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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: Akram, Muhammad | Muhammad, Ghulam | Allahviranloo, Tofigh | Hussain, Nawab
Article Type: Research Article
Abstract: The aim of this work is to solve the linear system of equations using LU decomposition method in bipolar fuzzy environment. We assume a special case when the coefficient matrix of the system is symmetric positive definite. We discuss this point in detail by giving some numerical examples. Moreover, we investigate m × n inconsistent bipolar fuzzy matrix equation and find the least square solution of the inconsistent bipolar fuzzy matrix using the generalized inverse matrix theory. The existence of the strong bipolar fuzzy least square solution of the inconsistent bipolar fuzzy matrix is discussed. In the end, a numerical …example is presented to illustrate our proposed method. Show more
Keywords: LU decomposition method, symmetric positive definite matrix, inconsistent bipolar fuzzy matrix equations, bipolar fuzzy least square solution
DOI: 10.3233/JIFS-201187
Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3329-3349, 2020
Authors: Liu, Peide | Ali, Zeeshan | Mahmood, Tahir
Article Type: Research Article
Abstract: The information measures (IMs) of complex fuzzy information are very useful tools in the areas of machine learning and decision making. In some multi-attribute group decision making (MAGDM) problems, the decision makers can make a decision mostly according to IMs such as similarity measures (SMs), distance measures (DIMs), entropy measures (EMs) and cross-entropy measures (C-EMs) in order to choose the best one. However, the relation between C-EMs and DIMs in the environment of complex fuzzy sets (CFSs) has not been developed and verified. In this manuscript, the notions of DIMs and C-EMs in the environment of CFSs are investigated and …the relation between DIMs and EMs in the environment of CFSs is also discussed. The complex fuzzy discrimination measures (CFDMs), the complex fuzzy cross-entropy measures (CFC-EMs), and the symmetry complex fuzzy cross-entropy measures (SCFC-EMs) are proposed. We also examined that the C-EMs satisfied all the conditions of DIMs, and finally proved that C-EMs including CFC-EMs were also a DIMs. In last, we used some practical examples to illustrate the validity and superiority of the proposed method by comparing with other existing methods. Show more
Keywords: Fuzzy sets, complex fuzzy sets, cross-entropy measures, distance measures
DOI: 10.3233/JIFS-191718
Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3351-3374, 2020
Authors: Javed, Shazia | Ahmad, Noor Atinah
Article Type: Research Article
Abstract: Despite its low computational cost, and steady state behavior, some well known drawbacks of the least means squares (LMS) algorithm are: slow rate of convergence and unstable behaviour for ill conditioned autocorrelation matrices of input signals. Several modified algorithms have been presented with better convergence speed, however most of these algorithms are expensive in terms of computational cost and time, and sometimes deviate from optimal Wiener solution that results in a biased solution of online estimation problem. In this paper, the inverse Cholesky factor of the input autocorrelation matrix is optimized to pre-whiten input signals and improve the robustness of …the LMS algorithm. Furthermore, in order to have an unbiased solution, mean squares deviation (MSD) is minimized by improving convergence in misalignment. This is done by regularizing step-size adaptively in each iteration that helps in developing a highly efficient optimal preconditioned regularized LMS (OPRLMS) algorithm with adaptive step-size. Comparison of OPRLMS algorithm with other LMS based algorithms is given for unknown system identification and noise cancelation from ECG signal, that results in preference of the proposed algorithm over the other variants of LMS algorithm. Show more
Keywords: Optimal Cholesky factor, regularization, variable step-size, preconditioning
DOI: 10.3233/JIFS-191728
Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3375-3385, 2020
Authors: Singh, Ravindra | Khatoon, Shahida | Chaudhary, Himanshu | Pandey, Ashish
Article Type: Research Article
Abstract: Gimballed sensor system is a precision electromechanical assembly designed primarily to isolate the optical system from disturbances induced by the operating environment. This paper gives an insight to the design and development of gimballed sensor system for Line of Sight (LOS) stabilization of an electro-optical tracking and pointing system. Initially kinematic equations are formulated to establish a relationship between LOS angle and applied torque. This relationship is used to obtain nested loop transfer function model. First, the parameters of the proposed assembly are determined through experimentation & rigorous analysis process, and then conventional control design methodology is adopted for controller …configuration design for current and rate loop. The frequency response analysis of the designed LOS stabilization model with conventional controller