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The purpose of the Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology is to foster advancements of knowledge and help disseminate results concerning recent applications and case studies in the areas of fuzzy logic, intelligent systems, and web-based applications among working professionals and professionals in education and research, covering a broad cross-section of technical disciplines.
The journal will publish original articles on current and potential applications, case studies, and education in intelligent systems, fuzzy systems, and web-based systems for engineering and other technical fields in science and technology. The journal focuses on the disciplines of computer science, electrical engineering, manufacturing engineering, industrial engineering, chemical engineering, mechanical engineering, civil engineering, engineering management, bioengineering, and biomedical engineering. The scope of the journal also includes developing technologies in mathematics, operations research, technology management, the hard and soft sciences, and technical, social and environmental issues.
Authors: Abbasizadeh, N. | Davvaz, B.
Article Type: Research Article
Abstract: This paper provides a new connection between algebraic hyperstructures and fuzzy sets. We present the concept of I -fuzzy topological polygroups and prove some properties. The concept of I -fuzzy topological polygroups is a generalization of the concept of I -fuzzy topological groups. By considering the relative fuzzy topology on fuzzy subpolygroups we prove some related properties.
Keywords: Polygroup, I-fuzzy topology, I-fuzzy quasi-coincident neighborhood system, I-fuzzy topological polygroups
DOI: 10.3233/JIFS-18833
Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 1671-1682, 2019
Authors: Türkmen, Muhammed Recai | Dündar, Erdinç
Article Type: Research Article
Abstract: In this study, we have investigated the concepts of lacunary summable, lacunary statistical convergence and lacunary statistically Cauchy sequence for double sequences in fuzzy normed spaces. Also, we have investigated some properties and relationships between these concepts.
Keywords: Double sequences, statistical convergence, fuzzy numbers, fuzzy normed spaces, lacunary sequences
DOI: 10.3233/JIFS-18841
Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 1683-1690, 2019
Authors: Duan, Huiming | Liu, Yongzhi | Wang, Di | He, Leiyuhang | Xiao, Xinping
Article Type: Research Article
Abstract: The modeling and prediction of short-term traffic flow can reflect the prediction results of the traffic state and traffic flow data. In this paper, first, we use a high-dimensional tensor to represent the multi-mode characteristics of traffic flow data, and we make use of the basic operations properties of tensors, such as Tucker decomposition, to study the methods for filling in data, such as ITRM. Additionally, we preprocess the lost traffic flow and abnormal data. At the same time, we study the short-term traffic flow based on the “week-day-time” multi-mode of the traffic flow data. Using the grey model (GM …(1, 1)) to predict the same period of the weekly mode, the scrolling grey model (SGM) of the same time period is predicted. For the time mode, a neural network time series of wavelet analysis is used to predict the traffic flow forecast during the same period. Then, the prediction results of the three different models are weighted by the grey correlation analysis method, and then, the coupling prediction model of the three models is obtained. In the end, according to the traffic flow data of the main road of Shaoshan road in Changsha, Hunan, China, we first preprocess the lost data by using the filling algorithm for the tensor data, and then, we make the traffic flow data complete, use the three tensor data modes of traffic flow, and analyze the results. The experimental results show that the coupling prediction model with the tensor model is much better than the single GM (1, 1) model, the SGM and the neural network prediction model. Show more
Keywords: High-dimensional tensor, multi-mode traffic flow data, short-term traffic flow forecasting, grey model
DOI: 10.3233/JIFS-18804
Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 1691-1703, 2019
Authors: Han, Yuan-Liang | Shi, Fu-Gui
Article Type: Research Article
Abstract: In this paper, the degree of which an L -subset is an L -convex fuzzy ideal is proposed and its some characterizations are given. Besides, an L -fuzzy convexity on a lattice is naturally proposed and its some properties are studied.
Keywords: L-convex fuzzy ideal, Implication operator, L-fuzzy ideal degree, L-fuzzy convexity
DOI: 10.3233/JIFS-18764
Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 1705-1714, 2019
Authors: Yu, Wangwang | Zhang, Hui | Li, Boquan
Article Type: Research Article
Abstract: In this paper, we present a priority degree method of hesitant fuzzy linguistic term sets (HFLTSs) based on a type of G function. First, we obtain several invalid examples by using Rodríguez et al. and Lee et al.’s method of HFLTSs. Considering these problems, second, after transforming HFLTS into the interval number and proposing a priority degree method of the interval number using the G function, we present a priority degree method of HFLTEs. Finally, we compare both Rodríguez et al.’s decision-making method and lee et al.’s decision-making method with our priority degree method. The result shows that …our priority degree method is more rational. Show more
Keywords: Hesitant fuzzy linguistic term set, Hesitant fuzzy set, Interval number, G function, Priority degree
DOI: 10.3233/JIFS-18773
Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 1715-1725, 2019
Authors: Thao, Nguyen-Trang
Article Type: Research Article
Abstract: Fuzzy time series modeling has recently become an interesting topic to study. Among fuzzy time series models, the Abbasov-Mamedova (AM) model has advantages over the others because it can forecast the value that is outside the min-max range of the original data. However, the performance of the AM model strongly depends on three parameters that are user-defined. In previous studies, the optimal parameters of the fuzzy time series models have been identified with a global optimization method. Surprisingly, optimizing the parameters of the Abbasov and Mamedova model has not been solved in spite of its advantages over the others. This …paper presents a new approach to improve the performance of AM model based on the evolutionary algorithm. Particularly, the objective function is calculated as the Mean absolute percentage error which will be minimized using the differential evolution (DE) algorithm. The experiments on Azerbaijan’s population, Vietnam’s GDP and rice production demonstrate the feasibility and applicability of the proposed methods. Show more
