Journal of Intelligent & Fuzzy Systems - Volume 40, issue 6

Authors: Jiang, Chunmao | Guo, Doudou | Sun, Lijuan

Article Type: Research Article

Abstract: The basic idea of the three-way decisions (3WD) is ‘thinking in threes.’ The TAO (trisecting-acting-outcome) model of 3WD includes three components, trisect a whole into three reasonable regions, devise a corresponding strategy on the trisection, and measure the effectiveness of the outcome. By reviewing existing studies, we found that only a few papers touch upon the third component, i.e., measure the effect. This paper’s principal aim is to present an effectiveness measure framework consisting of three parts: a specific TAO model - Change-based TAO model, interval sets, and utility functions with unique characteristics. Specifically, the change-based TAO model provides a …method to measure effectiveness based on the difference before and after applying a strategy or an action. First, we use interval sets to represent these changes when a strategy or an action is applied. These changes correspond to three different intervals. Second, we use the utility measurement method to figure out three change intervals. Namely, different utility measures correspond to the different intervals, concave utility metric, direct utility metric, and convex utility metric, respectively. Third, it aggregates the toll utility through the joint of the three utilities mentioned above. The weights among these three are adjusted by a dual expected utility function that conveys the decision-makers’ preferences. We give an example and experiment highlighting the validity and practicability of the utility measure method in the change-based TAO model of three-way decisions. Show more

Keywords: Three-way decisions, change-based TAO model, interval set, utility measurement, dual expected utility

DOI: 10.3233/JIFS-202207

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11071-11084, 2021

Authors: Qian, Tiancheng | Mei, Xue | Xu, Pengxiang | Ge, Kangqi | Qiu, Zhelei

Article Type: Research Article

Abstract: Recently many methods use encoder-decoder framework for video captioning, aiming to translate short videos into natural language. These methods usually use equal interval frame sampling. However, lacking a good efficiency in sampling, it has a high temporal and spatial redundancy, resulting in unnecessary computation cost. In addition, the existing approaches simply splice different visual features on the fully connection layer. Therefore, features cannot be effectively utilized. In order to solve the defects, we proposed filtration network (FN) to select key frames, which is trained by deep reinforcement learning algorithm actor-double-critic. According to behavior psychology, the core idea of actor-double-critic is …that the behavior of agent is determined by both the external environment and the internal personality. It avoids the phenomenon of unclear reward and sparse feedback in training because it gives steady feedback after each action. The key frames are sent to combine codec network (CCN) to generate sentences. The operation of feature combination in CCN make fusion of visual features by complex number representation to make good semantic modeling. Experiments and comparisons with other methods on two datasets (MSVD/MSR-VTT) show that our approach achieves better performance in terms of four metrics, BLEU-4, METEOR, ROUGE-L and CIDEr. Show more

Keywords: Video captioning, deep reinforcement learning, frame sampling, feature fusion, sparse reward, actor-critic

DOI: 10.3233/JIFS-202249

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11085-11097, 2021

Authors: Chen, Yang | Yang, Jiaxiu

Article Type: Research Article

Abstract: In recent years, interval type-2 fuzzy logic systems (IT2 FLSs) have become a hot topic for the capability of coping with uncertainties. Compared with the centroid type-reduction (TR), investigating the center-of-sets (COS) TR of IT2 FLSs is more favorable for applying IT2 FLSs. Actually, it is still an open question for comparing Karnik-Mendel (KM) types of algorithms and other types of alternative algorithms for COS TR. This paper gives the block of fuzzy reasoning, COS TR, and defuzzification of IT2 FLSs based on Nagar-Bardini (NB), Nie-Tan (NT) and Begian-Melek-Mendel (BMM) noniterative algorithms. Six simulation experiments are used to show the …performances of three types of noniterative algorithms. The proposed noniterative algorithms can obtain much higher computational efficiencies compared with the KM algorithms, which give the potential value for designing T2 FLSs. Show more

Keywords: Interval type-2 fuzzy logic systems, center-of-sets type-reduction, Nagar-Bardini algorithms, computational efficiency, Nie-Tan algorithms

