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

Authors: Lei, Fan | Wei, Guiwu | Wu, Jiang | Wei, Cun | Guo, Yanfeng

Article Type: Research Article

Abstract: Probabilistic uncertain linguistic sets (PULTSs) have extensively been employed in multiple attribute group decision making (MAGDM)problem. The QUALIFLEX method, which is relatively a novel MAGDM technique, aims to obtain the optimal alternative. This paper proposes the probabilistic uncertain linguistic QUALIFLEX (PUL-QUALIFLEX) method with CRITIC method. To show the effectiveness of the designed method, an application is given for green supplier selection and the derived results are compared with some existing methods. Thus, the advantage of this proposed method is that it is simple to understand and easy to compute. The proposed method can also contribute to the selection of suitable …alternative successfully in other selection issues. Show more

Keywords: Multiple attribute group decision making (MAGDM), probabilistic uncertain linguistic term sets (PULTSs), CRITIC method, QUALIFLEX method, green supplier selection

DOI: 10.3233/JIFS-191737

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

Authors: Chuanchao, Zhang

Article Type: Research Article

Abstract: In view of the characteristics with big date, high feature dimension, and dynamic for a large-scale intuitionistic fuzzy information systems, this paper integrates intuitionistic fuzzy rough sets and generalized dynamic sampling theory, proposes a generalized attribute reduction algorithm based on similarity relation of intuitionistic fuzzy rough sets and dynamic reduction. It uses dynamic reduction sampling theory to divide a big data set into small data sets and relative positive domain cardinality instead of dependency degree as decision-making condition, and obtains reduction attributes of big intuitionistic fuzzy decision information systems, and achieves the goal of extracting key features and fault diagnosis. …The innovation of this paper is that it integrates generalized dynamic reduction and intuitionistic fuzzy rough set, and solves the problem of big data set which cannot be solved by intuitionistic fuzzy rough set. Taking an actual data as an example, the scientificity, rationality and effectiveness of the algorithm are verified from the aspects of stability, diagnostic accuracy, optimization ability and time complexity. Compared with similar algorithms, the advantages of the proposed algorithm for big data processing are confirmed. Show more

Keywords: Intuitionistic fuzzy rough set, similarity relation, relative positive domain, generalized dynamic reduction, large fuzzy decision information system, attribute reduction

DOI: 10.3233/JIFS-200347

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-17, 2020

Authors: Fei, Kaifang | Jiang, Minghui | Zhang, Yadan

Article Type: Research Article

Abstract: In this paper, the matters of dissipativity and finite time synchronization for memristor-based neural networks (MNNs) with mixed time-varying discontinuities are investigated. Firstly, under the framework of extending Filippov differential inclusion theory, several effective new criteria are derived. Then, the global dissipativity of Filippov solution to neural networks is proved by using generalized Halanay inequality and matrix measure method. Secondly, some novel sufficient conditions are introduced to guarantee the finite-time synchronization of the drive-response MNNs based on a simple Lyapunov function and two different feedback controllers. Finally, several numerical examples are given to verify the validity of the theoretical results.

Keywords: Memristor, dissipativity, finite time synchronization, mixed time-varying delayed, neural networks

DOI: 10.3233/JIFS-191397

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-18, 2020

Authors: Saini, Jagriti | Dutta, Maitreyee | Marques, Gonçalo

Article Type: Research Article

Abstract: Indoor air pollution (IAP) has become a serious concern for developing countries around the world. As human beings spend most of their time indoors, pollution exposure causes a significant impact on their health and well-being. Long term exposure to particulate matter (PM) leads to the risk of chronic health issues such as respiratory disease, lung cancer, cardiovascular disease. In India, around 200 million people use fuel for cooking and heating needs; out of which 0.4% use biogas; 0.1% electricity; 1.5% lignite, coal or charcoal; 2.9% kerosene; 8.9% cow dung cake; 28.6% liquified petroleum gas and 49% use firewood. Almost 70% …of the Indian population lives in rural areas, and 80% of those households rely on biomass fuels for routine needs. With 1.3 million deaths per year, poor air quality is the second largest killer in India. Forecasting of indoor air quality (IAQ) can guide building occupants to take prompt actions for ventilation and management on useful time. This paper proposes prediction of IAQ using Keras optimizers and compares their prediction performance. The model is trained using real-time data collected from a cafeteria in the Chandigarh city using IoT sensor network. The main contribution of this paper is to provide a comparative study on the implementation of seven Keras Optimizers for IAQ prediction. The results show that SGD optimizer outperforms other optimizers to ensure adequate and reliable predictions with mean square error = 0.19, mean absolute error = 0.34, root mean square error = 0.43, R2 score = 0.999555, mean absolute percentage error = 1.21665, and accuracy = 98.87%. Show more

Keywords: Indoor air quality, pollutants, prediction system, optimizers

DOI: 10.3233/JIFS-200259

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-17, 2020

Authors: Zhang, Gangqiang | Li, Zhaowen | Zhang, Pengfei | Xie, Ningxin

Article Type: Research Article

Abstract: An information system as a database that stands for relationships between objects and attributes is an important mathematical model. An image information system is an information system where each of its information values is an image and its information structures embody internal features of this type of information system. Uncertainty measurement is an effective tool for evaluation. This paper explores measures of uncertainty for an information system by using the proposed information structures. The distance between two objects in an image information system is first given. After that, the fuzzy T cos -equivalence relation, induced by this system by …using Gaussian kernel method, is obtained, where Gaussian kernel is based on this distance. Next, information structures of this system are described by set vectors, dependence between information structures is studied and properties of information structures are given by using inclusion degree, and application for information structures and uncertainty measures of an image information system are investigated by the information structures. Moreover, effectiveness analysis is done to show the feasibility of the proposed measures from the angle of statistics. Finally, an application of the proposed measurement for attribute reduction is given. These results will be helpful for understanding the essence of uncertainty in an image information system. Show more

