Journal of Intelligent & Fuzzy Systems - Volume 37, issue 1

Authors: Fahandezi Sadi, Majid | Ansari, Ebrahim | Afsharchi, Mohsen

Article Type: Research Article

Abstract:  Supervised Word Sense Disambiguation (WSD) systems use features of the target word and its context to learn about all possible samples in an annotated dataset. Recently, word embeddings have emerged as a powerful feature in many NLP tasks. In supervised WSD, word embeddings can be used as a high-quality feature representing the context of an ambiguous word. In this paper, four improvements to existing state-of-the-art WSD methods are proposed. First, we propose a new model for assigning vector coefficients for a more precise context representation. Second, we apply a PCA dimensionality reduction process to find a better transformation of feature …matrices and train a more informative model. Third, a new weighting scheme is suggested to tackle the problem of unbalanced data in standard WSD datasets and finally, a novel idea is presented to combine word embedding features extracted from different independent corpora, which uses a voting aggregator among available trained models. All of these proposals individually improve disambiguation performance on Standard English lexical sample tasks, and using the combination of all proposed ideas makes a significant improvement in the accuracy score. Show more

Keywords: Word sense disambiguation, Word embedding, Supervised learning, Support vector machine

DOI: 10.3233/JIFS-182868

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1467-1476, 2019

Authors: Wang, Guijun | Gao, Jiansi

Article Type: Research Article

Abstract: Simple binary coded genetic algorithm (GA) and particle swarm optimization (PSO) fall easily into local minimums and fail to find the global optimal solution to the algorithm. Thus, the development of a hybrid algorithm between GA and PSO is urgently demanded. In this paper, a three-layer polygonal fuzzy neural network (PFNN) model and its error function are first given by the arithmetic operations of the polygonal fuzzy numbers. Second, the random sequences are constructed by a chaos random generator, these random sequences are used as the initial population of chaos GA and the optimal individuals for sub-populations gained by chaos …search are used as the initial population of PSO, and then an new parallel conjugate gradient-particle swarm optimization (PCG-PSO) is designed. Finally, a case study shows the proposed parallel CG-PS algorithm not only avoids dependence of traditional GA on initial values and overcomes the poor global optimization capability of traditional PSO, but also possesses advantages of rapid convergence and high stability. Show more

Keywords: Polygonal fuzzy number, polygonal fuzzy neural network, chaos genetic algorithm, particle swarm optimization, parallel conjugate gradient-particle swarm optimization

DOI: 10.3233/JIFS-182882

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1477-1489, 2019

Authors: Jani, Kuntesh K. | Srivastava, Subodh | Srivastava, Rajeev

Article Type: Research Article

Abstract: One of the most common lesions of the gastrointestinal tract (GIT) is an ulcer. Capsule endoscopy (CE) is a recent advancement in the field of gastroenterology for diagnosis of GIT abnormalities. However, CE video length ranges from 6 to 8 hours generating approximately 60000 images. For a medical expert, examination of such lengthy videos is time-consuming and tiresome. Also, the accuracy of diagnosis will largely depend upon individual expertise. A computer-aided diagnosis (CAD) system can significantly improve accuracy and reduce diagnosis time. In the proposed automated ulcer detection system, relevant features of the histogram of oriented gradients (HOG) and uniform …local binary patterns (LBP) are optimally selected by high variance low correlation (HVLC) based novel feature selection technique and the classification task is performed using support vector machine (SVM). Proposed feature selection technique reduces the feature set by 96.53% and outperforms five other state of the art feature selection techniques. The performance of proposed system is compared with other systems and it performs with accuracy, F measure and sensitivity of 95%, 95.12%, and 97.5% respectively. Show more

Keywords: Automated ulcer detection, CAD, capsule endoscopy, feature selection, HVLC

