Journal of Intelligent & Fuzzy Systems - Volume 40, issue 4

Authors: Liu, Hsiao-Man | Huang, Chung-Chi | Huang, Chung-Lin | Ke, Yen-Ting

Article Type: Research Article

Abstract: This study proposes a health assessment and predictive assistance system for intelligent health monitoring. Through machine learning, the tool features a customized set of quantitative measurements and web analysis systems for physical and mental fitness. The system replaces the manpower and time requirements of the past necessary to conduct interviews and keep paper records, allowing users to observe and analyze physical and mental fitness status through the webpage. To achieve this, ECG, EEG, and EMAS are used to follow physiological, psychological, and meridian energy states. ASP.NET software is used as a development tool for the system cloud page, which constructs, …documents, evaluates, and predicts functions for the smart health assistance system. The measurement data is entered and recorded in the cloud database. The data is used to construct an assessment and prediction of the user’s state of mind and body through machine learning methods, as well as the individual’s physical and mental fitness. Show more

Keywords: Intelligent assessment, intelligent prediction, somatic fitness, healthcare, machine learning

DOI: 10.3233/JIFS-189618

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7957-7967, 2021

Authors: Huang, Chung-Lin | Huang, Chung-Chi

Article Type: Research Article

Abstract: Knowledge graphs are useful sources for various AI applications, however the basic paradigm to support pilot training is still unclear. In the paper, It is proposed to generate the customized knowledge graph of flight trainings using machine learning method for the flight training program. In order to provide the successful key to the further understanding of the learning problems between the students and the instructors. In this research, we collected data from an aeronautical academic in Taiwan that students were trained for Recreation Pilot License Program. We performed a test on 24 students at the first of each training course, …16 data of collected been used on building the module, 8 of them used to exam the module. There are 12 courses in the training program, and 30 hours total time were suggested by academic. The score which we applied on test were based on LCG method which is the sum of Maneuver and SRM Grades. For the indicators of course component in Learner Centered Grading, namely (a) CCS1: Operation & Effect of Controls; (b) CCS2: Straight & Level; (c) CCS3: Climbing & Descending; (d) CCS4: Turning; (e) CCS5: Stalling; (f) CCS6: Revision; (g) CCS7: Circuits; (h) CCS8: Cross-Wind Training; (i) CCS9: Circuit Emergency; (j) CCS10: Solo Circuit; (k) CCS11: Forced Landing; and (l) CCS12: Precautionary & Searching Landing. Through the method of Knowledge Graph, we deduct and predict the number of hours that need to be added for each student’s learning. Using the dynamic knowledge graph to display the key issues of the course learning continuously, and make follow-up decisions for the students, instructors and airliners. Show more

Keywords: Customized knowledge graph, FAA-industry training standards, machine learning

DOI: 10.3233/JIFS-189619

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7969-7979, 2021

Authors: Wen, Bor-Jiunn | Kao, Chia-Hung | Yeh, Che-Chih

Article Type: Research Article

Abstract: Labor force is gradually becoming insufficient owing to the aging population. The quality and safety of workforces are increasingly important, and thus, a set of intelligent wearable devices that assist the transport of loads by laborers, provide auxiliary standing support, and prevent falls were designed in this study. By applying an auxiliary force to the knee joint externally, an intelligent wearable device saves labor and reduces the burden on this joint, thereby protecting it. This study utilizes a Bayesian backpropagation algorithm for intelligent control. The intelligent wearable device provides the most suitable velocity and torsion depending on the initial driving …torsion of the user by a Bayesian backpropagation algorithm based on the current angle position, velocity, and torsion load of the device motor, thereby achieving an intelligent control effect of auxiliary standing support. A triaxial accelerometer is utilized to sense a fall and prevent it by a so-called fuzzy-Bayesian backpropagation control (FBC). Eventually, this study successfully designed and manufactured an intelligent wearable device by the FBC method. For a single motor control, two knee auxiliary devices can generate a torsion of 18.6 Nm. For dual motor control, two knee auxiliary devices can generate a torsion of 43.2 Nm. Thus, the laborers can not only perform their work efficiently and safely but also reduce costs and raise the working market competitiveness. Show more

