Journal of Intelligent & Fuzzy Systems - Volume 29, issue 6

Authors: Zhu, Yungang | Liu, Dayou | Li, Yong | Wang, Xinhua

Article Type: Research Article

Abstract: Active and dynamic fusion for fuzzy and uncertain data have key challenges such as high complexity and difficult to guarantee accuracy, etc. In order to resolve the challenging issues, in this article a selective and incremental data fusion approach based on probabilistic graphical model is proposed. General Bayesian networks are adopted to represent the relationship among the data and fusion result. It purposively selects the most informative and decision-relevant data for fusion based on Markov Blanket in probabilistic graphical model. Meanwhile we present a special incremental learning method for updating the fusion model to reflect the temporal changes of environment. …Theoretical analysis and experimental results all demonstrate the proposed method has higher accuracy and lower time complexity than existing state-of-the-art methods. Show more

Keywords: Data fusion, probabilistic graphical models, fuzzy and uncertain data, incremental learning

DOI: 10.3233/IFS-151939

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 6, pp. 2397-2403, 2015

Authors: Kong, Qing-Zhao | Wei, Zeng-Xin

Article Type: Research Article

Abstract: Many researchers have combined rough set theory and fuzzy set theory in order to easily approach problems of imprecision and uncertainty. Covering-based rough sets are one of the important generalizations of classical rough sets. Naturally, covering-based fuzzy rough sets can be studied as a combination of covering-based rough set theory and fuzzy set theory. It is clear that Pawlak’s rough set model and fuzzy rough set model are special cases of the covering-based fuzzy rough set model. This paper investigates the properties of covering-based fuzzy rough sets. In addition, operations of intersection, union and complement on covering-based fuzzy rough sets …are investigated. Finally, the corresponding algebraic properties are discussed in detail. Show more

Keywords: Fuzzy rough sets, monotone covering, approximation operator, algebraic property

DOI: 10.3233/IFS-151940

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 6, pp. 2405-2411, 2015

Authors: Khan, Changez | Anwar, Sajid | Bashir, Shariq | Rauf, Abdul | Amin, Adnan

Article Type: Research Article

Abstract: Suitable site selection for a specific purpose is a crucial activity, and of the greatest importance to a project manager. Several methods have been proposed by the research community for effective site selection, but all proposed methods incur high costs. This study explores the combination of a rough set theory approach (RSTA) with Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for suitable site selection for food distribution. This method provides a set of rules to determine different sites, which ultimately can help management develop strategies for suitable site selection. A set of rules for suitable site selection …are derived from information related to a practical case, Pakistan Red Crescent Society (PRCS), to demonstrate the prediction ability of RSTA. The results clearly demonstrate that the RSTA model can be a valuable tool for site identification. Rough set theory also assists management in making appropriate decisions based on their objectives while avoiding unnecessary costs. However, while RSTA provides rules to determine the best sites for food distribution, it does not pinpoint the best sites for food distribution. To be more precise and accurate, this work is extended to another multi-criteria decision-making technique solution: the TOPSIS method. By using this method, this study provides the best top priority site for food distribution of PRCS. Show more

Keywords: Site selection, rough set theory, TOPSIS, multi-criteria decision making (MCDM)

DOI: 10.3233/IFS-151941

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 6, pp. 2413-2419, 2015

Authors: Chai, Gan | Huang, Min-min | Han, Jing | Jiang, Min

Article Type: Research Article

Abstract: To deal with the problem in emergency plan matching of highway traffic that incident description is incomplete, incident properties are unclear, and plan matching is inaccurate, etc., a plan matching method is proposed based on fuzzy sets and rough sets. The property weight calculation method based on rough sets is used to reduce the dependency on prior knowledge; the structural similarity calculation is used to solve the problem of property missing and matching angle varying; the fuzzy set calculation method is adopted to solve the problem of fuzzy property similarity missing. The traffic emergency plan matching case for Changzhou section …of Shanghai-Nanjing highway demonstrates that the proposed method can improve the accuracy and reliability of highway traffic emergency matching, reflecting the advantages of rough sets and fuzzy sets in emergency plan matching. Show more

Keywords: Highways, plan matching, fuzzy sets, rough sets, similarity

DOI: 10.3233/IFS-151942

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 6, pp. 2421-2427, 2015

Authors: Song, Lijun | Jin, Shanying

Article Type: Research Article

Abstract: Aimed at overcoming subjectivity and improving the accuracy of traditional production performance evaluation methods for manufacturing enterprises, a new model of performance evaluation was proposed based on rough sets and a wavelet neural network (RS - WNN). Firstly, an evaluation index system considering innovation performance was constructed. Secondly, a theory of rough sets and fuzzy mathematics was utilized to preprocess and simplify the index system, and then, the input dimensionality of wavelet neural network was reduced. Finally, algorithms of stepwise checkout and iterative descending grads were employed to decide the parameters of WNN and to obtain the synthetic evaluation value …of production performance. A case study showed that the proposed model was effective and feasible in measuring production performance. Show more