DOI: 10.3233/JIFS-182883

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1491-1498, 2019

Authors: Xing, Zhikai | Jia, Heming | Song, Wenlong

Article Type: Research Article

Abstract: Considering that the 3D pulse-coupled neural network (3D-PCNN) model has the deficiency of high parameter complexity and low accuracy in color image segmentation, swarm intelligence optimization algorithm is adopted to optimize the image segmentation process. In this paper, whale optimization algorithm (WOA) is adopted to optimize the 3D-PCNN model parameters E and β . The improved product cross entropy (IPCE) is chosen as the fitness function of optimization algorithm. WOA algorithm is used to find the minimum fitness function, and the corresponding optimal parameters are obtained. Through the study of image segmentation in the image segmentation library of University of …Berkeley and the actual plant canopy image, the maximum entropy value and the Tsallis entropy value are compared and analyzed. Experimental results illustrate that the proposed algorithm can obtain more accurate image segmentation effect and higher segmentation rate. Show more

Keywords: 3D-PCNN, color image segmentation, whale optimization algorithm, improved product cross entropy

DOI: 10.3233/JIFS-182893

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1499-1511, 2019

Authors: Zuo, Wen-Jin | Li, Deng-Feng | Yu, Gao-Feng | Zhang, Li-Ping

Article Type: Research Article

Abstract: With the development of modern property service industry, the property perceived service quality (PPSQ) evaluation data is characterized by multiple evaluation subjects, complicated data structure and large scale data. Since the traditional decision-making methods are difficult to solve the above similar problems, this paper proposes a large group decision-making (LGDM) method of generalized multi-attribute and multi-scale (MAMS) based on the linear programming technique for multidimensional analysis of preference (LINMAP). In this method, the large-scale heterogeneous data of expert preference and user evaluation is fused. The decision matrix of generalized MAMS is used to process user evaluation information. The positive ideal …solution (PIS) and the attribute weights are determined by the LINMAP model. The comprehensive evaluation values are calculated and hereby the alternatives are ranked order. According to the relation between attribute weights and preset values, a mechanism for identifying invalid data is designed. This paper analyzes a set of survey data of PPSQ for the four public construction projects in the same city. The analysis results show the validity and rationality of the proposed method, and develop the property service evaluation theory. Show more

Keywords: Large group decision-making, generalized multi-attribute and multi-scale method, linear programming technique for multidimensional analysis of preference, large-scale heterogeneous data processing, property perceived service quality

DOI: 10.3233/JIFS-182934

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1513-1527, 2019

Authors: Abbas, Syed Zaheer | Ali Khan, Muhammad Sajjad | Abdullah, Saleem | Sun, Huafei | Hussain, Fawad

Article Type: Research Article

Abstract: Pythagorean fuzzy sets (PFSs) and interval-valued Pythagorean fuzzy sets (IVPFSs) play a vital role in decision-making processes. In this paper based on PFS and IVPFS we introduce the concept of Cubic Pythagorean fuzzy set in which membership degree is an IVPFS and non-membership degree is a PFS. We define some basic operation of Cubic Pythagorean fuzzy numbers (CPFNs). We define score and accuracy functions to compare CPFNs. We also define distance between CPFNs. Based on the defined operations we develop Cubic Pythagorean fuzzy weighted averaging (CPFWA) operator and Cubic Pythagorean fuzzy weighted geometric (CPFWG) operator. We discuss some properties of …the developed operators such as idempotancy, boundedness and monotonicity. Moreover, we give a multi-attribute decision making, to show the validity and effectiveness of the developed approach. Finally, we compare our approach with the existing methods. Show more

Keywords: Pythagorean fuzzy sets, interval-valued Pythagorean fuzzy sets, Cubic Pythagorean fuzzy sets, Cubic Pythagorean fuzzy weighted averaging (CPFWA) operator, Cubic Pythagorean fuzzy weighted geometric (CPFWG) operator, decision making

