Li-Hong Juang^a, Ming-Ni Wu^b, Shin-An Lin^b

Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 249-256, 2018, DOI:10.1080/10798587.2016.1272777

Abstract Detecting human gender from complex background, illumination variations and objects under computer vision system is very difficult but important for an adaptive information service. In this paper, a preliminary design and some experimental results of gender recognition will be presented from the walking movement that utilizes the gait-energy image (GEI) with denoised energy image (DEI) pre-processing as a machine learning support vector machine (SVM) classifier to train and extract its characteristics. The results show that the proposed method can adopt some characteristic values and the accuracy can reach up to 100% gender recognition rate under combining the horizontal added vertical… More >

S. Bartkevicius^a, O. Fiodorova^b, A. Knys^c, A. Derviniene^d, G. Dervinis^c, V. Raudonis^c, A. Lipnickas^c, V. Baranauskas^c, K. Sarkauskas^c, L. Balasevicius^c

Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 241-248, 2018, DOI:10.1080/10798587.2016.1264695

Abstract The paper deals with supervised robot navigation in known environments. The navigation task is divided into two parts, where one part of the navigation is done by the supervisor system i.e. the system sets the vector marks on the salient edges of the virtual environment map and guides the robot to reach these marks. Mobile robots have to perform a specific task according to the given paths and solve the local obstacles avoidance individually. The salient point’s detection, vector mark estimation and optimal path calculation are done on the supervisor computer using colored Petri nets. The proposed approach was extended… More >

Mohamed Ben Gharsallah^a, Issam Ben Mhammed^b, Ezzedine Ben Braiek^a

Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 231-240, 2018, DOI:10.1080/10798587.2016.1262457

Abstract In radiography imaging, contrast, sharpness and noise there are three fundamental factors that determine the image quality. Removing noise while preserving and sharpening image contours is a complicated task particularly for images with low contrast like radiography. This paper proposes a new anisotropic diffusion method for radiography image enhancement. The proposed method is based on the integration of geometric parameters derived from the local pixel intensity distribution in a nonlinear diffusion formulation that can concurrently perform the smoothing and the sharpening operations. The main novelty of the proposed anisotropic diffusion model is the ability to combine in one process noise… More >

Qing-Hua He^a, Bin Yu^b, Xin Hong^a, Bo Lv^a, Tao Liu^b, Jian Ran^b, Yu-Tian Bi^a

Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 223-230, 2018, DOI:10.1080/10798587.2016.1261957

Abstract Lung abnormalities and respiratory diseases increase with the development of urban life. Lung sound analysis provides vital information of the present condition of the pulmonary. But lung sounds are easily interfered by noises in the transmission and record process, then it cannot be used for diagnosis of diseases. So the noised sound should be processed to reduce noises and to enhance the quality of signals received. On the basis of analyzing wavelet packet transform theory and the characteristics of traditional wavelet threshold de-noising method, we proposed a modified threshold selection method based on Particle Swarm Optimization (PSO) and support vector… 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 >

Somayeh Ezadi^a, Tofigh Allahviranloo^b

Intelligent Automation & Soft Computing, Vol.24, No.1, pp. 193-204, 2018, DOI:10.1080/10798587.2017.1328812

Abstract In this article, the researcher at first focuses on introducing a linear regression based on the Z-number. In this regression, observations are real, but the coefficients and results of observations are unknown and in the form of Z-rating. Therefore, to estimate this type of regression, we have three distinct ways depending on different conditions dominating the problem. The three methods are a combination of artificial neural networks and fuzzy generalized improvements of the technique. Moreover the method of calculating the weights of the Z-number neural network has been mentioned and the stability of neural network weights is considered. In some… 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 >