Keywords: Intelligent wearable device, auxiliary stand, falling prevention, fuzzy-bayesian backpropagation control

DOI: 10.3233/JIFS-189620

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7981-7991, 2021

Authors: Pan, Nan | Shen, Xin | Guo, Xiaojue | Cao, Min | Pan, Dilin

Article Type: Research Article

Abstract: In recent years, electricity stealing has been repeatedly prohibited, and as the methods of stealing electricity have become more intelligent and concealed, it is growing increasingly difficult to extract high-dimensional data features of power consumption. In order to solve this problem, a correlation model of power-consumption data based on convolutional neural networks (CNN) is established. First, the original user signal is preprocessed to remove the noise. The user signal with a fixed signal length is then intercepted and the parallel class labelled. The segmented user signals and corresponding labels are input into the convolutional neural network for training, and the …trained convolutional neural network is then used to detect and classify the test user signals. Finally, the actual steal leak dataset is used to verify the effectiveness of this algorithm, which proves that the algorithm can effectively carry out anti–-electricity stealing by warning of abnormal power consumption behavior. There are lots of line traces on the surface of the broken ends which left in the cable cutting case crime scene along the high-speed railway in China. The line traces usually present nonlinear morphological features and has strong randomness. It is not very effective when using existing image-processing and three-dimensional scanning methods to do the trace comparison, therefore, a fast algorithm based on wavelet domain feature aiming at the nonlinear line traces is put forward to make fast trace analysis and infer the criminal tools. The proposed algorithm first applies wavelet decomposition to the 1-D signals which picked up by single point laser displacement sensor to partially reduce noises. After that, the dynamic time warping is employed to do trace feature similarity matching. Finally, using linear regression machine learning algorithm based on gradient descent method to do constant iteration. The experiment results of cutting line traces sample data comparison demonstrate the accuracy and reliability of the proposed algorithm. Show more

Keywords: Anti–electricity stealing, high-dimensional data features, convolutional neural network, early warning

DOI: 10.3233/JIFS-189621

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7993-7999, 2021

Authors: Jeong, Sang-Ki | Ji, Dea-Hyeong | Oh, Ji-Youn | Seo, Jung-Min | Choi, Hyeung-Sik

Article Type: Research Article

Abstract: In this study, to effectively control small unmanned surface vehicles (USVs) for marine research, characteristics of ocean current were learned using the long short-term memory (LSTM) model algorithm of a recurrent neural network (RNN), and ocean currents were predicted. Using the results, a study on the control of USVs was conducted. A control system model of a small USV equipped with two rear thrusters and a front thruster arranged horizontally was designed. The system was also designed to determine the output of the controller by predicting the speed of the following currents and utilizing this data as a system disturbance …by learning data from ocean currents using the LSTM algorithm of a RNN. To measure ocean currents on the sea when a small USV moves, the speed and direction of the ship’s movement were measured using speed, azimuth, and location (latitude and longitude) data from GPS. In addition, the movement speed of the fluid with flow velocity is measured using the installed flow velocity measurement sensor. Additionally, a control system was designed to control the movement of the USV using an artificial neural network-PID (ANN-PID) controller [12 ]. The ANN-PID controller can manage disturbances by adjusting the control gain. Based on these studies, the control results were analyzed, and the control algorithm was verified through a simulation of the applied control system [8, 9 ]. Show more

Keywords: USV (Unmanned surface vehicles), RNN (Recurrent neural network), LSTM (Long short-term memory models), ANN-PID (Artificial neural networks-PID)

