Journal of Intelligent & Fuzzy Systems - Volume 33, issue 5

Authors: Yu, Miao | Mei, Sisi | Lu, Zichen | Xiao, Jiqiu

Article Type: Research Article

Abstract: In a market economy, it isn’t an effective solution to the main contradiction of the Customs if simply relying on unlimited investment of management resources and the extensive extension of expansion-style management. Based on the need of solving this principal contradiction, the paper comprehensively reviews the concept and status of risk dispatched. We constructed a customs risk decision and performance evaluation of risk parameters management theoretical models. Also, we analyze the problems of customs risk management both from qualitative and quantitative aspects and make recommendations for the further optimization of risk management and surveillance.

Keywords: Risk dispatched, risk decision, performance evaluation of risk parameters

DOI: 10.3233/JIFS-169343

Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 5, pp. 2925-2935, 2017

Authors: Li, Chen | Wei, Fajie | Wang, Cheng | Zhou, Shenghan

Article Type: Research Article

Abstract: To guarantee the performance and security of the complex system, in this paper, we focus on the problem of fault diagnosis and fault prediction method for the complex system. The proposed fault diagnosis and prediction system is made up of three parts: 1) Data preprocessing, 2) Degradation state detection, and 3) Fault diagnosis. Afterwards, we exploit the Wavelet transform correlation filter to extract features for complex system fault diagnosis and prediction. Particularly, the direct spatial correlations of wavelet transform contents are used to search the locations of edges. To promote the performance of Hidden Markov model, we propose a HMM-based …semi-nonparametric method by the probabilistic transition frequency profile matrix and the average probabilistic emission matrix. Then, the training sequence which is the most similar to a particular sequence can be found by the modified HMM model. Finally, experimental results prove that the proposed algorithm can effectively enhance the accuracy of equipment fault diagnosis and equipment state recognition task. Show more

Keywords: Complex system, Hidden Markov model, fault diagnosis, fault prediction

DOI: 10.3233/JIFS-169344

Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 5, pp. 2937-2944, 2017

Authors: Li, Quanbao | Wei, Fajie | Zhou, Shenghan

Article Type: Research Article

Abstract: Multi-variety and small batch production is one type of mainstream production methods. Currently, methods of enterprise risk warning have been abundantly researched by scholars, but the effect of its application to the multi-variety and small batch manufacturing practices is not ideal. In this study, the authors apply the transductive support vector machine and active learning to the study of enterprise risk and early warning methods. The experiment utilizes real-world enterprise data and demonstrates that this method may meet the practical needs of the enterprise risk early warning systems and contributes to solving problems of multi-variety and small batch manufacturing operations.

Keywords: Early warning, risk management, active learning, transductive support vector machine, semi-supervised learning

DOI: 10.3233/JIFS-169345

Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 5, pp. 2945-2952, 2017

Authors: Du, Yuan-Wei | Xu, Wen-Ming

Article Type: Research Article

Abstract: The existing multiattribute group decision making methods with interval-valued intuitionistic fuzzy (IVIF) sets only consider weights of the experts who participated in decision making, however the reliabilities of that are not considered at all. In order to solve this problem and make a much scientific decision, a transformation method from IVIF value to belief degree is defined based on the frame of discernment consisting of only excellent and non-excellent two hypotheses. Then the basic probability assignment (BPA) function computing method is introduced by discounting belief degrees with both weights and reliabilities. The derived BPA functions are combined by the analytically …evidential reasoning (ER) methodology for two times, the one is to combine BPA functions on all attributes with respect to a specified expert, and the other is to combine the combined BPA functions for all experts with respect to a specified alternative. Finally, the relative coefficient is employed to rank the alternatives with IVIF sets. An example is proposed to illustrate the decision making process by the proposed method. Show more

Keywords: Multiple attribute decision making, group decision making, interval-valued intuitionistic fuzzy sets, evidential reasoning, expert reliability

DOI: 10.3233/JIFS-169346

Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 5, pp. 2953-2960, 2017

Authors: Huang, Jun | Zhu, Dingju | Tang, Yong

Article Type: Research Article

Abstract: This paper discussed a healthcare big data analysis system and device for health diagnosis robot. The system is composed of the health examination data acquisition equipment and a healthcare big data server. The health examination data acquisition equipment is used for acquiring health examination target data to be sent to the healthcare big data server. The healthcare big data server is used for searching the healthcare big data for health examination source data of the highest fuzzy matching degree with health examination target data. The corresponding diagnosis data to health examination source data is retrieved from healthcare big data server, according to …which the analysis results corresponding to health examination target data is generated. The healthcare big data analysis system and device for health diagnosis robot provided in this paper makes the best of the healthcare big data to carry out analysis on health examination target data in order to improve the accuracy of the analysis results and raise the utilization rate of the healthcare big data. Show more

Keywords: Healthcare big data, health diagnosis, big data analysis

DOI: 10.3233/JIFS-169347

Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 5, pp. 2961-2970, 2017

Authors: Li, Yujie | Zhang, Long | Liu, Haorui

Article Type: Research Article

Abstract: This paper presents a novel indirect type-2 fuzzy sliding mode (T2FSM) control approach for fractional order chaotic systems. In this paper both switching control term and the equivalent control term are estimated in comparison with the current fuzzy sliding mode control system designs, where the control law of sliding mode is directly replaced by a fuzzy term controller. The consequent adaptive T2FSM parameters are adjusted online to synchronize two fractional order systems with uncertainty. As a result, the chattering phenomenon is weakened and the error is also lessened, while the controller robustness against system uncertainties and unknown disturbances is improved. …The designed approach has achieved the following advantages. Firstly, by applying the Lyapunov design method and interval T2FSM method to achieve the control law. This proposed approach makes a good performance for the overall system. Another advantage of the proposed design is to relax the requirement for the limit of approximation error and an estimation method is also employed to observe the bound of it real time. Simulation results confirm the perfect method in the existence of a disturbance with uncertainty. Show more