DOI: 10.3233/JIFS-202264

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11099-11106, 2021

Authors: Li, Mengmeng | Zhang, Chiping | Chen, Minghao | Xu, Weihua

Article Type: Research Article

Abstract: Multi-granulation decision-theoretic rough sets uses the granular structures induced by multiple binary relations to approximate the target concept, which can get a more accurate description of the approximate space. However, Multi-granulation decision-theoretic rough sets is very time-consuming to calculate the approximate value of the target set. Local rough sets not only inherits the advantages of classical rough set in dealing with imprecise, fuzzy and uncertain data, but also breaks through the limitation that classical rough set needs a lot of labeled data. In this paper, in order to make full use of the advantage of computational efficiency of local rough …sets and the ability of more accurate approximation space description of multi-granulation decision-theoretic rough sets, we propose to combine the local rough sets and the multigranulation decision-theoretic rough sets in the covering approximation space to obtain the local multigranulation covering decision-theoretic rough sets model. This provides an effective tool for discovering knowledge and making decisions in relation to large data sets. We first propose four types of local multigranulation covering decision-theoretic rough sets models in covering approximation space, where a target concept is approximated by employing the maximal or minimal descriptors of objects. Moreover, some important properties and decision rules are studied. Meanwhile, we explore the reduction among the four types of models. Furthermore, we discuss the relationships of the proposed models and other representative models. Finally, illustrative case of medical diagnosis is given to explain and evaluate the advantage of local multigranulation covering decision-theoretic rough sets model. Show more

Keywords: Covering rough sets, local rough sets, local covering rough sets, multigranulation rough sets

DOI: 10.3233/JIFS-202274

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11107-11130, 2021

Authors: Wei, Shanting | Zhang, Zhuo | Chen, Xintong

Article Type: Research Article

Abstract: Network-based incubation has undergone rapid developments and the incubation mechanism has begun to change recently. To incentive the start-ups on the basis of ensuring its own interests, the incubator needs to design a feasible contract. According to network theory, a single network cannot adequately describe the heterogeneous alliances of incubated start-ups in the business incubator. Therefore, by constructing super-network structure of incubated start-ups, this paper designs two types of linear incentive contracts and uses numerical simulation to further discuss the model. The results indicate that the business incubator should design the contract according to the different capability levels and risk …preference degree of start-ups: linear screening contract (LSC) is more effective to motivate the incubated start-ups to improve the capability, while the incentive effect will be weakened by the increasing proportion of high-capability start-ups; for high risk-preference start-ups, linear pooling contract (LPC) is superior than LSC. The results can serve as a theoretical direction for the business incubator to effectively distinguish different capability levels of start-ups and make better decision on contract design to motivate start-ups on the basis of ensuring the maximization of its own utility. Show more

Keywords: Business incubator, start-up, super-network, dynamic capability, cooperative network, knowledge network

DOI: 10.3233/JIFS-202279

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11131-11144, 2021

Authors: Chen, Kuen-Suan | Yu, Chun-Min

Article Type: Research Article

Abstract: Many corporations purchase components from suppliers, which can reduce operating costs and enable firms to focus their resources on core advantages. Studies have indicated that process quality and manufacturing time performance are two crucial indicators for supplier selection. We used the process quality index and a manufacturing time performance index to create a dual dimensional fuzzy supplier selection model. First, the upper confidence limits of these two indices were derived, and a fuzzy membership function based on these limits was constructed. Based on the fuzzy test rules for process quality and manufacturing time performance, we divided the fuzzy supplier selection …matrix into nine evaluation zones. Using the upper confidence limits of these two indices, we created evaluation coordinates and assigned weights based on the location of the coordinates. Then, the total of all the weights was employed to form a supplier selection index for which a higher value means a higher ranking. The use of confidence limits decreased the chance of misjudgment resulting from sampling errors while the fuzzy test rules increased the applicability of the model. Consequently, the proposed model can be used to select suppliers efficiently so as to form partnerships in which corporations and suppliers can grow together. Show more

Keywords: Fuzzy supplier selection model, fuzzy membership function, manufacturing time performance, process quality, upper confidence limit

DOI: 10.3233/JIFS-202349

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11145-11158, 2021

Authors: Lei, Shi

Article Type: Research Article

Abstract: An improved Web community discovery algorithm is proposed in this paper based on the attraction between Web pages to effectively reduce the complexity of Web community discovery. The proposed algorithm treats each Web page in the Web pages collection as an individual with attraction based on the theory of universal gravitation, elaborates the discovery and evolution process of Web community from a Web page in the Web pages collection, defines the priority rules of Web community size and Web page similarity, and gives the calculation formula of the change in Web page similarity. Finally, an experimental platform is built to …analyze the specific discovery process of the Web community in detail, and the changes in cumulative distribution of Web page similarity are discussed. The results show that the change in the similarity of a new page satisfies the power-law distribution, and the similarity of a new page is proportional to the size of Web community that the new page chooses to join. Show more