DOI: 10.3233/JIFS-189622

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8001-8011, 2021

Authors: Choi, Hey-Min | Kim, Min-Kyu | Yang, Hyun

Article Type: Research Article

Abstract: Recently, abnormally high water temperature (AHWT) phenomena are occurring more often due to the global warming and its impact. These phenomena have damaged extensively to the maritime economy around the southern coast of Korea and caused an illness by exacerbating the propagation of Vibrio pathogens. To mitigate damages by AHWT phenomena, it is necessary to respond as quickly as possible or predict them in advance. In this study, therefore, we proposed a deep learning-based methodology to predict the occurrences of AHWT phenomena using the long short-term memory (LSTM) model. First, a LSTM model was trained using the satellite-derived water temperature …data over the past ten years. Then, the water temperatures after a few days were estimated using the trained LSTM model. In a performance evaluation, when estimating water temperatures after one-day, the model achieved results of 1.865 and 0.412 in terms of mean absolute percentage error (MAPE) and root mean square error (RMSE), respectively. Second, we developed a decision algorithm based on the Markov state transition in order to predict the AHWT occurrence probability. As a result, we obtained 0.88 of F1 score for predicting AHWT phenomena after 1 day in case of the southern coast of Korea. Show more

Keywords: Long short-term memory, deep learning, satellite data, abnormally high water temperature

DOI: 10.3233/JIFS-189623

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8013-8020, 2021

Authors: Phawinee, Suphawimon | Cai, Jing-Fang | Guo, Zhe-Yu | Zheng, Hao-Ze | Chen, Guan-Chen

Article Type: Research Article

Abstract: Internet of Things is considerably increasing the levels of convenience at homes. The smart door lock is an entry product for smart homes. This work used Raspberry Pi, because of its low cost, as the main control board to apply face recognition technology to a door lock. The installation of the control sensing module with the GPIO expansion function of Raspberry Pi also improved the antitheft mechanism of the door lock. For ease of use, a mobile application (hereafter, app) was developed for users to upload their face images for processing. The app sends the images to Firebase and then …the program downloads the images and captures the face as a training set. The face detection system was designed on the basis of machine learning and equipped with a Haar built-in OpenCV graphics recognition program. The system used four training methods: convolutional neural network, VGG-16, VGG-19, and ResNet50. After the training process, the program could recognize the user’s face to open the door lock. A prototype was constructed that could control the door lock and the antitheft system and stream real-time images from the camera to the app. Show more

Keywords: Face recognition, intelligent lock, ResNet, deep learning

DOI: 10.3233/JIFS-189624

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8021-8031, 2021

Authors: Wen, Yafeng

Article Type: Research Article

Abstract: With the promotion of BIM Technology, prefabricated building is developed rapidly in China. However, BIM technology has been only partially applied to prefabricated building, and there is still a gap between prefabricated building and intelligent construction. This paper focus on BIM 5D, together with relevant information technologies, all of which will be highly integrated and applied to prefabricated building, with the mission to get related information and enable the rapid flow of information, as well as bringing human perception, memory, knowledge and wisdom into prefabricated building, driving the development of prefabricated buildings to intelligence and leanness. Intelligent construction is …an innovated construction model based on the combination of latest information technology and engineering construction. Thus, it is particularly important to train personnel with corresponding knowledge structure, knowledge system and professional ability for intelligent construction. This paper also discusses about how to train personnel on prefabricated building and intelligent construction. Show more

Keywords: BIM5D, prefabricated building, intelligent construction, personnel training

DOI: 10.3233/JIFS-189625

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8033-8041, 2021

Authors: Hsieh, Wen-Hsiang | Chen, Yi-Syun | Wu, Shang-Teh

Article Type: Research Article

Abstract: Iterative Learning Control is a branch of intelligent control which combines artificial intelligence and control theory. This objective of this study aims at reducing the cyclic error of an inverse ball screw transmission system by using iterative learning control approach. Firstly, kinematic and dynamic analyses are conducted by using the vectorial loop closure and Lagrange equations, respectively. Then, system identification is performed followed by controller design. Moreover, controller parameters are optimized to minimize the error. Finally, the feasibility and the effectiveness of the proposed approach are verified by computer simulation and prototype experiment. The experimental results showed that the reducing …percentage of the square error sum of the output speed is 90.64% by using PID control only. If ILC is applied additionally, the error is further reduced to 94.21%. Therefore, the proposed approach is not only feasible and but also effective. Show more

