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

Authors: Wang, Wei | Cai, Guanghui | Hu, Junjuan

Article Type: Research Article

Abstract: Through considering the volatility asymmetry in financial markets, we extend the threshold autoregressive conditional heteroskedasticity model to the general threshold autoregressive conditional heteroskedasticity model with asymmetry. The sufficient conditions for the existence of the stationary solution and the finiteness of the moments of the model are derived. The parameters and the threshold value of the model are estimated using the quasi-maximum likelihood method. The results of Monte Carlo simulation method show that the method performs well. By applying this method to the Shanghai daily return and volatility series with the significant leverage effect, we find that the asymmetric model with …general threshold better reflects the asymmetric fluctuation characteristics than the original model. Show more

Keywords: Volatility asymmetry, GARCH model, threshold value, maximum likelihood method, Monte Carlo simulation

DOI: 10.3233/JIFS-179849

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2020

Authors: Xi, Liang | Yao, Zhiyu | Zhao, Yilin | Zhang, Fengbin | Sun, Yuezhongyi

Article Type: Research Article

Abstract: The clonal selection algorithm(CSA) is a core method in artificial immune system, which is famous for its intelligent evolution in artificial intelligence application. However, There are some shortcomings in the algorithm, such as local optima and low convergence speed, which make its practical effects not ideal. Culture algorithm(CA) is driven by knowledge, which can significantly improve the evolutionary efficiency. Chaos mechanism can make the algorithm have better problem space coverage ability. Therefore, a culture&chaos-inspired CSA(CC-CSA) is proposed in this paper to deal with the problems mentioned before. CC-CSA adopts the double-layer evolutionary framework of CA to extract knowledge and guide …the crossover and chaotic mutation operation to complete the evolution process. The implicit knowledge is used to adaptively control the chaotic mutation scale, guide the individuals to jump out of the local optima, and realize the accurate search in the latter evolution cycle to gradually approach the optimal solution. It can be seen from the mathematical model analysis that CC-CSA can converge to the global optimal solution. Compared with the experimental results of the original CSA and its representative, up-to-date improved methods, CC-CSA has the fastest convergence speed and the best detection performances. It is also proved that CC-CSA can solve the problems of local optima and slow convergence speed by using the knowledge guidance of CA’s double-layer framework and good coverage ability of chaos mechanism to the problem space. Show more

Keywords: Artificial immune system, clonal selection algorithm, culture algorithm, chaos mechanism, abnormal detection

DOI: 10.3233/JIFS-192188

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

Authors: Liu, Rong | Li, Huajun

Article Type: Research Article

Abstract: This paper proposes the concept of an intelligent logistics system (ILS) in the context of the Internet of Things (IoT), expounds the characteristics of the ILS, and constructs a logical framework of the ILS based on the IoT. In the dynamic IoT environment, in order to obtain a highly satisfied logistics service, a locally optimal choice of logistics service selection scheme is proposed. This scheme uses the traditional web service combination idea to solve the intelligent logistics service problem. First, model and calculate the Quality of Service (QoS) attributes in logistics, and then select an atomic solution with the best …utility value from each logistics sub-process, perform service composition and execute. The feasibility and effectiveness of the model and algorithm under this scheme are verified by experiments. Show more

Keywords: Internet of Things, intelligent logistics, service composition, web service, logistics service

DOI: 10.3233/JIFS-179854

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2020

Authors: Zhanga, Ye | Haob, Qiang | Caib, Guoqiang | Yangc, Chen

Article Type: Research Article

Abstract: The prevailing vehicle recognition technology is adversely affected by the environment such as complex traffic scenarios and weather conditions. This paper proposes a robust vehicle recognition model based on human memory mechanism named Memory-based Vehicle Recognition Model (MVRM). Motivated by the success of memory and attention mechanism, we explore some features of human visual attention model. Fusing short term and long-term memory modules together yield deeper architectures recognizing increasing complex environmental scenarios. Firstly, a rare motion feature has been introduced to measure the visual salience, which improves the accuracy of the visual attention mechanism. Second, a model of vehicle salient …region recognition has been established. The results of experiments show that the dynamic vehicle recognition rate of MVRM is 77.10%, while its false recognition rate has only a nominal value of ∼4.5%. Furthermore, the model offers good recognition of vehicle targets under complex environment conditions related to weather and road traffic. Show more

