Journal of Intelligent & Fuzzy Systems - Volume 34, issue 4

Authors: Vu, Ho | Lupulescu, Vasile | Van Hoa, Ngo

Article Type: Research Article

Abstract: In this paper the interval-valued delay fractional differential equations (IDFDEs) under the Caputo generalized Hukuhara differentiability are introduced. By establishing some necessary comparison results and using the monotone iterative technique combined with the method of upper and lower solutions, we investigate the existence of extremal solutions for interval-valued delay fractional differential equations. Several examples are presented to illustrate the concepts and results.

Keywords: Interval-valued functions, interval-valued fractional integral and derivatives, interval-valued delay fractional differential equation

DOI: 10.3233/JIFS-171070

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 4, pp. 2177-2195, 2018

Authors: Chen, Keji | Yang, Bo | Pei, Xiaofei | Guo, Xuexun

Article Type: Research Article

Abstract: This paper proposes an intelligent safe driving system (ISDS) for autonomous vehicles. The system utilizes a hierarchical control framework, where the high-level and low-level controllers are responsible for the decision making and motion control respectively. In the high-level controller, two finite-state machines (FSMs) are applied. One of the FSMs identifies the relative positions of the surrounding vehicles to the subject vehicle, and the other one chooses the proper driving behaviors intelligently to deal with the complex situations. In the low-level controller, the double-model-predictive-control structure is designed for the lateral motion control, and the PID feedback control with the inverse model …is employed for the longitudinal motion control. The proposed control system is tested in the Simulink/CarSim simulation environment. The results show that the controlled subject vehicle is able to avoid the collision with the surrounding vehicles and acquire the desired speed autonomously. The motion stability is also guaranteed during the accelerating/decelerating and lane changing. Show more

Keywords: Autonomous vehicle, intelligent driving, motion control, finite-state machine, model predictive control

DOI: 10.3233/JIFS-171186

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 4, pp. 2197-2212, 2018

Authors: You, Cuilian | Zhang, Ruili

Article Type: Research Article

Abstract: The theory of fuzzy differential equation has been studied by many researchers. In this paper, the fuzzy differential equation is a different type of differential equations, its fuzziness is not only in the initial conditions and coefficients, but also in the driven process. This paper presents some methods to solve linear complex fuzzy differential equations, and proves some existence and uniqueness theorems of solution for complex fuzzy differential equations based on Lipschitz condition and linear growth condition.

Keywords: Fuzzy variable, fuzzy integral, fuzzy differential, fuzzy differential equation, existence and uniqueness theorem

DOI: 10.3233/JIFS-171231

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 4, pp. 2213-2222, 2018

Authors: Xin, Xiu | Lian, Huan

Article Type: Research Article

Abstract: This paper attempts to study circuit axioms and connectedness of M -fuzzifying matroids. Based on the results of circuit-maps given by Yao and Shi, remarks concerning circuit-maps and connectedness of fuzzifying matroids are shown, and thus the useful notion of an M -fuzzifying matroid induced by an M -fuzzy family of circuits is introduced. Circuit axioms of an M -fuzzifying matroid induced by an M -fuzzy family of circuits are established, which are the generalizations of circuit axioms for a matroid in a normal way. Connectedness of an M -fuzzifying matroid induced by an M -fuzzy family of circuits is …then defined by its M -fuzzy family of circuits, a fuzzy analog of connectedness of a matroid. Additionally, two kinds of M -fuzzifying matroids are compared. Show more

Keywords: M-fuzzifying matroid, M-fuzzy family of circuits, connectedness

DOI: 10.3233/JIFS-171239

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 4, pp. 2223-2234, 2018

Authors: Hu, Guolin | Liu, Xiaodong | Wang, Likui | Li, Hongxing

Article Type: Research Article

Abstract: This paper addresses the problem of designing the controller for a class of nonlinear systems by using the Takagi-Sugeno fuzzy models. Based on generalised fuzzy Lyapunov function and homogeneous polynomial techniques, a new method is proposed to locally stabilize the Takagi-Sugeno fuzzy system. The new method overcomes the drawbacks of the previous results and enlarges the design space. Finally, two examples are given to illustrate the effectiveness of the approach.

Keywords: Takagi-Sugeno fuzzy model, linear matrix inequalities (LMIs), generalised fuzzy Lyapunov function, homogeneous polynomial techniques, homogeneous polynomially non-quadratic control law (HPNQCL)

DOI: 10.3233/JIFS-171266

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 4, pp. 2235-2246, 2018

Authors: Del Moral, Maria José | Tapia, Juan Miguel | Chiclana, Francisco | Al-Hmouz, A. | Herrera-Viedma, Enrique

Article Type: Research Article

Abstract: Soft consensus is a relevant topic in group decision making problems. Soft consensus measures are utilized to reflect the different agreement degrees between the experts leading the consensus reaching process. This may determine the final decision and the time needed to reach it. The concept of coincidence has led to two main approaches to calculating the soft consensus measures, namely, concordance among expert preferences and concordance among individual solutions. In the first approach the coincidence is obtained by evaluating the similarity among the expert preferences, while in the second one the concordance is derived from the measurement of the similarity …among the solutions proposed by these experts. This paper performs a comparative study of consensus approaches based on both coincidence approaches. We obtain significant differences between both approaches by comparing several distance functions for measuring expert preferences and a consensus measure over the set of alternatives for measuring the solutions provided by experts. To do so, we use the nonparametric Wilcoxon signed-ranks test. Finally, these outcomes are analyzed using Friedman mean ranks in order to obtain a quantitative classification of the considered measurements according to the convergence criterion considered in the consensus reaching process. Show more