Keywords: Ball screw, ILC controller, PID controller, Oldham coupling

DOI: 10.3233/JIFS-189627

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8043-8052, 2021

Authors: Lai, Yi-Horng

Article Type: Research Article

Abstract: OBJECTIVES: Efavirenz therapy plays an important role in controlling the progression of HIV/AIDS. However, efavirenz often causes short-term side effects for the central nervous system, and it remained controversial as to whether efavirenz leads to depression or even suicidal attempt when applied for a longer period of time. The purpose of this study is to determine the association between the use of efavirenz and depressive disorders. METHODS: This study explored the use of efavirenz on HIV-infected patients using National Health Insurance Research Database (NHIRD) in Taiwan by Bayesian survival analysis and investigated whether the use of efavirenz has …the risk of depressive disorders. To reduce the dependence of statistical modeling assumptions, this study applied propensity score matching to research data. RESULTS: Based on the result of this study, it can be found that the use of efavirenz (HR = 1.009, 95% CI=–0.505 0.554), gender (HR = 0.324, 95% CI = –2.544 0.381) were not significantly associated with the occurrence of depressive disorders, whereas age of HIV diagnosis (HR = 1.021, 95% CI = 0.011 0.055) was significantly associated with the occurrence of depressive disorders. This study concludes that the use of efavirenz does not in-crease the risk of depressive disorders among HIV-treated patients. CONCLUSIONS: For the care of HIV-infected patients (especially the older ones), the psychological harm from society, such as lack of social support, social stigma or unemployment is higher than the harm of medicine. Show more

Keywords: Human immunodeficiency virus (HIV), active antiretroviral therapy, depressive disorder, propensity score matching, Bayesian cox regression

DOI: 10.3233/JIFS-189628

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8053-8062, 2021

Authors: Lee, Chien-Cheng | Gao, Zhongjian | Huang, Xiu-Chi

Article Type: Research Article

Abstract: This paper proposes a Wi-Fi-based indoor human detection system using a deep convolutional neural network. The system detects different human states in various situations, including different environments and propagation paths. The main improvements proposed by the system is that there is no cameras overhead and no sensors are mounted. This system captures useful amplitude information from the channel state information and converts this information into an image-like two-dimensional matrix. Next, the two-dimensional matrix is used as an input to a deep convolutional neural network (CNN) to distinguish human states. In this work, a deep residual network (ResNet) architecture is used …to perform human state classification with hierarchical topological feature extraction. Several combinations of datasets for different environments and propagation paths are used in this study. ResNet’s powerful inference simplifies feature extraction and improves the accuracy of human state classification. The experimental results show that the fine-tuned ResNet-18 model has good performance in indoor human detection, including people not present, people still, and people moving. Compared with traditional machine learning using handcrafted features, this method is simple and effective. Show more

Keywords: Human movement detection, Wi-Fi, CNN, ResNet, channel state information

DOI: 10.3233/JIFS-189629

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8063-8072, 2021

Authors: Chou, Hsi-Chiang | Han, Kai-Yu

Article Type: Research Article

Abstract: This study developed a smart cane with remote electrocardiogram (ECG) and fall detection. The cane comprises a self-developed ECG detection circuit, fall detection module composed of a three-axis gyroscope and three-axis accelerator, and two wireless transmission modules. The data reception end features a human–machine interface with self-developed ECG analysis and fall detection programs, providing reference data for identifying an abnormal situation. The hardware of the proposed system is divided into two parts. First, ECG detection is achieved using a copper column-shaped detector in place of conventional ECG electrodes. The self-developed sensor circuit amplifies the collected signals and filters unwanted noise …to generate complete ECG signals. An Arduino MEGA microcontroller board and the two wireless transmission modules then transmit the signals to the human–machine interface. Second, fall detection is achieved using the aforementioned fall detection module to collect numerical data, which are then transmitted to the human–machine interface through the Arduino MEGA and wireless transmission modules. The proposed system can be applied to real-time monitoring and provide reference data for health care professionals and nursing personnel. Show more