is done in simulation and the obtained results are verified experimentally against angular disturbances in real time scenario. Further, Based on prior qualitative information about system dynamics and linguistic performance criteria, a fuzzy logic controller of mamdani type with simplified rule set is developed with an objective to improve the disturbance attenuation and command response performance of designed system irrespective of angular disturbances due to platform vibrations, model uncertainties and mass imbalance in gimbal assembly. Both the Fuzzy logic simulation model and conventional model are tested based on critical performance characteristics such as stability of the loop, responsiveness of the loop and insensitivity to disturbances. Finally, the comparative analysis suggests that, although both the control configuration satisfies the required accuracy, Fuzzy logic control certainly improvised the performance of the gimballed sensor system and hence can be very effective for more precise pointing, tracking and stabilization application. Show more
Keywords: Proportional integral (PI) compensation, fuzzy logic control, jitter attenuation, gimballed electro-optical system, tracking and pointing
DOI: 10.3233/JIFS-191735
Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3387-3399, 2020
Authors: Peng, Yong | Zhang, Leijie | Kong, Wanzeng | Qin, Feiwei | Zhang, Jianhai
Article Type: Research Article
Abstract: Subspace learning aims to obtain the corresponding low-dimensional representation of high dimensional data in order to facilitate the subsequent data storage and processing. Graph-based subspace learning is a kind of effective subspace learning methods by modeling the data manifold with a graph, which can be included in the general spectral regression (SR) framework. By using the least square regression form as objective function, spectral regression mathematically avoids performing eign-decomposition on dense matrices and has excellent flexibility. Recently, spectral regression has obtained promising performance in diverse applications; however, it did not take the underlying classes/tasks correlation patterns of data into consideration. …In this paper, we propose to improve the performance of spectral regression by exploring the correlation among classes with low-rank modeling. The newly formulated low-rank spectral regression (LRSR) model is achieved by decomposing the projection matrix in SR by two factor matrices which were respectively regularized. The LRSR objective function can be handled by the alternating direction optimization framework. Besides some analysis on the differences between LRSR and existing related models, we conduct extensive experiments by comparing LRSR with its full rank counterpart on benchmark data sets and the results demonstrate its superiority. Show more
Keywords: Low-rankness, spectral regression, matrix factorization, subspace learning, classification
DOI: 10.3233/JIFS-191752
Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3401-3412, 2020
Authors: Tan, Ruipu | Zhang, Wende
Article Type: Research Article
Abstract: Trapezoidal fuzzy neutrosophic decision making plays an important role in decision-making processes with uncertain, indeterminate, and inconsistent information. In this paper, we propose a new multi-attribute decision-making method based on decision-making trial and evaluation laboratory (DEMATEL), fuzzy distance, and linear assignment method (LAM), and we express evaluation values as the trapezoidal fuzzy neutrosophic numbers (TrFNNs). First, attribute weights are obtained using the DEMATEL method and the new fuzzy distance of TrFNNs based on graded mean integration representation is defined. Then, alternatives are ranked using the LAM in operations research. In addition, we make two comparative analyses in the end to …illustrate the feasibility and rationality of our method. Finally, an illustrative example about typhoon disaster assessment is presented to show the advantages of the proposed method. Show more
Keywords: Multiple attribute decision making, trapezoidal fuzzy neutrosophic set, DEMATEL, fuzzy distance, LAM, typhoon disaster evaluation
DOI: 10.3233/JIFS-191758
Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3413-3439, 2020
Authors: Huang, Li | Wu, Jian-Zhang | Beliakov, Gleb
Article Type: Research Article
Abstract: MCCPI (Multiple Criteria Correlation Preference Information) is a kind of 2 dimensional decision preference information obtained by pairwise comparison on the importance and interaction of decision criteria. In this paper, we introduce the nonadditivity index to replace the Shapley simultaneous interaction index and construct an undated MCCPI based decision scheme. We firstly propose a diagram to help decision maker obtain the nonadditivity index type MCCPI, then establish transform equations to normalize them into desired capacity and finally adopt a random generation MCCPI based comprehensive decision aid algorithm to explore the dominance relationships and creditable ranking orders of all decision alternatives. …An illustrative example is also given to demonstrate the feasibility and effectiveness of the proposed decision scheme. It’s shown that based on some good properties of nonadditivity index in practice, the updated MCCPI model can deal with the internal interaction among decision criteria with relatively less model construction and calculation effort. Show more