Keywords: Web community, web page, attraction, evolution process, web page similarity

DOI: 10.3233/JIFS-202366

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11159-11169, 2021

Authors: He, Weiming | Wu, You | Xiao, Jing | Cao, Yang

Article Type: Research Article

Abstract: Feature pyramids are commonly applied to solve the scale variation problem for object detection. One of the most representative works of feature pyramid is Feature Pyramid Network (FPN), which is simple and efficient. However, the fully power of multi-scale features might not be completely exploited in FPN due to its design defects. In this paper, we first analyze the structure problems of FPN which prevent the multi-scale feature from being fully exploited, then propose a new feature pyramid structure named Mixed Group FPN (MGFPN) , to mitigate these design defects of FPN. Concretely, MGFPN strengthens the feature utilization by two …modules named Mixed Group Convolution(MGConv) and Contextual Attention(CA) . MGConv reduces the spatial information loss of FPN in feature generation stage. And CA narrows the semantic gaps between features of different receptive field before lateral summation. By replacing FPN with MGFPN in FCOS, our method can improve the performance of detectors in many major backbones by 0.7 to 1.2 Average Precision(AP) on MS-COCO benchmark without adding too much parameters and it is easy to be extended to other FPN-based models. The proposed MGFPN can serve as a simple and strong alternative for many other FPN based models. Show more

Keywords: Object Detection, Feature Pyramids, FPN, Mixed Group Convolution, Contextual Attention

DOI: 10.3233/JIFS-202372

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11171-11181, 2021

Authors: Touqeer, Muhammad | Umer, Rimsha | Ali, Muhammad Irfan

Article Type: Research Article

Abstract: Pythagorean fuzzy sets and interval-valued Pythagorean fuzzy sets are more proficient in handling uncertain and imprecise information than intuitionistic fuzzy sets and fuzzy sets. In this article, we put forward a chance-constraint programming method to solve linear programming network problems with interval-valued Pythagorean fuzzy constraints. This practice is developed using score function and upper and lower membership functions of interval-valued Pythagorean fuzzy numbers. The feasibility of the anticipated approach is illustrated by solving an airway network application and shown to be used to solve different types of network problems with objective function having interval-valued Pythagorean fuzzy numbers by employing it …on shortest path problem and minimum spanning tree problem. Furthermore, a comparative examination was performed to validate the effectiveness and usefulness of the projected methodology. Show more

Keywords: Interval-valued pythagorean fuzzy number (IVPFN), interval-valued trapezoidal pythagorean number (IVTrPFN), linear programming problem (LPP), chance-constraint programming (CCP)

DOI: 10.3233/JIFS-202383

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11183-11199, 2021

Authors: Zeng, Shaohua | Wu, Yalan | Wang, Shuai | He, Ping

Article Type: Research Article

Abstract: The segmentation and extraction of the purple soil region from purple soil color image can effectively avoid the influence of background on recognition of soil types. A scale weighted fuzzy c-means clustering algorithm(SWFCM) is proposed for effective segmentation of purple soil color image. The main work is to establish the maximum difference optimization model with the mean of Gaussian distance between each pixel and each peak of the image histogram, and optimize the clustering number and the initial clustering centers. Then, the compactness of each class is defined to weight the Euclidean distance between the pixel and the clustering center …and improve the optimization model of FCM for raising its clustering performance. Aiming at the problem of removing scattered small soil blocks in the background and filling holes in the purple soil region, the algorithm of extracting the boundary of the purple soil region and the algorithm of filling the purple soil region are proposed. Finally, the normal and robust experiments are carried out on the normal sample set and robust sample set. And the performances of relative algorithms are compared, which involves the previously released FCM algorithms and some methods for the segmentation of purple soil color image and our proposed algorithm. Experimental results show that performance of SWFCM is better and it can provide a high reference for adaptive segmentation of purple soil color images. Especially for robust experiment images, its average segmentation accuracy is improved by 6 . 64% ∼ 8 . 25 % compared with other purple soil segmentation algorithms. Show more

Keywords: color image segmentation, purple soil, fuzzy c-means clustering(FCM)

DOI: 10.3233/JIFS-202401

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 11201-11215, 2021