Frequency: Quarterly E- ISSN: 2277-2316 P- ISSN: Awaited Abstracted/ Indexed in: Ulrich's International Periodical Directory, Google Scholar, SCIRUS, Genamics JournalSeek, EBSCO Information Services
Quarterly published "Inventi Impact: Fuzzy Systems" publishes high quality unpublished, as well as high impact pre-published research and reviews related to theory, design and application of fuzzy systems, soft computing systems, grey systems and extension theory systems from hardware to software. Its target audience includes research communities from academics as well as of industry.
Coloring of fuzzy graphs has many real-life applications in combinatorial optimization problems like traffic light system, exam scheduling, and register allocation. The coloring of total fuzzy graphs and its applications are well studied. This manuscript discusses the description of 2-quasitotal graph for fuzzy graphs. The proposed concept of 2-quasitotal fuzzy graph is explicated by several numerical examples.Moreover, some theorems related to the properties of 2-quasitotal fuzzy graphs are stated and proved. The results of these theorems are compared with the results obtained from total fuzzy graphs and 1-quasitotal fuzzy graphs. Furthermore, it defines 2-quasitotal coloring of fuzzy total graphs and which is justified....
In many real world data analysis tasks, it is expected that we can get much more useful knowledge by utilizing multiple\ndatabases stored in different organizations, such as cooperation groups, state organs, and allied countries. However, in many\nsuch organizations, they often hesitate to publish their databases because of privacy and security issues although they believe\nthe advantages of collaborative analysis. This paper proposes a novel collaborative framework for utilizing vertically partitioned\ncooccurrence matrices in fuzzy co-cluster structure estimation, in which cooccurrence information among objects and items is\nseparately stored in several sites. In order to utilize such distributed data sets without fear of information leaks, a privacy preserving\nprocedure is introduced to fuzzy clustering for categorical multivariate data (FCCM).Withholding each element of cooccurrence\nmatrices, only object memberships are shared by multiple sites and their (implicit) joint co-cluster structures are revealed through\nan iterative clustering process. Several experimental results demonstrate that collaborative analysis can contribute to revealing\nglobal intrinsic co-cluster structures of separate matrices rather than individual site-wise analysis. The novel framework makes it\npossible for many private and public organizations to share common data structural knowledge without fear of information leaks....
Relational fuzzy clustering has been developed for extracting intrinsic cluster structures of relational data and was extended to\r\na linear fuzzy clustering model based on Fuzzy c-Medoids (FCMdd) concept, in which Fuzzy c-Means-(FCM-) like iterative\r\nalgorithm was performed by defining linear cluster prototypes using two representative medoids for each line prototype. In this\r\npaper, the FCMdd-type linear clustering model is further modified in order to handle incomplete data including missing values,\r\nand the applicability of several imputation methods is compared. In several numerical experiments, it is demonstrated that some\r\npre-imputation strategies contribute to properly selecting representative medoids of each cluster....
This paper represents the clinical decision support system for video head impulse test (vHIT) based on fuzzy inference system. It\nexamines the eye and head movement recorded by the eye movement tracking device, calculates the vestibulo-ocular reflex (VOR)\ngain, and applies fuzzy inference system to output the normality and artifact index of the test result. The position VOR gain and the\nproportion of covert and overt catch-up saccades (CUS) within the dataset are used as the input of the inference system. In addition,\nthis system yields one more factor, the artifact index, which represents the current interference in the dataset. Data of fifteen\nvestibular neuritis patients and two of normal subjects were evaluated. The artifact index appears to be very high in the lesion\nside of vestibular neuritis (VN) patients, indicating highly theoretical contradictions, which are low gain but without CUS, or\nnormal gain with the appearance of CUS. Both intact side and normal subject show high normality and low artifact index, even\nthough the intact side has slightly lower normality and higher artifact index. In conclusion, this is a robust system, which is the\nfirst one that takes gain and CUS into account, to output not only the normality of the vHIT dataset, but also the artifacts....
We propose a new method for ordering bipolar fuzzy numbers. In this method, for comparison of bipolar LR fuzzy numbers, we\nuse an extension of Kerre�s method being used in ordering of unipolar fuzzy numbers. We give a direct formula to compare two\nbipolar triangular fuzzy numbers in ...