Keywords: Group decision making, fuzzy preference relations, consensus

DOI: 10.3233/JIFS-171282

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 4, pp. 2247-2259, 2018

Authors: Avatefipour, Omid | Nafisian, Amir

Article Type: Research Article

Abstract: In this paper, a new combined method based on Clonal Selection Algorithm (CSA) and Artificial Neural Network (ANN) machine learning algorithm has been presented for the Short Term Load Forecasting (STLF) application. Compared to the other existing evolutionary based algorithm in this area, the proposed technique exploits both the ANN’s learning properties for solving the nonlinear and complex problems and CSA population-based algorithm for global and local search. Moreover, in order to select the most informative and irredundant features from the input feature set, a new feature selection method is introduced by using fuzzy set theory and fuzzy clustering techniques. …In regards to overall performance enhancement of CSA algorithm, three sub-modifications are proposed to expand the search capability of CSA and avoid premature convergence. Finally, in order to demonstrate the effectiveness and superiority of proposed method compared to other existing methods, the real dataset of daily peak value of electric load consumption is provided and simulation results reveal the improved forecasting accuracy of the proposed method over the other popular techniques in the STLF application. Show more

Keywords: Short Term Load Forecasting (STLF), optimization techniques, Clonal Selection Algorithm (CSA), Artificial Neural Network (ANN), fuzzy-based feature selection

DOI: 10.3233/JIFS-171292

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 4, pp. 2261-2272, 2018

Authors: Yuksel, Mehmet Emin | Basturk, Nurcan Sarikaya | Badem, Hasan | Caliskan, Abdullah | Basturk, Alper

Article Type: Research Article

Abstract: The high resolution hyperspectral remote sensing data collected from urban and landscape areas have been extensively studied over the past decades. Recent applications pose an emerging need of analyzing the land cover types based on high resolution hyperspectral remote sensing data originating from remote sensory devices. Toward this goal, we propose a deep neural network (DNN) classifier in this paper. The DNN is constructed by combining a stacked autoencoder with desired numbers of autoencoders and a softmax classifier. Our experimental results based on the hyperspectral remote sensing data demonstrate that the presented DNN classifier can accurately distinguish different land covers …including the mixed deciduous broadleaf natural forest and different land covers such as agriculture, roads, buildings, etc. We test the proposed method by using three different benchmark data sets. The proposed method showcases the huge potential of deep neural networks for hyperspectral data analysis. Show more

Keywords: Hyperspectral remote sensing, deep learning, deep neural network, softmax classifier, stacked autoencoder

DOI: 10.3233/JIFS-171307

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 4, pp. 2273-2285, 2018

Authors: Wang, Jian | Guo, Jiansheng | Zheng, Mingfa | Wang, Zutong | Li, Zhengxin

Article Type: Research Article

Abstract: Orienteering problem is gradually prevalent in the recent decade, but studies considering both uncertainty and multiobjective are still at low pace. In this paper, the uncertain multiobjective orienteering problem (UMOOP) is modeled based on uncertainty theory, in which objective functions contain uncertain vectors. Firstly, the Kataoka criterion and the ‘worst-case-oriented’ philosophy are adopted, and the UMOOP is transformed into a deterministic problem α -UMOOP with a series of chance constrains. On this basis, concept of efficient solution with belief degree is defined. Secondly, two assumptions are introduced to deal with the uncertain vectors, and a deterministic equivalent form D-UMOOP …can be obtained. It is theoretically proved that efficient solutions to D-UMOOP are equivalent to the efficient solutions with belief degrees to the UMOOP. Additionally, since the D-UMOOP is NP-hard, a discrete multiobjective bat algorithm is designed with the discrete updating process and the multiobjective local search strategy. Finally, an application is presented to the unmanned aerial vehicle (UAV) reconnaissance mission planning problem, which is modeled as uncertain biobjective orienteering problems, and tackled by the theoretical result and algorithm in this paper. The studies provide a new way for multiple attribute and uncertain decision-making problems. Show more

Keywords: Uncertainty theory, uncertainty multiobjective orienteering problem, efficient solutions with belief degrees, discrete multiobjective bat algorithm, UAV reconnaissance mission planning

DOI: 10.3233/JIFS-171331

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 4, pp. 2287-2299, 2018

Authors: Xiao, Xinping | Jiang, Meng | Wen, Jianghui | Wu, Chaozhong

Article Type: Research Article

Abstract: Based on the conditional heteroskedasticity of following vehicle acceleration fluctuation in car-following behavior, this paper combines the idea of driving force, Intelligent Driving Model (IDM) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH model) to establish a novel car-following model. First, the concept of safety driving force and efficiency driving force are recommended, and both of them are defined by the idea of IDM, and the dynamic balance of them are the reason for acceleration fluctuation. Then, according to the heteroskedasticity of acceleration sequence, the classic GARCH model is introduced to establish the relationship among the variance of acceleration fluctuation items, driving …force items and fluctuating memory items. On this basis, a novel car-following model is established, and the relational properties are studied. Finally, an example is used to verify our model, the results show that the novel car-following model is more accurate than IDM model, and the forward prediction result is close to the actual acceleration change value, which can predict the occurrence of dangerous driving behavior. Show more

Keywords: Conditional heteroskedasticity, IDM model, GARCH model, driving force

DOI: 10.3233/JIFS-171351

Citation: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 4, pp. 2301-2311, 2018