Keywords: Multiple criteria decision analysis, capacity, fuzzy measure, nonadditivity index, interaction index
DOI: 10.3233/JIFS-191789
Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3441-3452, 2020
Authors: Kamaruzaman, Nurzahara Atika | Omar, Mohd
Article Type: Research Article
Abstract: In practice, the demand for a fresh product depends on how fresh it is, therefore, it is important to take expiration date into consideration as it is a key to determine the freshness level of any perishable items. Furthermore, based on marketing and economic theory, selling price plays a crucial role in influencing the demand. Also, a higher inventory level may enhance the profit as it encourages consumers to buy more. Since the demand for fresh product declines over time, markdown policy is offered after some time to increase the demand and profit while reducing the inventory. For this demand …function, it may be profitable to maintain a high stock level and the zero ending inventory is relaxed to non-zero ending inventory. Salvage value is incorporated into the deteriorating units. Using differential equations, we propose an economic order quantity model which demand dependent on freshness-expiration date, price and inventory level under markdown policy. We also demonstrate the relationship between markdown time and the annual total profit. Numerical example and sensitivity analysis are used to illustrate the effectiveness of the model. Show more
Keywords: Inventory control, perishable items, expiration date, markdown policy, pricing strategy
DOI: 10.3233/JIFS-191794
Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3453-3461, 2020
Authors: Ji, Fujiao | Zhao, Zhongying | Zhou, Hui | Chi, Heng | Li, Chao
Article Type: Research Article
Abstract: Heterogeneous information networks are widely used to represent real world applications in forms of social networks, word co-occurrence networks, and communication networks, etc. However, It is difficult for traditional machine learning methods to analyze these networks effectively. Heterogeneous information network embedding aims to convert the network into low dimensional vectors, which facilitates the following tasks. Thus it is receiving tremendous attention from the research community due to its effectiveness and efficiency. Although numerous methods have been present and applied successfully, there are few works to make a comparative study on heterogeneous information network embedding, which is very important for developers …and researchers to select an appropriate method. To address the above problem, we make a comparative study on the heterogeneous information network embeddings. Specifically, we first give the problem definition of heterogeneous information network embedding. Then the heterogeneous information networks are classified into four categories from the perspective of network type. The state-of-the-art methods for each category are also compared and reviewed. Finally, we make a conclusion and suggest some potential future research directions. Show more
Keywords: heterogeneous information network, network embedding, network representation learning, social network analysis
DOI: 10.3233/JIFS-191796
Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3463-3473, 2020
Authors: Shahsavari-Pour, Nasser | Mohammadi-Andargoli, Hamed | Bahram-Pour, Najmeh
Article Type: Research Article
Abstract: The purpose of this paper is to introduce a new meta-heuristic algorithm and apply this for solving a multi-objective flexible job-shop scheduling problem. The name of this algorithm is Cosmogony (CA). This algorithm has inspired by the ecosystem process of creatures and their environment. For a better understanding, we make an effort to apply the concepts of the meta-heuristic algorithms up to a possible extent. This algorithm identifies local optimal points during the self-search process of problem-solving. Initial creatures have been generated randomly in a certain number. This algorithm incorporates many features of the other algorithms in itself. So that …to prove the ability and efficiency of CA, a flexible job-shop scheduling problem has surveyed. This problem is in a Non-resumable situation with maintenance activity constraints in a two-time fixed and non-fixed state. The algorithm performance is evaluated by numerical experiments. The result has shown the proposed approach is more efficient and appropriate than the other methods. It also has high power in the searching process in the feasible region of the multi-objective flexible job-shop scheduling problem and high converge power. Show more
Keywords: Cosmogony algorithm, meta-heuristic algorithms, flexible job shop scheduling problem, multi-objective optimization
DOI: 10.3233/JIFS-191839
Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3475-3501, 2020
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