Keywords: Electrocardiogram, fall detection, wireless transmission, human–machine interface

DOI: 10.3233/JIFS-189630

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8073-8086, 2021

Article Type: Other

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8087-8087, 2021

Authors: Sanjuán Martínez, Oscar | Fenza, Giuseppe | Gonzalez Crespo, Ruben

Article Type: Editorial

DOI: 10.3233/JIFS-189631

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8089-8090, 2021

Authors: Chen, Zhongshan | Zhang, Shengwei | Zhang, Juxiao | Hu, Zuojin | Han, Xue | Xu, Mengyang

Article Type: Research Article

Abstract: Artificial Intelligence (AI) is the enhancement and method of computer system that handles tasks which requires human like intelligence such as recognition, language translation and visual interpretation. Subjective image quality assessment (IQA) is difficult to be implemented in real-time systems, methodology for enhancing the involvement in producing IQA model is to improve the quality of image by significant evaluation. Intuitively, human eyes are not sensitive to the distortion and damage from the area with lesser visual saliency (VS), VS is closely related to IQA. With this consideration, an effective IQA was proposed, which involved two processes. The local quality map …of a distorted image was computed using the structural similarity function of its feature attributes, such as brightness, chrominance and gradient. Second, the local quality map was weighted with visual saliency (VS) to get the objective evaluation of image quality. The VS was modeled by extracting the saliency of low-level features of the image, wiping off the molestation information from these saliency based on an apriori threshold, and combining the effective information to construct the saliency map. Image processing using fuzzy is gathering features and segments as fuzzy set while processing images. The experiments on the two largest database for six classical IQA metrics demonstrate that performance of weighted-VS IQA metrics is superior to the performance of no weighted-VS IQA metrics, and the proposed IQA method has higher computational accuracy than the other IQA metrics under a moderate computational complexity, especially for two types of distortion images, such as local block-wise (Block) and fast-fading (FTF). Show more

Keywords: Image quality assessment (IQA), brightness distortion, chrome distortion, gradient distortion, visual saliency (VS), structural similarity, artificial intelligence (AI), fuzzy set

DOI: 10.3233/JIFS-189632

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8091-8100, 2021

Authors: Zhou, Wei

Article Type: Research Article

Abstract: Decentralized application (DAPP), replacing traditional business logic and data access layer with block chain, is a new form of Internet service. Testing DAPP requires large-scale distributed systems. Performing experiments in a real system is costly and difficult. This article carefully analyses the process of block generation and synchronization and explains the reasons for the low efficiency of block chain system simulation. We incorporate fuzzy rule based model for enhancing the logging system in blockchain. Rules based on fuzzy are utilized inside system of fuzzy logic to obtain outcome on basis of input variables. The data of Ethereum and Bitcoin proves …that the block generation interval conforms to the exponential distribution, and the real PoW calculation can be replaced with random numbers. Both block verification and network propagation processes have latency, which can be simulated with asynchronous messaging. Based on the above analysis, this article proposes a high-performance simulation method based on event-driven model, which is suitable for describing the communication and synchronization behave our of block chain networks. The method can effectively describe the block generation, the synchronization process between nodes, and supports different equity proof forms. Using this method, the performance of the PoW systemis tested. Under the ecs.c6.xlargeinstance,the simulation running speed reaches 782 times of actual system. Further experiments show that this method can be efficiently used in larger-scale networks and is an effective tool for DAPP developing and testing. Show more

Keywords: Decentralized applications, blockchain, complex network, distributed system, artificial intelligence, fuzzy logic, fuzzy rule

