Journal of Intelligent & Fuzzy Systems - Volume 37, issue 2

Authors: Qi, Geqi | Guan, Wei | He, Zhengbing | Huang, Ailing

Article Type: Research Article

Abstract: The well-known Fuzzy C-Means (FCM) algorithm and its modified clustering derivatives have been widely applied in various fields. However, previous studies have focused on the yield of correctly clustered data, and few have addressed the alignment of extracted influential areas of clusters to natural cluster structure. Various clustering algorithms present diverse characteristics in cluster structure detection due to the different clustering principles involved. For example, Mahalanobis distance-based FCM algorithms effectively detect the influential direction of each cluster, while kernel-based FCM algorithms provide an interface for adjusting the influential range. Combining the advantages of these previous algorithms, the Adaptive Kernel Fuzzy …C-Means (AKFCM) algorithm based on cluster structure is proposed in this paper. The AKFCM algorithm can effectively detect the influential direction and adjust the influential range of each cluster with adaptive kernelization. By applying the previous and AKFCM algorithms to both synthetic and real-world datasets, the proposed algorithm is proven to achieve better performance not only in clustering accuracy but also in the extraction of reasonable influential areas. The proposed algorithm could be helpful for clustering datasets composed of clusters with different directions and ranges in structure. Show more

Keywords: Fuzzy C-Means, mahalanobis distance, kernel fuzzy C-Means, influential area, adaptive kernel

DOI: 10.3233/JIFS-182750

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 2, pp. 2453-2471, 2019

Authors: Riaz, Muhammad | Tehrim, Syeda Tayyba

Article Type: Research Article

Abstract: A huge range of human decisions is involved bipolar subjective thoughts. For illustration, effects and side effects are two different aspects of decision analysis. The equilibrium and mutual coexistence of these two aspects are treated as a key for balanced social environment. A verity of bipolar fuzzy decision making with different technique is available for bipolar fuzzy characterizations of the universe of options that depend on a limited number of grades. So, the concept of simple bipolar fuzzy set is insufficient to provide the information about the occurrence of ranking with accuracy because information is limited. In this regard, we …use cubic bipolar fuzzy sets (CBFSs) as the generalization of bipolar fuzzy sets. In human decisions, the second important part is ranking of alternatives obtained after evaluation. The motivation behind this research is to develop an appropriate aggregation method which is simple reliable and efficient enough to handle cubic bipolar fuzzy data. We propose aggregation operators, including, cubic bipolar fuzzy weighted averaging operator, cubic bipolar fuzzy ordered weighted averaging operator and cubic bipolar fuzzy hybrid weighted averaging operator for P -order and R -order. We demonstrate simplicity and efficiency of proposed aggregation operators and algorithm by discussing multi-attribute group decision making (MAGDM) problem under cubic bipolar fuzzy information. We also discuss the comparison analysis of the proposed method of aggregation. Show more

Keywords: Cubic bipolar fuzzy set, Averaging aggregation operators for CBFSs, MAGDM

DOI: 10.3233/JIFS-182751

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 2, pp. 2473-2494, 2019

Authors: Salgado, Silvio Antônio Bueno | de Barros, Laécio Carvalho | Esmi, Estevão | Eduardo Sánchez, Daniel

Article Type: Research Article

Abstract:  In this paper, we consider a type of fuzzy harmonic oscillator described by a differential equation of the form x ″ + a 2 x  = 0 with initial conditions given by fuzzy numbers. Here, we assume that x ″ (t ) and a 2 x  (t ) are linearly correlated fuzzy numbers for t ∈ ℝ and a ∈ ℝ , a ≠ 0 . In general, this assumption is necessary for the equality x ″ + a 2 x  = 0 to make sense. Using this interactive relation, we obtain a solution …for this problem using a fuzzy Laplace transform method. Show more

Keywords: Interactive fuzzy numbers, Fuzzy differential equation, Fuzzy Laplace transform, Fuzzy harmonic oscillator