DOI: 10.3233/JIFS-18382

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1529-1544, 2019

Authors: Rahman, Atta

Article Type: Research Article

Abstract: In this paper, a numerical solution to the Troesch problem using a memetic computing technique is proposed. In this regard, a linear combination of Gaussian radial basis functions (GRBF) as approximate mathematical framework is suggested. A set of unknown yet adaptable parameters are modeled in a cost function, representing the trial solution. Differential Evolution (DE) algorithm crossed with Interior Point algorithm (IPA) and Pattern Search (PS) are utilized to find the unknowns. Numerical results based on three special cases of proposed scheme are compared with the exact solution as well as many other numerical and classical approximation methods. Analysis reveals …that the proposed scheme is promising in terms of accuracy and conformation to the exact solution. Show more

Keywords: Troesch problem, differential evolution, gaussian radial basis function, boundary value problem, pattern search (PS), interior point algorithm (IPA), memetic computing (MC)

DOI: 10.3233/JIFS-18579

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1545-1554, 2019

Authors: Zhang, Haidong | He, Yanping | Ma, Weiyuan

Article Type: Research Article

Abstract: Through a combination of hesitant fuzzy sets with rough sets, this study develops a single-granulation hesitant fuzzy rough set model from the perspective of granular computing. In the multi-granulation framework, we propose two types of multi-granulation rough set model, called the optimistic multi-granulation hesitant fuzzy rough sets and pessimistic multi-granulation hesitant fuzzy rough sets. In the models, the multi-granulation hesitant fuzzy lower and upper approximations are defined based on multiple hesitant fuzzy tolerance relations. The relationships among the single-granulation hesitant fuzzy rough sets, optimistic multi-granulation hesitant fuzzy rough sets and pessimistic multi-granulation hesitant fuzzy rough sets are also investigated. Finally, …we develop an approximation reduction approach of multi-granulation hesitant fuzzy rough sets to eliminate redundant hesitant fuzzy granulations with a detailed example. Show more

Keywords: Single-granulation hesitant fuzzy rough set, Multi-granulation hesitant fuzzy rough set, Hesitant fuzzy granulations, Approximation reduction

DOI: 10.3233/JIFS-18586

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1555-1567, 2019

Authors: Wang, Fang | Li, Xiao-Tong | Zhao, Jin | Chen, Shao-Hua

Article Type: Research Article

Abstract: The multiple attribute decision making (MADM) with interval grey uncertain linguistic (IGUL) is a topic of current interest, and various methods have been developed. However, few approaches taking the behavioral characteristics of the decision maker into account. In this paper, an extension of TODIM (i.e., an acronym in Portuguese of interactive and multiple attribute decision making) method, in which three behavioral characteristics of the decision maker (i.e., risk aversion, reference dependence and loss aversion) are considered, is proposed. First, the δ -Hamming distance is defined to deal with the interval grey uncertain linguistic variables by considering the level of the …decision maker’s risk aversion, and its distinguish ability is validated by compared to the classical Hamming distance. Then, the details of the TODIM· SIR method is demonstrated: (i) considering the reference dependence behaviour of the decision maker, the positive-ideal alternative (i.e., PIA ) and the negative-ideal alternative (i.e., NIA ) are defined, and the gain and loss degrees of each alternative relative to NIA and PIA are computed based on the δ -Hamming distance; (ii) taking the loss aversion behaviour of the decision maker into account, the perceived dominance degree of the decision maker for the gain and the loss is calculated; (iii) according to the idea of the Superiority and Inferiority Ranking method (i.e., SIR, an outranking method), the Gain-flow and the Loss-flow are defined, and the partial ranking orders and the complete ranking order are obtained. Finally, two numerical examples are given to illustrate the robustness and validity of the method, and a comparative analysis is also conducted to compare the TODIM· SIR method with both the classical TODIM method and the classical SIR method. Show more

Keywords: TODIM, SIR, Multiple attribute decision making, interval grey uncertain linguistic

DOI: 10.3233/JIFS-18654

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1569-1581, 2019