Qais A. Khasawneh^1,3, Mohammad Abdel Kareem Jaradat^1,2, Mohammad Al-Shabi⁴, Hala Khalaf¹

Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 443-457, 2018, DOI:10.31209/2018.100000008

Abstract This work presents a new micro-positioning system that is implemented in an inchworm robot to move into desired locations. The system consists of four-bar mechanism; one link is fixed, and each one of the remaining links carries a piezoelectric actuator (PZT). PZTs are specifically chosen since they provide fast response and small displacements; up to ±30 µm for ±100 Volts. The system’s mathematical model is derived and is numerically simulated by MATLAB. Three fuzzy PI controllers, which are tuned automatically by genetic algorithm, are designed to control the system. Results indicate an error of less than 1% although disturbances present. More >

Kazim Sari

Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 405-412, 2018, DOI:10.1080/10798587.2017.1352258

Abstract Nowadays, there has been a great interest for business enterprises to work together or collaborate in the supply chain. It is thus possible for them to gain a competitive advantage in the marketplace. However, determining the right collaboration strategy is not an easy task. Namely, there are several factors that need to be considered at the same time. In this regard, an expert system based on fuzzy rules is proposed to choose an appropriate collaboration strategy for a given supply chain. To this end, firstly, the factors that are significant for supply chain collaboration are extracted via an extensive review… More >

Mohammed Algabri^a,c, Mohamed Abdelkader Bencherif^c, Mansour Alsulaiman^b,c, Ghulam Muhammad^b, Mohamed Amine Mekhtiche^c

Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 267-274, 2018, DOI:10.1080/10798587.2017.1278961

Abstract A method that uses fuzzy logic to classify two simple speech features for the automatic classification of voiced and unvoiced phonemes is proposed. In addition, two variants, in which soft computing techniques are used to enhance the performance of fuzzy logic by tuning the parameters of the membership functions, are also presented. The three methods, manually constructed fuzzy logic (VUFL), fuzzy logic optimized with genetic algorithm (VUFL-GA), and fuzzy logic with optimized particle swarm optimization (VUFL-PSO), are implemented and then evaluated using the TIMIT speech corpus. Performance is evaluated using the TIMIT database in both clean and noisy environments. Four… More >

Somayeh Ezadi^a, Tofigh Allahviranloo^b

Intelligent Automation & Soft Computing, Vol.24, No.1, pp. 217-221, 2018, DOI:10.1080/10798587.2017.1367146

Abstract Many practical applications, under the definitive evolutionary state of the nature, the consequences of the decisions, mental states of a decision maker are required. Thus, the need is for a new concept in the analysis of decision-making. Zadeh has introduced this concept as the Z-number. Because the concept is relatively new, Z-number in fuzzy sets, hence, its basic theoretical aspects are yet undetermined. This paper presents a method for ranking Z-numbers. Hence, we propose a new method for ranking fuzzy numbers based on that of hyperbolic tangent function and convex combination. Then, using the same technique we propose a method… More >

R. A. Aliev^a,b

Intelligent Automation & Soft Computing, Vol.24, No.1, pp. 211-216, 2018, DOI:10.1080/10798587.2017.1330311

Abstract Commonsense reasoning plays a pivotal role in the development of intelligent systems for decisionmaking, system analysis, control and other applications. As Prof. L. Zadeh mentions a kernel of the theory of commonsense is the concept of usuality. Zadeh suggested main principles of the theory of usuality, unfortunately up to present day; a fundamental and systemic approach to reasoning with usual knowledge is not developed.
In this study, we develop a new approach to calculus of usual numbers (U-numbers). We consider a U-number as a Z-number, where the second component is “usually”. Validity of the suggested approach is verified by examples. More >

R. A. Aliev^a,b, Vladik Kreinovich^c

Intelligent Automation & Soft Computing, Vol.24, No.1, pp. 205-210, 2018, DOI:10.1080/10798587.2017.1330310

Abstract Traditional [0; 1] based fuzzy sets were originally invented to describe expert knowledge expressed in terms of imprecise “fuzzy” words from the natural language. To make this description more adequate, several generalizations of the traditional [0; 1] based fuzzy sets have been proposed, among them type- 2 fuzzy sets and Z-numbers. The main objective of this paper is to study the relation between these two generalizations. As a result of this study, we show that if we apply data processing to Z-numbers, then we get type-2 sets of special type —that we call monotonic. We also prove that every monotonic… More >

Lala M. Zeinalova^a, O. H. Huseynov^b, P. Sharghi^c

Intelligent Automation & Soft Computing, Vol.24, No.1, pp. 187-192, 2018, DOI:10.1080/10798587.2017.1327551

Abstract Regression analysis is widely used for modeling of real-world processes in various fields. It should be noted that information relevant to real-world processes is characterized by imprecision and partial reliability. This involves combination of fuzzy and probabilistic uncertainties. Prof.. L. Zadeh introduced the concept of a Z-number as a formal construct for dealing with such information. The present stateof-the-art of regression analysis under Z-number valued information is very scarce. In this paper we consider a Z-number valued multiple regression analysis and its application to a real-world decisionmaking problem. The obtained results show applicability of the proposed approach. More >

Mark J. Wierman

Intelligent Automation & Soft Computing, Vol.24, No.1, pp. 179-186, 2018, DOI:10.1080/10798587.2017.1327160

Abstract The theory of Zets is presented and the standard techniques of set theory allows for the development of a rich algebra of Zets. It shows that Zets and fuzzy sets are essentially interchangeable. However, the fundamental manipulations, techniques, and definitions of Zets are simple and more amenable to analyze. For example, the extension principle is easy to define. More >

Gunay Sadikoglu

Intelligent Automation & Soft Computing, Vol.24, No.1, pp. 173-178, 2018, DOI:10.1080/10798587.2017.1327159

Abstract Consumer behaviour has always been of a great interest in marketing research. The consumer buying behaviour has become an integral part of strategic market planning and includes mental, emotional and physical activities. The consumer behaviour and decision-making process are usually subject to uncertainties related to influences of socio-cultural, psychological and personal factors. In this paper, the Z-number concept is applied for handling uncertainties in analysing the consumer buying behaviour. More >

Wen Jiang, Chunhe Xie, Boya Wei, Yongchuan Tang

Intelligent Automation & Soft Computing, Vol.24, No.1, pp. 165-172, 2018, DOI:10.1080/10798587.2017.1327158

Abstract The main objective of this paper is to propose a new method for failure mode and effects analysis (FMEA) based on Z-numbers. In the proposed method, firstly, Z-numbers are used to perform the valuations (Z-valuation) of the risk factors like occurrence (O), severity (S) and detection (D). Secondly, the Z-valuations of the risk factors are integrated by fuzzy weighted mean method. A new risk priority number named as ZRPN is calculated to prioritize failure modes based on a modified method of ranking fuzzy numbers. Finally, a case study for the rotor blades of an aircraft turbine is performed to demonstrate… More >