Journal of Intelligent & Fuzzy Systems - Volume Pre-press, issue Pre-press

Authors: Wu, Tsu-Yang | Lin, Jerry Chun-Wei | Yun, Unil | Chen, Chun-Hao | Srivastava, Gautam | Lv, Xianbiao

Article Type: Research Article

Abstract:  Association-rule mining (ARM) has concerned as an important and critical research issue in the field of data analytics and mining that aims at finding the correlations among the items in binary databases. However, conventional algorithms considered the frequency of the item(sets) in binary databases for ARM, which is not sufficient in real-life situations. Mining of useful information is not an easy task especially if the item(sets) consist of the added values. Moreover, the discovered knowledge is not easy to understand if you are not the domain experts. For the past decades, several intelligent systems involved the fuzzy-set theory for many …domains and applications due to it is interpretable for human reasoning. Before, the Apriori-based method for discovering fuzzy frequent itemsets (FFIs) based on the type-2 fuzzy-set theory was proposed, which requires the amount of computations with enormous candidates. In this study, we then first present a fast list-based multiple fuzzy frequent itemset mining (named as LFFT2)algorithm under type-2 fuzzy-set theory. It is developed by the type-2 membership functions to retrieve the multiple fuzzy frequent itemsets for presenting more useful and meaningful knowledge for making the efficient strategies or decisions. From the results shown in the experiments, it is clear to see that the developed LFFT2 outperforms the conventional Apriori-based approach regarding the execution time and the number of examined nodes in the search space. Show more

Keywords: Data mining, fuzzy frequent itemset mining, type-2 fuzzy-set theory, list-based structure

DOI: 10.3233/JIFS-179666

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Zhou, Jun | Zhou, Xuan | Liang, Guangchuan | Peng, Jinghong

Article Type: Research Article

Abstract:  Underground natural gas storage (UNGS), usually regarded as one of the most important gas storing and peak shaving method today, has been widely used in various parts of the world. The pipeline gathering system plays a key role in UNGS surface engineering. Thus, optimization of the whole system is crucial to lower the total investment. However, we cannot find that any scholars have published related papers on the gathering pipeline network for UNGS at present. This paper focuses on the two-level star gas field gathering pipeline network construction, establishes a mixed integer nonlinear programming (MINLP) model with considering the injection …and withdrawal process of UNGS. Minimizing pipeline network investment is the object of this model. Constraints of connection mode, platform, pipe length, flow rate, node pressure, pipe diameter are also taken into consideration in this model. A special genetic algorithm is proposed to figure out the optimal topological structure, location of platform and central station, pipe diameter, gas velocity along each pipe of this model. Last, two typical real cases are taken to test the applicability of the proposed model and the accuracy of the special GA. The optimal results indicate the mathematical model can lower the total investment and the corresponding GA can solve it efficiently. Show more

Keywords: Layout, pipeline network, GA, underground natural gas storage, MINLP

DOI: 10.3233/JIFS-191383

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-24, 2020

Authors: Chen, Tao | Lv, Hongxia | Sun, Yichen | Wang, Xiaoyi

Article Type: Research Article

Abstract: As one kind of highest hierarchy node on the network, the transfer scheme of high-speed railway hub timetable should be studied at priority. After defining the problem that optimizing transfer scheme of timetable at high-speed railway hub, this paper proposes time adjusting strategy and platform adjusting strategy to optimize the problem, of which the first strategy introduces a FUZZY set of reasonable time range to reduce the possible train conflicts at adjacent stations on the network, and the second strategy helps to use different transfer time to match the arrival and departure of trains. Then, an optimization model of timetable …based on passenger transfer is established with the minimized invalid transfer waiting time for passenger and train conflicts at adjacent stations as the objective function. The model is solved by the above two strategies in MATLAB software. Finally, the rationality and effectiveness of this model are verified, taking Shanghai Hongqiao Station as an example. Show more

Keywords: High-speed railway, hub, transfer, timetable optimization

DOI: 10.3233/JIFS-179662

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Li, Zhanhui | Fan, Jiancong | Ren, Yande | Tang, Leiyu

Article Type: Research Article

Abstract: As a common disease, migraine has a high incidence but the pathogenesis is still not clear. Resting-state Functional Magnetic Resonance Imaging (rs-fMRI) is an important research topic in the field of brain medicine, which can classify rs-fMRI data to automatically diagnose brain diseases. However, the original features of the rs-fMRI data are difficult to be extracted and the high-dimensional characteristics, which make the data analysis an extremely complicated task. Those have also plagued many researchers and bring great challenges to the existing pattern classification methods. Aiming at the high dimensionality of rs-fMRI data, in this paper, we propose a feature …extraction approach based on the combination of neighborhood rough set and PCA, thereby improving the accuracy of migraine identification. Firstly, Resting-State fMRI Data Analysis Toolkit plus was applied for preprocessing, calculating three characteristic indices: Amplitude of Low Frequency Fluctuation (ALFF), Regional Homogeneity (ReHo) and Functional Connectivity (FC. The inter-group difference analysis was performed by two-sample T test and GRF correction. Then, correlation coefficient matrix original features extraction was performed by means of automatic anatomical label template (AAL). Finally, the original features were trained by the traditional classification algorithm in machine learning. The experimental results show that the propose approach can obtain good performance in predicting migraine. Show more

Keywords: Resting state functional magnetic resonance imaging, migraine, correlation coefficient matrix, neighborhood rough set, principal component analysis, classification

DOI: 10.3233/JIFS-179661

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2020

Authors: Nguyen, Luong V. | Thu, Nguyen T.