Keywords: fuzzy time series, differential evolution, optimization, forecast, MAPE
DOI: 10.3233/JIFS-18636
Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 1727-1741, 2019
Authors: Ma, Hongzhan | Chu, Xuening | Li, Yupeng
Article Type: Research Article
Abstract: Product redesign strategy can effectively shorten design lead time and reduce production cost of new variants development. Identification of function components is the basis of product redesign. In the existing methods to identify the function components, customer requirements are primarily considered while the failure knowledge, a critical information to improve product reliability, is often ignored. The objective of this research is to identify the to-be-improved components considering both customer requirements and product reliability. First, a two-stage fuzzy quality function deployment (QFD) is used to calculate the importance weight of each component considering customer requirements. Second, the fuzzy failure mode effects …and analysis (FMEA) is adopted to measure the failure risk of each component. Different from traditional FMEA, the failure causality relationships are analyzed in this work to provide a means of making use of failure information more effectively for constructing a directed failure causality relationship diagram. Fuzzy permanent function is developed to quantify the failure risk of each component. Then, a modification necessity index is introduced to model the degree of modification necessity for each component considering customer requirements and failure risk. Finally, the optimal set of function components that need to be modified is identified by 0-1 objective programming and constrained optimization. A case study for identification of the function components for the operation device of a crawler crane is implemented to demonstrate the effectiveness of the developed approach. Show more
Keywords: Identification of function component, fuzzy QFD, FMEA, fuzzy permanent function, 0-1 objective programming
DOI: 10.3233/JIFS-18614
Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 1743-1757, 2019
Authors: Ren, Liwei | Ban, Xiaojun | Ying, Hao
Article Type: Research Article
Abstract: Controlling a dynamic system to make its output identical to a user-desired reference trajectory given to the system’s input without any delay (i.e., perfect output tracking control) is an important and frequently encountered control requirement in industries (e.g., robotic control). When disturbances exist in a system, perfect output tracking control may be impossible to attain and alternatively asymptotical output tracking is sought. This paper presents an asymptotical output tracking control design method for a general class of discrete-time TS fuzzy systems with quadratic rule consequents, which offer better modeling capabilities than the linear rule consequents. The control problem is dealt …with by utilizing the feedback linearization method. To guarantee asymptotical output tracking performance in the presence of square disturbance signal, an auxiliary PI controller is added to attenuate the disturbance. The feedback linearization method is known in the literature to fail to work for certain systems because it can make the tracking controller’s output unbounded. To address this issue, we put forward a full block S-procedure condition to check whether such failure will occur for any given quadratic TS fuzzy system. Applying feedback linearization to the quadratic TS fuzzy systems is innovative relative to the literature that has exclusively dealt with the TS fuzzy systems with linear rule consequents only. Two numerical examples are provided to illustrate the effectiveness and utility of our theoretical results. Show more
Keywords: Discrete-time quadratic TS fuzzy systems, asymptotical output tracking, disturbance rejection, feedback linearization, full block S-procedure
DOI: 10.3233/JIFS-18454
Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 1759-1772, 2019
Authors: Zareapoor, Masoumeh | Shamsolmoali, Pourya | Yang, Jie
Article Type: Research Article
Abstract: Imaging techniques are the most rapidly growing area of computer vision, and the resolution has reached a new level. Super-resolution is a technique that enhances the resolution of images from the low-resolution input and help to accurately analyze and derive the data. Recently convolutional neural network are becoming mainstream in computer vision. Most existing CNN models based super-resolution either directly reconstruct the low-resolution input and then improve the resolution at the last layer, or another way is, to firstly enlarge the low-resolution input to high resolution (HR), then reconstruct the HR to obtain the desired output. These models encounter some …major flows; large computational resources and losing information. In this paper, we adopt gradual process for training the CNN, to propose an efficient super-resolution model. The gradual strategy helps network to progressively magnify and reconstruct the LR image in each step, and thereby possibly avoid of losing information (second problem). In addition, we optimize the number of layers, add the residual network and skip connection to the proposed network to ease the difficulty of training (first problem). The proposed model not only achieves a compatible performance with the existing prominent methods but also, efficiently reduce the computational expenses. Show more
Keywords: Super-resolution, deep network, skip connections, image processing
DOI: 10.3233/JIFS-18136
Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 1773-1783, 2019
Authors: Barzegar Kelishami, Hasan | Fariborzi Araghi, Mohammad Ali | Allahviranloo, Tofigh
Article Type: Research Article
Abstract: In this paper, by using the fuzzy CESTAC method and the CADNA library a procedure is proposed to control the step size for solving the fuzzy differential equation with fuzzy boundary conditions based on the finite differences method under generalized H-differentiability (gH-differentiability). An algorithm is presented to implement the discrete stochastic arithmetic for solving the given fuzzy boundary value problem on the C++ code via the CADNA library. Also, a theorem is proved to show the accuracy of results based on the concept of the common proximity of two fuzzy numbers. Finally, some examples are solved by using the proposed …algorithm to illustrate the effectiveness of applying the stochastic arithmetic (SA) in place of the floating-point arithmetic (FPA) to validate the results and find the optimal solution. Show more
Keywords: Finite differences method, Fuzzy boundary value problem (FBVP), Stochastic arithmetic, CESTAC method, CADNA Library
DOI: 10.3233/JIFS-181055
Citation: Journal of Intelligent & Fuzzy Systems, vol. 36, no. 2, pp. 1785-1796, 2019
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