motors, fault detection

DOI: 10.3233/JIFS-161964

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 1, pp. 689-701, 2018

Authors: Ameri, R. | Asghari-Larimi, M. | Firouzkouhi, N.

Article Type: Research Article

Abstract: Let H be a hypersemigroup(hypergroup), we associate a fuzzy geometric spaces ( Δ , B ˜ ) to H , where Δ is a nonzero fuzzy subset of H and B ˜ is a family of nonzero fuzzy subsets of H such that B ˜ ⊆ Δ . Also, we prove that this fuzzy geometric space is strongly transitive on hypergroups, while it is not strongly transitive on hypersemigroups.

Keywords: Fuzzy geometric spaces, fuzzy hypesemigroup, fuzzy hypergroup, strongly transitive, fuzzy geometric spaces

DOI: 10.3233/JIFS-162444

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 1, pp. 703-709, 2018

Authors: Wang, Guo-Fang | Fang, Zhou | Li, Ping

Article Type: Research Article

Abstract: Reusing knowledge obtained in other related but different tasks to accelerate the learning procedure of reinforcement learning (RL) has attracted more and more attention and expert knowledge transfer is the root cause of positive effect. Nevertheless, compared with acquiring knowledge by RL training in source tasks, this paper proposes to transfer knowledge contained in human-demonstrations of source tasks. Based on this, three specific forms of knowledge in total are mined from demonstration trajectories to be reused in the target task to shape RL and all of them are closely associated with the similarity between states of different tasks which can …be measured by Euclidean distance via human-supplied inter-task mappings. In more detail, the similarity between the target state and the most similar state in source samples, the proportion of different actions among the k -NN of the target state in source samples and the proportion of different actions under a constant similarity with the target state in source samples are respectively selected to initialize the value of state-action function. Simulation experiments of mountain car problems with different difficulties and different dimensions suggest that all the three shaping methods could obviously speed up RL. In comparison, it can also be found that the two latter methods are more robust and efficient to the quality of human demonstrations as it takes more source samples’ information into consideration. Show more

Keywords: Transfer, human-demonstrations, shaping, reinforcement learning

DOI: 10.3233/JIFS-17052

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 1, pp. 711-720, 2018

Authors: Fan, Fengfei | Gai, Shan

Article Type: Research Article

Abstract: A new de-noising algorithm by using the Laplace model and the Normal Inverse Gauss model based on the non-subsampled contourlet transform is proposed. Firstly, the sub-band coefficients of non-subsampled transform are fitted by using the joint statistical model which can capture the texture information well of the natural image. Secondly, the new adjustment factor is introduced to improve the coefficients fitting accuracy of the joint statistical model. Finally, the new parameter estimation algorithm is proposed under the Bayesian estimation framework. The experimental results show that the proposed algorithm obtains better visual effects and de-noising results compared with the state-of-art de-noising …algorithms. Show more

Keywords: Image de-noising, non-subsampled contourlet transform, laplace model, normal Inverse Gaussian model, bayesian estimation

DOI: 10.3233/JIFS-17434

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 1, pp. 721-731, 2018

Authors: Song, Qingfeng | Shi, Kai | Lin, Sheng | Xu, Guangping | Yang, Oliver | Wang, Jinsong

Article Type: Research Article

Abstract: This paper investigates the problems of making optimal decisions on pricing and shelf-space for a fuzzy supply chain with one perishable product, with the help of Radio Frequency Identification Device (RFID) technology to reduce shrinkage. Based on the criterion of Value-at-Risk (VaR) and its minimization, we introduce one centralized decision model and three decentralized decision models to obtain the respective optimal decisions of both the manufacturer and the retailer, by analyzing the fuzzy uncertainties and the relationship among the demand, retail price and shelf-space. The corresponding optimal strategies of the two participants are obtained along with one example.

Keywords: Fuzzy variable, supply chain, Radio Frequency Identification Devices (RFID), Value-at-Risk (VaR), game theory

DOI: 10.3233/JIFS-17508

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 1, pp. 733-744, 2018

Authors: ur Rahman, Ghaus | Din, Qamar | Faizullah, Faiz | Khan, Faiz Muhammad

Article Type: Research Article

Abstract: In this paper, we study the qualitative behavior of the positive solutions of a second-order rational fuzzy difference equations with initial conditions and parameters are positive fuzzy numbers. More precisely, we investigate existence of positive solutions, boundedness, persistence and stability analysis of a second-order fuzzy rational difference equation. Some numerical examples are given to verify our theoretical results.

Keywords: Fuzzy difference equations, existence of solutions, boundedness character, local and global behavior

DOI: 10.3233/JIFS-17922

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 1, pp. 745-753, 2018