DOI: 10.3233/JIFS-182761

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 2, pp. 2495-2501, 2019

Authors: Zheng, Tao | Li, Bo | Yao, Jiaxu

Article Type: Research Article

Abstract: Deep convolutional neural networks (CNNs) have shown outstanding performance in salient object detection. However, there exist two conundrums under-explored. 1) High-level features are beneficial to locate salient objects while low-level features contain fine-grained details. How to combine these two types of features to promote accuracy is the first conundrum. 2) Previous CNN-based methods adopt a convolutional layer after extracting features to infer saliency maps. While encountering images that are different greatly from training dataset, adopting a convolutional layer as a classifier is not robust enough to detect all salient objects. In addition, limited receptive field and lack of spatial correlation …will cause salient objects to be incomplete while blurring their boundaries. In this paper, a Lateral Hierarchically Refining Network (LHRNet) is put forward for accurate salient object detection. Firstly, LHRNet efficiently integrates multi-level features, which simultaneously incorporates coarse semantics and fine details. Then a coarse saliency prediction is made from low-resolution features by convolution. Finally, a series of nearest neighbor classifiers are learned to hierarchically restore the missing parts of salient objects while refining their boundaries, yielding a more reliable final prediction. Comprehensive experiments demonstrate that this network performs favorably against state-of-the-art approaches on six datasets. Show more

Keywords: Salient object detection, Deep learning, Convolutional neural networks

DOI: 10.3233/JIFS-182769

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 2, pp. 2503-2514, 2019

Authors: Liu, Peide | Khan, Qaisar | Mahmood, Tahir

Article Type: Research Article

Abstract: The power average (PA) has the property that it can eliminate the influence of inconvenient data and the Muirhead mean (MM) operator takes the correlations among the input arguments, and the single valued neutrosophic (SVN) set is a better tool to deal with incomplete, inconsistent and indeterminate information than fuzzy set (FS) and intuitionistic FS (IFS). Thus the main goal of this article is to develop a few new operators for aggregating SVN information and apply them to multiple-attribute group decision making (MAGDM). To fully utilize the advantages of MM operator and PA operator, we develop the single-valued neutrosophic power …MM (SVNPMM) operator, weighted single-valued neutrosophic power MM (WSVNPMM) operator, single-valued neutrosophic power dual MM (SVNPDMM) operator and weighted single-valued neutrosophic power dual MM (WSVNPDMM) operator, and discuss their essential properties, particular cases about the parameter vector. The obvious advantages of the proposed operators are that it can eliminate the influence of inconvenient data and can take the correlation among input data at the same time. Moreover, based on the developed aggregation operators, a novel technique to MAGDM problem is proposed. Lastly, a numerical example is provided to show the efficiency and realism of the proposed technique. Show more

Keywords: Power average, muirhead mean operator, single valued neutrosophic sets, MAGDM

DOI: 10.3233/JIFS-182774

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 2, pp. 2515-2537, 2019

Authors: Khalid, Asma | Beg, Ismat

Article Type: Research Article

Abstract: The aim of this paper is to introduce the notion of truthfulness in an influence based decision making model. An expert may submit his opinions truthfully or he may dismantle the original situation by undermining the actual opinion, such a decision maker is called an evasive decision maker or an almost truthful decision maker in this paper. It is assumed that experts in the panel are dignified members hence even though they are not habitual liars, they are either “almost truthful” or evasive. To measure their degree of truthfulness, we use the information provided by them in the form of …preference relations. We use this information to state the foundation of influence model of evasive decision makers. Finally, a ranking method is proposed to find best possible solutions. Show more

Keywords: Truthfulness, group decision making, social influence networks, additive reciprocity

DOI: 10.3233/JIFS-182775

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 2, pp. 2539-2548, 2019

Authors: Khan, Jan Sher | Ahmad, Jawad | Ahmed, Saygin Siddiq | Siddiqa, Hafza Ayesha | Abbasi, Saadullah Farooq | Kayhan, Sema Koç