Keywords: Granular computing, image information system, distance, information structure, dependence, inclusion degree, uncertainty, measure

DOI: 10.3233/JIFS-191628

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-23, 2020

Authors: Barlak, Damla

Article Type: Research Article

Abstract: In this study, we introduce the concepts of φ λ ,μ -double statistically convergence of order β in fuzzy sequences and strongly λ - double Cesaro summable of order β for sequences of fuzzy numbers. Also we give some inclusion theorems.

Keywords: Statistical convergence, Cesàro summability, Modulus function, 40A05, 40A25, 40A30, 40C05, 03E72

DOI: 10.3233/JIFS-200039

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-6, 2020

Authors: Li, Feng

Article Type: Research Article

Abstract: Mining maximal frequent patterns is significant in many fields, but the mining efficiency is often low. The bottleneck lies in too many candidate subgraphs and extensive subgraph isomorphism tests. In this paper we propose an efficient mining algorithm. There are two key ideas behind the proposed methods. The first is to divide each edge of every certain graph (converted from equivalent uncertain graph) and build search tree, avoiding too many candidate subgraphs. The second is to search the tree built in the first step in order, avoiding extensive subgraph isomorphism tests. The evaluation of our approach demonstrates the significant cost …savings with respect to the state-of-the-art approach not only on the real-world datasets as well as on synthetic uncertain graph databases. Show more

Keywords: Uncertain graph, maximal frequent pattern, data mining

DOI: 10.3233/JIFS-200237

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

Authors: Li, Chunya | Li, Yan

Article Type: Research Article

Abstract: This paper establishes a theoretical model of third-party mobile payment user satisfaction based on the ASCI model and proposes research hypotheses. Then, the questionnaire survey method is used to collect sample data and carry out reliability and validity test. After the test is passed, structural equation modeling (SEM) is used to verify the research model and hypothesis. Finally, the analysis concludes: perceived quality and perceived value will have a positive impact on user satisfaction; user expectations will affect user satisfaction through perceived quality and perceived value; the impact of perceived risk on user satisfaction is not obvious. Propose reasonable suggestions …for third-party mobile payment companies based on the research conclusions. Show more

Keywords: Third-party mobile payment, internet of things, structural equation model (SEM)

DOI: 10.3233/JIFS-189425

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

Authors: Pan, Dongyang | Liu, Jingrui

Article Type: Research Article

Abstract: Mechanical biology is the study of the influence of the mechanical environment on human health, disease, or injury. To study the mechanism of the organism’s perception and response to mechanical signals can promote the development of biomedical basic and clinical research, and promote human health. The purpose of this paper is to study the mathematical modeling method of the effect of multimodal mechanical signals on cell stretching and compression. This article first established a cell mechanics model based on the generalization of membrane theory, introduced the micro-manipulation techniques used to characterize cell mechanics and the method of cell mechanics loading, …and then explained why mathematical modeling was established. Finally, according to the multi-modality During the mechanical preparation process, the effects of multi-modal mechanical signals on the stretching and compression of annulus fibrosus stem cells were studied. The experimental results in this paper show that after planting fibrous stem cells with different elastic modulus, the cell proliferation is obvious after the tensile mechanical stimulation of different conditions, and the different elastic modulus scaffolds are stimulated by the tensile mechanical stimulation of 2% tensile amplitude. The cell morphology is different. The low elastic modulus is round-like, and the high elastic modulus is fusiform-like. After 5% and 12% stretch amplitude, the cells are oriented at different elastic modulus. Arranged, there is no obvious difference in cell morphology. Show more

Keywords: Multimodal mechanical signals, cell stretching and compression, mathematical modeling methods, cell biomechanics

DOI: 10.3233/JIFS-189422

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

Authors: Qian, Yu

Article Type: Research Article

Abstract: With the development of wireless sensor technology, more and more fields are applied to wireless sensor technology, and the design and implementation of the flight scene system are in it. The purpose of this study is to design and implement a flight visual simulation system using sensor technology and QAR data. The method of this study is to first establish the mathematical model of the aircraft and then calculate the aerodynamic force and torque of each part of the aircraft respectively to obtain the nonlinear dynamic model of the aircraft, and finally realize the whole simulation model on the MATLAB …platform. The results show that the main motion variables corresponding to the conjugate complex root (0.0530.287i) are the velocity and pitch angle of the aircraft, and they all change slowly and long period. The period is 21.9 seconds, and the frequency doubling time (LN2 / 0.053 + 0.287i) is 11.0 seconds, which meets the requirements of flight quality specification. It is concluded that the flight visual simulation system in this study can well describe the flight trajectory and observe the external scene. The simulation system uses computer graphics and image technology to realize real-time and accurate simulation and reproduction of the flight status and trajectory of the aircraft, which can provide an intuitive and convenient simulation analysis method for the exploration of new aerospace technology and engineering design. Show more

Keywords: Sensor technology, QAR data, flight visual system, simulation design

DOI: 10.3233/JIFS-189429

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