DOI: 10.3233/JIFS-189633

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8101-8107, 2021

Authors: Ma, Yanran | Cai, Jianfeng | Wang, Yiqi | Farooq Sahibzada, Umar

Article Type: Research Article

Abstract: Based on information asymmetry, agency theory and resource-based view (RBV), this study investigates the impact of venture capital (VC) on venture firm innovation performance, ascertains the extent to which VC affects venture firm innovation performance and finds the mediating effect of management incentives. Constructing a sample of a novel panel dataset of firms listed on the SME Board of China, we examined a sample of 927 start-ups between 2008 and 2017, showing a notable negative relationship between VC and Patent, and a positive relationship between VC and total factor productivity (TFP), providing stable evidence that VC could not spur firm …patent directly, but facilitate the commercialization of innovation. Moreover, it shows that management equity incentives (MEI) and management cash incentives (MCI) playing significant positive mediating role between VC and TFP, while there is no mediating effect between VC and Patent. Findings of this study strengthen the experience of VC and suggest how practitioners of SMEs to enhance the commercialization of innovation, considerably extends our understanding of the impact of VC on venture firm innovation performance. Show more

Keywords: Venture capital (VC), management incentives (MI) , innovation, patent, total factor productivity (TFP)

DOI: 10.3233/JIFS-189634

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8109-8115, 2021

Authors: Wang, Qian | Wang, Jianxu | Li, Hua | Li, Xiang

Article Type: Research Article

Abstract: Equipment manufacturing industry is the core industry of national economy. The development of artificial intelligence technology provides new development opportunities for the transformation and upgrading of equipment manufacturing industry, but in this process, China’s equipment manufacturing enterprises are faced with serious financing constraints and financing efficiency needs to be improved. Based on the panel data of Listed Companies in equipment manufacturing industry from 2009 to 2018, the article constructs a panel data regression model by using stochastic frontier analysis to measure the financing efficiency of equipment manufacturing industry and study its influencing factors. The results show that the average financing …efficiency of China’s equipment manufacturing enterprises is in the medium level, while the traditional equipment manufacturing industry is lower; external financing has a positive impact on the financing efficiency of enterprises, and labor input has a negative impact; in the analysis of influencing factors, the Capital structure, R&D investment, Accounts receivable turnover rate, Fixed assets turnover rate have a great impact on the financing efficiency. The research results have a certain reference significance for equipment manufacturing enterprises to improve financing efficiency. Show more

Keywords: Equipment manufacturing, financing efficiency, stochastic frontier analysis

DOI: 10.3233/JIFS-189635

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8117-8126, 2021

Authors: Bin, Guo | Liang, Ge

Article Type: Research Article

Abstract: Public-Private Partnership (PPP) model is an important measure for transferring government functions and promoting socialist market economy in China. After four years of high-speed development and standardized development in recent years, PPP model has achieved good effect in our country. However, multiple problems emerged. In China, the “public” party of the model has always been dominated by state-owned enterprises. Although private enterprises have the willingness to participate, the actual participation degree and volume are not high which is not good for the sustainable development of the PPP model. This paper applied grounded theory to carry out in-depth interviews with the …representatives from government, private enterprise, and SPV company in some key PPP projects with private participation, propose four coral categories to construct the whole process of private enterprises’ participation and summarize the behavioral features, and explore private enterprises’ realization of their participation willingness into actual participation behavior and the generation of their continuous participation willingness so as to clear the private enterprises’ participation path in PPP projects. Show more

Keywords: PPP model, grounded theory, Artificial Intelligence (AI), private enterprises, participation behavior

DOI: 10.3233/JIFS-189636

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8127-8137, 2021

Authors: Chen, Peng | Nie, Yingzhi

Article Type: Research Article

Abstract: Based on the company cases published in China over the past ten years, both theoretical methods and Artificial intelligence technologies were applied to analysis cases data on the effectiveness of clauses restricting equity transfer in articles of association of limited liability companies (LLCs). With its unique characters based on shareholders and strong vitality, limited liability company (LLC), as the “evergreen tree” among the market players, is a company form adopted by many investors. Nevertheless, due to its prominent closed characteristics, equity transfer has become a bottleneck for the development of LLCs. According to this paper, it is necessary to distinguish …between the effectiveness of clauses restricting internal and external equity transfer in articles of association of LLCs. Fuzzy Analytic Hierarchical Process (AHP) is utilized for which involves process of analytic hierarchy modelled with utilizing theory of fuzzy logic. Moreover, instead of being confined to the existing legal norms, the judgment standard of clauses restricting equity transfer in articles of association of LLCs should be comprehensively measured by the golden rules, i.e. “fairness”, “autonomy” and “operability”. Show more