Keywords: Vehicle recognition, human memory, complex environment, cognitive

DOI: 10.3233/JIFS-179852

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

Authors: Li, Guangrong | Yang, Jinxiu | Huang, Ying

Article Type: Research Article

Abstract: Supply chain finance (SCF) plays a prominent role in solving the small-middle enterprises financing difficulties. But its credit risk is easy to conduct and magnify alone the supply chain relation to develop into system risk. In the paper the main structure and causal relationship of SCF credit risk system are analyzed. And then the intelligent analysis system model of SCF credit risk evolving mechanism is constructed based on systematic dynamic, which simulates how the key factors act to each other and how they function to SCF credit risk. The intelligent analysis results show that: (1) The sub-system of bank, core …enterprise, small-mid enterprise and risk intermediary interact and constitute the SCF credit risk system. (2) The credit risk management strategy execution and the management infrastructure input of the bank sub-system can promote improving the management base of core enterprise and small-mid enterprises. (3) To increase the management efficiency of core enterprise and small-mid enterprises can improve enterprises operating level and solvency, and then decrease the SCF credit risk. And also, the core enterprise influences the SMEs’ solvency by actively function to the operation ability. (4) The increasing of risk intermediary can accelerate to the SCF loan quantity, and at the same time, reduce the credit risk. Show more

Keywords: Supply chain finance, credit risk, systematic dynamic, evolving mechanism, intelligent analysis system

DOI: 10.3233/JIFS-179853

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

Authors: Malarvel, Muthukumaran | Nayak, Soumya Ranjan

Article Type: Research Article

Abstract: Edge detection and segmentation are the two main approaches being used since last three decades for successful image analysis in remote sensing domain. Although many intensive studies were undertaken, they all were limited to high-resolution aerial images and none addressed this problem exhaustively. The purpose of this study was to investigate both edge detection and segmentation by employing a novel hybrid method combining probability density function and partial differential equation to obtain accurate estimations. The newly proposed method is implemented in two phases: the first phase deals with smoothening that include improved kernel density estimation (KDE) with anisotropic diffusion coefficient …function kernel with both adaptive bandwidth and constant threshold selection using Shannon entropy, in addition to a weighting parameter of 3 × 3 window for lower probability of the whole image in diffusion function; whereas in the second phase, edge detection and segmentation are dealt with by incorporating two prominent techniques, namely diffusion coefficient equation and six-sigma control limit. We carried out a cross-sectional analysis using different datasets such as SIPI database and ground truth images for smoothing, edging and segmentation. Afterward, the results were compared with the other state-of-the-art techniques. Finally, the performance measures of the implemented technique were evaluated by means of entropy, fractal dimension, and an equivalent number of looks for smoothened images, by the Pratt metric for edge detection, and in the case of segmentation, misclassification error was considered. The experimental results demonstrated that the proposed scheme outperforms its counterparts in all aspects. Hence, the proposed hybrid scheme is better and robust, and results in accurate estimation for the given datasets. Show more

Keywords: Kernel density estimation, anisotropic diffusion, fractal dimension, aerial image, image smoothing, segmentation, edge detection

DOI: 10.3233/JIFS-191547

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

Authors: Sun, Baofeng | Zhang, Xinkang | Qiao, Hai | Li, Gendao | Chen, Yifei

Article Type: Research Article

Abstract: The efficient operation of Intelligent Warehousing System does not rely on individual resource scheduling in stages but multi-type resources collaborative scheduling. In this paper, a collaborative scheduling model for stackers, automated guided vehicles and picking workstations in outbound process is abstracted into a hybrid flow-shop scheduling problem within an automated warehouse scene. Considering the impacts of uncertain factors related to scheduling, the objective function of this model is minimizing the makespan based on the triangular fuzzy processing time. A genetic algorithm is designed to obtain feasible solution of this model with the form of vector coding and the approach of …ranking fuzzy numbers. Example analysis shows that the validity of the model and algorithm is verified. Within different resource allocation schemes, their evaluating indexes are significantly different, which are the likely completion time of system operation, the capability coordination degree and the initial investment. Furthermore, the increase of picking workstations is contributed much more to reducing the likely completion time and to improving the capability coordination degree than that of automated guided vehicles. Show more