Article Type: Research Article

Abstract: With the exponential growth of Internet technologies, digital information exchanged over the Internet is also significantly increased. In order to ensure the security of multimedia contents over the open natured Internet, data should be encrypted. In this paper, the quantum chaotic map is utilized for random vectors generation. Initial conditions for the chaos map are computed from a DNA (Deoxyribonucleic acid) sequence along with plaintext image through Secure Hash Algorithm-512 (SHA-512). The first two random vectors break the correlation among pixels of the original plaintext image via row and column permutation, respectively. For the diffusion characteristics, the permuted image is …bitwise XORed with a random matrix generated through the third random vectors. The diffused image is divided into Least Significant Bit (LSB) and Most Significant Bits (MSBs) and Discrete Wavelet Transform (DWT) is applied to the carrier image. The HL and HH blocks of the carrier image are replaced with LSBs and MSBs of the diffused image for the generation of a visually encrypted image. The detailed theoretical analysis and experimental simulation of the designed scheme show that the proposed encryption algorithm is highly secured. Efficiency and robustness of the proposed visually image encryption scheme is also verified via a number of attack analyses, i.e., sensitivity attack analysis (> 99%), differential attack analysis (NPCR > 99, UACI > 33), brute force attack (almost 7.9892), statistical attack (correlation coefficient values are almost 0 or less than zero), noise tolerance, and cropping attack. Further security analyses such as encryption quality (I D  ≅ 1564, D H  = 3.000), homogeneity (0.3798), contrast (10.4820) and energy (0.0144) of the scheme are also evaluated. Show more

Keywords: Light-weight, secure, visual image encryption, chaos, Deoxyribonucleic acid, permutation, diffusion

DOI: 10.3233/JIFS-182778

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 2, pp. 2549-2561, 2019

Authors: Sarwar Sindhu, M. | Rashid, Tabasam | Khan, M.

Article Type: Research Article

Abstract: Hesitant fuzzy sets (HFSs) play a dominant role in the decision making process. Different tools are developed to attract the decision makers (DMs) in making the effective decision, the hesitant fuzzy preference relation (HFPR) is one of the important implementation of them. Preference of an alternative over another alternative is a useful way to express the opinion of decision maker. In this paper, a hesitant fuzzy ranking (HFR) technique is established, constructed the hesitant fuzzy ranking from the HFPR in the group decision making situations. Secondly, a correlation between the alternatives is developed by using Spearman ranked correlation coefficient formula, …which helps the DMs to identify the better alternative. The novelty of the proposed strategy is that it evades the need to compute the cooperative preference relations and approvals are generated for the individuals in their original domains. Show more

Keywords: Hesitant fuzzy sets, Fuzzy preference relations, Hesitant fuzzy preference relation, Fuzzy rankings, Group decision making

DOI: 10.3233/JIFS-182780

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 2, pp. 2563-2573, 2019

Authors: Li, Yongjun | Wei, Jianshuang | Kang, Kai | Wu, Zhouyang

Article Type: Research Article

Abstract:  Aviation customer churn analysis is a difficult point, which has puzzled over airlines. The difficulties lie in the imbalance of customer churn data distribution and noisy data interference. Although some existing sampling techniques and ensemble models are good at dealing with class imbalance problem, noisy examples in dataset seriously affects the sampling quality and predictive accuracy of classifiers. Therefore, the purpose of our work is to effectively solve the problem of noise interference in imbalanced data classification and improve the effect of the ensemble classifier. In this paper, we propose a novel noise filtering algorithm that combined Tomek-link with distance …weighted KNN (TWK), which can effectively filter the noise from both minority and majority class in the imbalanced dataset and prevent relative value samples from being rejected by mistake. We integrate TWK and feature sampling into EasyEnsemble to get a new ensemble model, named FSEE-TWK for short, for customer churn analysis. The introduction of feature sampling to FSEE-TWK accelerate the process of training and avoid model over-fitting. We obtained imbalanced customer data from a major Chinese airline to predict potential churn customers. We use F-Measure and G-Mean to evaluate the performance of the new ensemble model. The experimental results show that the proposed model can effectively improve the classification of datasets and significantly reduce the training time of the model. Show more

Keywords: Aviation customer churn analysis, classification model, ensemble learning, noise filter, under-sampling

DOI: 10.3233/JIFS-182807

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 2, pp. 2575-2585, 2019

Authors: Li, Qing-Hua | Li, Hong-Yan

Article Type: Research Article

Abstract: Based on fuzzy inclusion order between L -subsets, stratified L -ordered uniform convergence spaces and stratified L -ordered limit spaces are introduced. It is shown that the resulting categories are all Cartesian closed topological categories. Also, the relationship among stratified L -ordered limit spaces, stratified L -ordered Cauchy spaces and stratified L -ordered uniform convergence spaces are investigated.

Keywords: (Stratified) L-ordered uniform convergence space, (Stratified) L-ordered limit space, (Stratified) L-ordered Cauchy space, Bireflective subcategory, Cartesian closed category

DOI: 10.3233/JIFS-182808

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 2, pp. 2587-2596, 2019