International Journal of Fuzzy Systems and Advanced Applications

ISSN: 2313-0512
Volume 5, 2018

Notice: As of 2014 and for the forthcoming years, the publication frequency/periodicity of NAUN Journals is adapted to the 'continuously updated' model. What this means is that instead of being separated into issues, new papers will be added on a continuous basis, allowing a more regular flow and shorter publication times. The papers will appear in reverse order, therefore the most recent one will be on top.

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Volume 5, 2018

Title of the Paper: Collaborative Filtering Recommendation with Fuzzy-weighted User Similarity


Authors: Soojung Lee

Pages: 48-55

Abstract: Similarity computation plays a critical role in collaborative filtering-based recommender systems. As these systems recommend items based on user ratings, they involve several inherent problems such as data sparsity, cold-start, scalability, and user subjectivity. Much effort has been devoted to handle these problems and simultaneously enhance the performance of the system, but there are still much to be improved. This study focuses on user-based collaborative filtering systems and proposes a new similarity measure which not only considers user ratings for common items but also reflects the rating behavior of all the users on each common item onto similarity. Performance of the proposed measure is investigated extensively under very different ratings data conditions. The results state that it mostly outperforms state-of-the-art similarity measures, where the degree of improvement is significantly high when it incorporates Pearson correlation.

Title of the Paper: Electronic Throttle Control based on Fuzzy Self-adaptive Backstepping


Authors: Sheng Zhang, Xuejun Li, Haoyu Yu

Pages: 41-47

Abstract: Backstepping and other control methods based on model compensation have unique advantages in controlling nonlinear multivariable objects. However, the control performance will decrease dramatically when an inaccurate electronic throttle model is used. In order to reduce the difficulty of modeling without reducing the control performance, this technical note introduces a fuzzy self-adaptive backstepping control method. For electronic throttle control of inversion problem, using fuzzy self-adaptive method close to the throttle unknown parts, which can achieve system design requirements without precise model. The systerm simulation and physical experiments show that this method compared with backstepping can significantly reduce adjustment time of throttle, the steady-state error and other performance.

Title of the Paper: On Robust Stability of Singular Uncertain Takagi–sugeno Fuzzy Systems with Additive Time-Varying Delays


Authors: N. Chaibi, E. H. Tissir, Charqui

Pages: 35-40

Abstract: This paper considers the problem of delaydependent robust stability for uncertain fuzzy singular systems with additive time-varying delays. The purpose of the robust stability problem is to give conditions such that the uncertain fuzzy singular system is regular, impulse free, and stable for all admissible uncertainties. The results are expressed in terms of linear matrix inequalities (LMIs). Finally, two numerical examples are provided to illustrate the effectiveness of the proposed method.

Title of the Paper: Comparative Study Between Neural Hysteresis, Fuzzy PI, and Neural Switching Table for an IM DTC Control


Authors: Habib Benbouhenni, Zinelaabidine Boudjema

Pages: 23-34

Abstract: Direct torque control (DTC) has gained popularity for development of advanced AC machines control due to its simplicity and offers fast instantaneous torque and flux controls. This paper proposes five DTC schemes that will be compared with each other. These five schemes are classical DTC, DTC with fuzzy PI controller, DTC with neural hysteresis, DTC with artificial neural network (DTC-ANN) and neural hysteresis DTC with fuzzy PI speed controller. In other hand, this paper presents an improved switching strategy for reducing flux and torque ripples in DTC of induction machine (IM) drives. It can be shown that the new switching table DTC-ANN while the reduction of torque ripples, stator flux ripples and THD value of stator current. The validity of the proposed methods is confirmed by the simulation results.

Title of the Paper: Nonlinear Model Predictive Control with Combined System Model of Fuzzy Predictive and PID Controller for Managing the Blood Glucose Level in Type I Diabetes


Authors: M. Nalini, V. Balaji

Pages: 17-22

Abstract: Diabetes is likewise alluded as diabetes mellitus, is a gathering of metabolic maladies and causes high glucose level over a long stretch. Because of absence of insulin discharge sort 1 diabetes happen and accordingly has a low level of glucose. Insulin must be infused to control the level of blood glucose in the body. In the event that the level of insulin surpasses the farthest point it might bring about death. This paper displayed on controlling the blood glucose level utilizing a nonlinear model prescient control. The blood glucose level is observed for every single moment and anticipated for whenever interim, the insulin infusion level will be resolved if the model finds the framework is in irregular range. The nonlinear prescient control model is ordered into two models. The primary model is alluded as plant model. It decides the diabetic control and the second model is alluded as framework model. It decides the insulin-glucose administrative framework. To decide the prescient control, Fuzzy and PID control technique is utilized. These two control techniques are utilized to decide the prescient control level and they are reproduced and done in MATLAB/Simulink. The aftereffects of the proposed technique uncover the adequacy in changing the blood glucose level by infusing required insulin.

Title of the Paper: Characterization οf (α,β)-Lower Level Normal Subgroup Of Intuitionistic Multi-Anti Fuzzy Normal Subgroup


Authors: S. Balamurugan

Pages: 7-16

Abstract: In this paper, an attempt has been made to study new algebraic nature of (α,β)-lower level normal subgroup of intuitionistic multi-anti fuzzy normal subgroup and their properties are discussed. Several new results are presented.

Title of the Paper: A Fuzzy Scenario-Based Decision Aid for Risk Assessment in Business Process Outsourcing


Authors: Nazli Goker, Mehtap Dursun

Pages: 1-6

Abstract: Outsourcing ensures a great opportunity for firms to adopt flexible operation strategies and dynamic environment. Technological developments enable global companies to outsource more complex business processes due to the high cost of in-house operations. Business process outsourcing, which is considered to be a new big current in information systems services, is an improved version of information technologies outsourcing. This study introduces a scenario-based fuzzy cognitive map methodology (FCM) for assessing risk criteria in business process outsourcing. Since there are cause-and-effect relationships between pair of concepts, and the problem can be represented by a network, FCM technique becomes appropriate to evaluate the risk factors of business process outsourcing. The case study is conducted in a bank performing in Turkish banking sector. Several scenario analyses are employed to understand the influence of an increase or a decrease of the power of specific concept(s) on other concepts.