Keywords: Fractional-order systems, chaotic synchronization, sliding mode control, Lyapunov synthesis, fuzzified switching-type term

DOI: 10.3233/JIFS-169348

Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 5, pp. 2971-2978, 2017

Authors: Pan, Weiwei | He, Huixin

Article Type: Research Article

Abstract: Fault level identification is a new challenge and a special task in the field of fault diagnosis. There are ordinal structures between different fault levels, so how to utilize the potential ordinal information is especially important for fault level diagnosis. Fault level identification can be regarded as ordinal classification in the fields of machine learning and pattern recognition. This paper first proposes an ordinal rough set model by introducing ordinal rough approximation operators based on fuzzy covering, and then designs a feature selection algorithm for ordinal classification. Finally, the proposed method is applied to the gear crack level identification. Experimental …results demonstrate the effectiveness of the proposed approach for fault level identification. Show more

Keywords: Ordinal classification, feature selection, fuzzy covering, fault level identification

DOI: 10.3233/JIFS-169349

Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 5, pp. 2979-2985, 2017

Authors: Zhang, Limei | Liu, Yongfu | Zhang, Penghui | Tang, Wei | Lv, Jing | Zhang, Lu | Li, Dongming

Article Type: Research Article

Abstract: With the penetration of multi-source and multi-type distributed generation (DG) in distribution network, the power flow calculations of distribution network become more and more complex. On the premise of analysis of power flow calculation model for different DG, this paper presents a power flow parallel computing algorithm for complex distribution network based on multicore CPU technique. On the basis of analysis of topological structure of distribution system, the task assignment problems in the isomorphism multicore processors were solved to improve speedup ratio and parallel efficiency. Integrated with the characteristics of backward/forward sweep methods, a hybrid power flow parallel computing method …was given to adapt for the nodal type of various DG. In order to test the convergence and parallel efficiency, the proposed algorithm have been tested on IEEE 90 bus and a composite system, which is composed of IEEE 20 bus, IEEE 90 bus, IEEE 37 bus and etc. The results show that the proposed hybrid power flow computing method is adaptive to the complex distribution network with multi-type DGs, and the designed parallel algorithm effectively shortens time of solving equations and multicore resources are fully utilized. Show more

Keywords: Distributed generation, distribution network, power flow, parallel computing

DOI: 10.3233/JIFS-169350

Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 5, pp. 2987-2997, 2017

Authors: Ji, Ying | Ma, Gang | Wei, Ju | Dai, Yeming

Article Type: Research Article

Abstract: The goal of this paper is going to present a hybrid approach to solve multi-criteria bilevel optimization models with uncertain parameters in the objective functions. In reality, the player can not provide the weights to the objectives exactly. Since to assert the correct weight for objective is difficult, ambiguity is often not absent in the weights given by the player. Therefore, each player (leader or follower) usually has to choose a weight of his objective from a given set. Then, we proposed a robust optimization approach to copy with this situation, where each player obtains his strategy by minimizing his …worst-case weighted sum objective over the given weight region. We note that the worst-case implies the maximization of the weights. The corresponding reformulation is presented with the different choice of weights. By an application in supply chain optimization with the consideration of both supply and demand uncertainties, the usefulness of the proposed method is shown. The comparison with the existed approach is also presented. Show more

Keywords: Uncertain multi-criteria programs, bilevel optimization, robust, Pareto, supply chain

DOI: 10.3233/JIFS-169351

Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 5, pp. 2999-3008, 2017

Authors: Liu, Gengchen | Zhang, Jianwu

Article Type: Research Article

Abstract: Plug-in hybrid electric vehicles (PHEVs) provide the flexibility to be used as pure electric vehicles in daily commuting, as well as common hybrid vehicles (HEVs) on longer trips. To appropriately distribute power between the engine and the energy buffer (normally battery) without sacrificing fuel economy, optimal control strategies of varies kinds have been proposed in recent years. Some strategies, however, cannot be applied in real time environment for the tightly independent on the future driving information. Some others could identify the different road condition but the identification accuracy is questionable, making their real-world effectiveness could suffer significantly. Moreover, the proposed …energy management method seldom consider the effect from the driver behavior, which is an essential factor that can determine the vehicle energy consumption. For such reasons, this paper proposes a novel energy management strategy, the instantaneous optimization method—Equivalent Consumption Minimization Strategy (ECMS) is chosen as the foundation solution to the PHEV energy management problem. Then the paper studies the effect from different driver behavior and uses fuzzy logic method to identify different drive behavior. Combined with the pre-knowledge provide by Intelligent Transport System (ITS), the equivalent factor, which is the core of ECMS, is adjusted, making the real instantaneous application of ECMS. Then the simulation is performed to prove its viability and effectiveness. Show more

Keywords: Equivalent Consumption Minimization Strategy (ECMS), Intelligent Transport System (ITS), equivalent factor, fuzzy logic, traffic flow theory

DOI: 10.3233/JIFS-169352

Citation: Journal of Intelligent & Fuzzy Systems, vol. 33, no. 5, pp. 3009-3020, 2017