Keywords: Automated warehouse, fuzzy processing time, collaborative scheduling, genetic algorithm, capability coordination degree

DOI: 10.3233/JIFS-191827

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

Authors: Nie, Xiangtian | Fan, Tianyu | Wang, Bo | Wu, Han

Article Type: Research Article

Abstract: To ensure that the safety risk indicator system of the south-to-north water diversion project is both scientific and independent, an indicator optimization method based on correlation and sensitivity analysis is proposed. The 3D grey correlation degree among the indicators is obtained by maximum deviation. At the same time, the principal component analysis method is adopted to calculate risk sensitivity based on the preliminary analysis on the risk indicators. The correlation degree reflects whether it is possible for the connotation overlapping between the risk indicators, and the sensitivity reflects the indicators’ influence on the system. The purpose of the research is …to optimize the risk system through removing the less sensitive one of the two relatively correlated indicators, and the calculation results prove the effectiveness and feasibility of the method. Show more

Keywords: Operational safety, correlation degree, sensitivity, maximum deviation, indicator optimization

DOI: 10.3233/JIFS-179848

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2020

Authors: Alkouri, Abd Ulzeez M. J. | Massa’deh, Morad Oqla | Ali, Mabruka

Article Type: Research Article

Abstract: Many factors with the perspective of bipolarity in the traditional Chinese food system “Yin and Yang food system” manipulate with types of food simultaneously to have a balanced body. This research studies the multiple attributes decision making (MADM) problem that measuring the “bipolarity of periodic” variation in bipolar information with an illustration example in order to find an optimal nutrition program for a person X . To convey this type of data to a mathematical formula and vice versa without losing the full meaning of human knowledge, we use bipolar fuzzy set in a complex geometry by extending the range …of bipolar fuzzy set to the realm of a complex number. This extension needs to be successful to study and introduce intensely a new mathematical structure called a bipolar complex fuzzy set (BCFS) with its properties. Ranges of values are extended to [0, 1] e iα [0,1]  and [-1, 0] e iα [-1,0] for both positive and negative membership functions, respectively, as a replacement for [-1, 0] × [0, 1] , as in the bipolar fuzzy set. The main benefit of BCFS that the amplitude and phase terms of BCFSs can convey bipolar fuzzy information. Moreover, the formal definition of BCF distance measure and illustration application are introduced. Some basic mathematical operations on BCFS are also proposed and study its properties with arithmetical examples. Show more

Keywords: Bipolar fuzzy set, bipolar complex fuzzy distance, bipolar fuzzy complement, union and intersection, fuzzy set, complex fuzzy set

DOI: 10.3233/JIFS-191350

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2020

Authors: Chung, Yao-Liang | Chung, Hung-Yuan | Tsai, Wei-Feng

Article Type: Research Article

Abstract: In the present study, we sought to enable instant tracking of the hand region as a region of interest (ROI) within the image range of a webcam, while also identifying specific hand gestures to facilitate the control of home appliances in smart homes or issuing of commands to human-computer interaction fields. To accomplish this objective, we first applied skin color detection and noise processing to remove unnecessary background information from the captured image, before applying background subtraction for detection of the ROI. Then, to prevent background objects or noise from influencing the ROI, we utilized the kernelized correlation filters (KCF) …algorithm to implement tracking of the detected ROI. Next, the size of the ROI image was resized to 100×120 and input into a deep convolutional neural network (CNN) to enable the identification of various hand gestures. In the present study, two deep CNN architectures modified from the AlexNet CNN and VGGNet CNN, respectively, were developed by substantially reducing the number of network parameters used and appropriately adjusting internal network configuration settings. Then, the tracking and recognition process described above was continuously repeated to achieve immediate effect, with the execution of the system continuing until the hand is removed from the camera range. The results indicated excellent performance by both of the proposed deep CNN architectures. In particular, the modified version of the VGGNet CNN achieved better performance with a recognition rate of 99.90% for the utilized training data set and a recognition rate of 95.61% for the utilized test data set, which indicate the good feasibility of the system for practical applications. Show more

Keywords: Deep CNN, gesture recognition, VGGNet, AlexNet

DOI: 10.3233/JIFS-200385

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