Keywords: Production performance, rough set, wavelet neural network

DOI: 10.3233/IFS-151943

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 6, pp. 2429-2437, 2015

Authors: Ji, Feng | Cai, Xingguo | Zhang, Jihong

Article Type: Research Article

Abstract: Wind power point forecasting is the primary method to deal with its uncertainty. However, in many applications, the probabilistic interval of wind power is more useful than traditional point forecasting. Methods to determine the probabilistic interval of wind power point forecasting value is very essential to power system operations. Based on the bootstrap method, this paper proposed a wavelet transform combined with a neuro-fuzzy network model to estimate the prediction interval of wind power. In the model, to account for the ramp event of wind power series, a wavelet-based ramp event was used and the moving block bootstrap method, which …considers the dependence of wind power series, was used to construct sampling datasets. Then, the bootstrapped datasets were estimated by a neuro-fuzzy network inference system. A case study provided a 90% confidence level of prediction intervals, which was constructed to examine the effectiveness of the model. Show more

Keywords: Prediction interval, wind power, bootstrap, ramp event, neuro-fuzzy network

DOI: 10.3233/IFS-151944

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 6, pp. 2439-2445, 2015

Authors: Tao, Yong | Zheng, Jiaqi | Lin, Yuanchang | Wang, Tianmiao | Xiong, Hegen | He, Guotian | Xu, Dong

Article Type: Research Article

Abstract: This paper proposes a fuzzy PID control method for deburring industrial robots. The adaptive fuzzy PID controller relates to the trajectory and joint angular parameters of the end-effector on a robot. The PID controller parameters update online at each sampling time to guarantee trajectory accuracy of the end-effector. The simulation of the fuzzy PID control is provided based on the 6-DOF deburring industrial robot. Experimental results demonstrate the efficiency of the fuzzy PID control method.

Keywords: Fuzzy PID controller, robot trajectory, joint angular, deburring industrial robot

DOI: 10.3233/IFS-151945

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 6, pp. 2447-2455, 2015

Authors: Zhang, Lanyong | Cao, An | Du, Yixuan

Article Type: Research Article

Abstract: The generator is an important component of the power system and, as a prerequisite for the normal work of the generator; one of the preconditions of excitation of a system running well will directly affect the operation of the motor characteristics and heavily influence the normal operation of the power system. In the excitation system, the control portion of the excitation system is the key to whether a system can effectively resist all kinds of emergencies. Regarding the excitation system of a high temperature superconducting machine, this paper proposes the design of an excitation system control strategy. Combining fuzzy control …and conventional PID control strategy, the proposed composition has the advantages of an excitation control strategy, which can achieve a precise control purpose, and provides good adaptive ability and robustness. And on this basis, the proposed composition seeks to combine variable universe fuzzy control, to further improve the control precision of the system. The fuzzy PID control system simulation model and the variable universe fuzzy PID control are investigated. Results are compared and indicate that the variable universe fuzzy PID control demonstrates better dynamic and static performance. Show more

Keywords: HTS machine excitation system, fuzzy PID, variable universe fuzzy control, simulation analysis

DOI: 10.3233/IFS-151946

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 6, pp. 2457-2465, 2015

Authors: Pan, Cheng-Yi | Wei, Wen-Long | Zhang, Chun-Yi | Song, Lu-Kai | Lu, Cheng | Liu, Ling-Jun

Article Type: Research Article

Abstract: To improve the precision of reliability analysis on turbine blades, the fuzzy response surface method of reliability analysis is proposed by considering the fuzziness of the input variables and the vagueness of the limit state variables. Initially, the fuzzy basic variables were converted into equivalent random variables according to the method of equivalent transformation. Additionally, the mathematic model of the fuzzy response surface for structural reliability analysis was established, based on the quadratic polynomial response surface function. The mean value and variance of the blade stress and radial deformation were obtained by using the Monte-Carlo method based on generous linkage …sampling to the model. Finally, the probability of failure and fuzzy random reliability index were calculated based on the probability integral method. Results indicate that the reliability probability of the blade is 97.665% , when the allowable stress and deformation are 390 MPa and 0.195 mm, respectively. It is demonstrated that with an increase of the fuzzy coefficient, the blade reliability index decreases; thus, the random reliability of the blade is slightly higher than the fuzzy reliability. Show more

Keywords: Fuzzy, reliability analysis, response surface method, blade, aero-engine

DOI: 10.3233/IFS-151947

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 6, pp. 2467-2474, 2015

Authors: Zhao, Wenjie | Zhao, Gang | Lv, Meng | Zhao, Jianjun

Article Type: Research Article

Abstract: Combustion optimization adjustment can effectively suppress NOx emissions from power plant boilers. Current combustion optimization adjustment methods involve nonlinear optimization based on the boiler combustion model, such as optimization by a genetic algorithm or particle swarm algorithm. The computational complexity of these methods results in poor real-time performance, which limits their practical applications. To solve this problem, a fuzzy optimization control method with better real-time performance is proposed. First, the space of the disturbance variables (DV), which are the input variables that combustion systems cannot adjust, is divided into a certain number of sub-spaces. Each sub-space center is then obtained …using the corresponding optimal combustion mode by offline nonlinear optimization, thereby forming a complete expert rule base. The corresponding optimal manipulated variables (MV), which are the input variables that combustion systems can adjust, are then quickly obtained online by means of fuzzy inference for each inputted DV. The fuzzy optimization control of boiler combustion adjustment is then determined. Simulation has shown that both the fuzzy optimization control method and the nonlinear optimization method can achieve a consistent control effect. However, the fuzzy optimization control method has a better real-time performance. Show more

Keywords: NOx emissions, combustion adjustment, nonlinear optimizing, fuzzy optimization control

DOI: 10.3233/IFS-151948

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 6, pp. 2475-2481, 2015