This paper investigates single-period inventory management problems with uncertain market demand, where the exact possibility distribution of demand is unavailable. In this condition, it is important to order a reliable quantity which can immunize against distribution uncertainty. To model this type of single-period inventory management problem, this paper characterizes the uncertain demand by generalized interval-valued possibility distributions. We present a novel concept about an uncertain distribution set to describe distribution perturbation characterization. First, we introduce a lambda selection of the interval-valued fuzzy variable, and the uncertain distribution set is a collection of all generalized possibility distributions of lambda selection variables. According to the uncertain distribution set, a new distributionally robust fuzzy optimization method is developed for single-period inventory management problems. Under mild assumptions, the robust counterpart of the proposed fuzzy singleperiod inventory management model is formulated, which is an optimization program with certain linear objectives and infinitely many integral constraints. We discuss the computational issue of integral constraints and reformulate equivalently the robust counterpart as three deterministic inventory submodels under generalized interval-valued trapezoidal possibility distributions. According to the characteristics of three submodels, a domain decomposition method is designed to find the robust optimal solution that can immunize against uncertainty in our single-period inventory management problem. Finally, some computational results demonstrate the efficiency of the proposed distributionally robust fuzzy optimization method....
The aim of this paper is to develop an effective method for solving bimatrix games with payoffs of intuitionistic fuzzy value. Firstly,\nbimatrix game model with intuitionistic fuzzy payoffs (IFPBiG) was put forward. Secondly, two kinds of nonlinear programming\nalgorithms were discussed with theNash equilibrium of IFPBiG. Thirdly,Nash equilibrium of the algorithm was proved by the fixed\npoint theory and the algorithm was simplified by linear programming methods. Finally, an example was solved through Matlab; it\nshowed the validity, applicability, and superiority...
One of the most important engineering problems, with numerous uses in the applied sciences, is the synchronization of chaos dynamical systems. This paper introduces a dynamic-free T-S fuzzy sliding mode control (TSFSMC) method for synchronizing the different chaotic fractional-order (FO) systems, when there is input saturation. Using a new definition of fractional calculus and the fractional version of the Lyapunov stability theorem and linear matrix inequality concept, a Takagi–Sugeno fuzzy sliding mode controller is driven to suppress and synchronize the undesired behavior of the FO chaotic systems without any unpleasant chattering phenomenon. Finally, an example of synchronization of complex power grid systems is provided to illustrate the theoretical result of the paper in real-world applications....
This study develops the water resources management model for conjunctive use of surface and subsurface water using a fuzzy\r\ninference system (FIS). The study applies the FIS to allocate the demands of surface and subsurface water. Subsequently, water\r\nallocations in the surface water system are simulated by using linear programming techniques, and the responses of subsurface\r\nwater system with respect to pumping are forecasted by using artificial neural networks. The operating rule for the water systems is\r\nthat themore abundant water system supplies more water. By using the fuzzy rule, the FIS conjunctive usemodel easily incorporates\r\nexpert knowledge and operational polices into water resources management.Theresult indicates that the FISmodel ismore effective\r\nand efficient when compared with the decoupled conjunctive use and simulation-optimizationmodels. Furthermore, the FIS model\r\nis an alternative way to obtain the conjunctive use policies between surface and subsurface water....
As companies operate in a competitive environment, where the struggle for survival on\nthe market is rather tough, the top management face new challenges to identify methods, and even\ntechniques, which allows it to select from the market those assets that provide an optimal ratio\nbetween the acquisition cost and the economic performance. In this context, a fuzzy logic managerial\ndecision tool for the assets acquisition is proposed with the paper. The algorithm has three main\ncomponents: the matrix of the membership degree of the existing bids to asset selection criteria,\nusing fuzzy triangular numbers; the vector of the global membership degree of the bids to the\nselection criteria and the maximum of the global membership degree as an inference operator for\nestablishing the validated bids by the algorithm. Two scenarios of asset acquisition were tested.\nAfter simulations, it was determined that the proposed fuzzy logic managerial decision tool\ncombines, with very good results, the acquisition cost of the assets with their economic performance....
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