Article Type: Research Article

Abstract: In this paper, we prove a fixed point theorem for intuitionistic fuzzy mappings concerning F -contractions without using the Pompeiu – Hausdorff distance between cut sets of intuitionistic fuzzy mappings. This result and its consequences extend and generalize several results in the literature. An application to the existence for solutions of a delay integral equation of Volterra type and an example are given to illustrate the usability of our results.

Keywords: Intuitionistic fuzzy mappings, intuitionistic fuzzy fixed point, nonlinear F-contractions, delay integral equations

DOI: 10.3233/JIFS-191806

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2020

Authors: Tingyu, Yang | Xiaoqian, Peng | Dingjun, Chen | Feiyu, Yang | Muneeb Abid, Malik

Article Type: Research Article

Abstract: With the increasingly close links between provinces and municipalities, the complexity and social connectivity of emergencies have gradually increased. How to realize the rapid and scientific dispatch of emergency resources based on the comprehensive transportation network has become a realistic need. However, due to barriers in management and communication between different administrative regions and different modes of transportation, emergency resource scheduling can only be carried out in the region, and the utilization of integrated traffic channels is insufficient to form a good multimodal transport system. The multi-agent system has strong self-organization ability, learning ability and reasoning ability, which solves problems …in the fields of dynamic decision-making and micro-simulation and provides ideas for solving the problem of comprehensive traffic emergency dispatching across regions. In this paper, the multi-agent system is introduced into the research of the task assignment problem of trans-regional comprehensive traffic emergency materials dispatching, based on the traditional bidding rules, the emergency dispatch task assignment rules are proposed and multi-agent trans-regional comprehensive traffic emergency dispatching model based on improved bidding rules is established. The simulation results show that the proposed method can break the regional barrier and form a multimodal transport scheme for emergency materials from the reserve point to the demand point under the minimum generalized time cost, providing decision support for emergency dispatch. Show more

Keywords: Multi-agent, trans-region, emergency dispatch, bidding

DOI: 10.3233/JIFS-179664

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2020

Authors: Zhang, Peiwen | Tao, Zhifu | Liu, Jinpei | Jin, Feifei | Zhang, Junting

Article Type: Research Article

Abstract: The aim of this paper is to develop a multi-attribute group decision making (MAGDM) with picture fuzzy sets based on ELECTRE TRI method, i.e., an ELECTRE TRI based group decision making with picture fuzzy information is given. The MAGDM with picture fuzzy information based on picture fuzzy ELECTRE TRI outranking method is divided into three stages, i.e., the group decision information aggregation stage, determination of parameters and ELECTRE TRI outranking based outranking stage. A novel comparison law for picture fuzzy sets is introduced. In the group decision information aggregation stage, the concept of picture fuzzy normalized weighted Bonferroni mean (PFNWBM …) is developed. The developed decision procedure is further applied to the assessment of energy security. The numerical example shows that the developed group decision procedure is feasible and valid. Show more

Keywords: Multi-attribute group decision making, picture fuzzy sets, ELECTRE TRI, supplier selection, picture fuzzy normalized Bonferroni mean

DOI: 10.3233/JIFS-191540

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2020

Authors: Liu, Yang | Lio, Waichon

Article Type: Research Article

Abstract: Nowadays, uncertainty theory has become a branch of axiomatic mathematics and has been studied by many researchers. In particular, uncertainty distribution is one of the most important tools to deal with indeterminate quantity in uncertainty theory. Peng and Iwamura (2010) presented a sufficient and necessary condition of a function being an uncertainty distribution. This paper gives a counterexample to illustrate this condition is not appropriate. A revision of the sufficient and necessary condition is also provided in this paper.

Keywords: Uncertainty theory, uncertain variable, uncertainty distribution

DOI: 10.3233/JIFS-191535

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2020

Authors: Xu, Changan | Li, Sihan | Xu, Heying | Ni, Shaoquan

Article Type: Research Article

Abstract: Passenger train occupation rate directly affects Railway Company’s revenue and capacity utilization of railway infrastructure, and measures to improve passenger train occupation rate is always the focus of railway companies’ attention. However, researches on what, and how factors influence passenger train occupation rate remain sparse. Based on the collective data of 363 passenger trains on the Beijing-Shanghai High-speed Railway in November 2015, this paper establishes a data-driven analysis framework to explore the influencing factors of passenger train occupation rate. Specifically, we first analyze the possible factors that influence train occupation rate from the perspective of train service planning. Then, the …approach of association rules is applied to analyze the potential relationship between train occupation rate and its influencing factors. And a total of 6711 and 8133 association rules were generated for high and low train occupation rate of passenger trains, respectively. Further analysis found that train departure and arrival times, train departure and arrival station class and the type of trains are the main factors influencing the level of train occupation rate. These findings can provide reference for train service planning. Show more

Keywords: Passenger train occupation rate, association rules, train service planning, Beijing-Shanghai high-speed railway

DOI: 10.3233/JIFS-179663

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2020

Authors: Xie, Chao-Fan | Xu, Lu-Xiong | Zhang, Fuquan

Article Type: Research Article

Abstract: Because of high efficiency and cleanness, the simulated moving bed (SMB) is the most important technology in chromatographic separation. SMB system, which contains several sectors of flow rate, the switching time of valves and many other possible influencing variables, is complex, highly sensitive and difficult to control. This paper proposes adjusted fuzzy control; the adjusted fuzzy controller is applied to the SMB system to control the separation concentration by establishing a variable direction correction formula. Compared with the traditional fuzzy controller, the adjusted fuzzy controller does not need to analyze the dynamic direction of the control force in advance, moreover, …the control accuracy is high and the fluctuation is small for SMB system. Show more

Keywords: Chromatographic, SMB, fuzzy, control

DOI: 10.3233/JIFS-179660

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2020