Keywords: Characters based on shareholders, nature of articles of association, effectiveness of clauses, judgment standard, fuzzy logic, fuzzy Analytic Hierarchical Process (AHP)

DOI: 10.3233/JIFS-189637

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8139-8150, 2021

Authors: Gu, Xungang | Li, Gang | Cao, Shengli | Zhang, Yumeng | Wang, Ran

Article Type: Research Article

Abstract: The reasonable cost budget of the e-government scheme can effectively promote the construction of the digital government. To analyze the cost impact components of the e-government system and find out the impact factor model works in China, this paper reviews relevant literature on software cost impact factors and proposes the impact factors model based on COCOMO II. Besides, combined with the actual construction of digital government and specific cases, this paper analyzes the mechanism of each impact factor in detail. The model can be used to guide the cost estimation of e-government software in China, especially with artificial intelligence estimation …method. An enhanced decision theory of theory based on fuzzy set has been adopted for analysis of cost factor on E-government software cost. Show more

Keywords: E-government, information system, software cost estimation, impact factors, fuzzy set

DOI: 10.3233/JIFS-189638

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8151-8161, 2021

Authors: Deng, Guangzhe | Fu, Yingkai

Article Type: Research Article

Abstract: As the stability of surrounding rock of coal roadway is affected by many factors, which makes the classification result hard to be consistent with the field practice. To solve the above problems, this paper proposes a method for the classification of stability of rock which is present in roadway of coal using the artificial intelligence algorithm. In this paper, the influencing factors of stability of rock which is present in roadway are analyzed, and seven influential factors are selected as classification indexes. To solve the problem of slow convergence speed and easy to fall into the local minimum of the …back propagation artificial neural network (BP-ANN), an improved BP-ANN algorithm based on additional momentum and Levenberg-Marquardt optimization is proposed based on the analysis of the existing improved methods, which improves the convergence speed and avoids the local minimum effectively. Based on the learning model available, classification system based on fuzzy rule have been implemented and yielded better behavior in the situation of uncertain data sets. Finally, the stability classification model of surrounding rocks of coal roadway using BP-ANN was established in MATLAB environment, and the model was applied to 13 data samples of coal roadway for testing, with the identification rate of 92.3%. The experimental results verify that the method proposed based on fuzzy rule classification system in this paper has a high accuracy of type identification and is applicable to the stability classification of surrounding rock in the coal roadway. Show more

Keywords: Coal roadway, surrounding rock, artificial intelligence, BP-ANN, fuzzy rule, classification system

DOI: 10.3233/JIFS-189639

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8163-8171, 2021

Authors: Wang, Xi | Chen, Qinyi | Wang, Jingyi

Article Type: Research Article

Abstract: The lightening system inside the residential or commercial building consumes the highest electrical power. For an energy efficient smart city development, some sustainable and low power consumption methods need to be explored. In this direction, we proposed solar energy based auto-intelligent LED light controlling system that uses wireless sensor network (WSN) with computation and control model for LED on/off and dimming of LED lights inside the building area. The WSN is employed with some sensor devices that sense and gather ambient context information which is transmitted to computation model. LEDs get power supply from photovoltaic solar panel systems that have …inbuilt battery banks. Fuzzy rough set is a simplification of a rough set, obtained from the normalization of fuzzy set in a approximation of crisp value. Fuzzy is utilized for analyzing the energy consumed in the system additionally. Performance evaluation of proposed Auto-intelligent LED system is carried out based on the comparative analysis of energy consumption of ac-grid system with solar energy based dc-grid system. Result analysis shows that proposed system saves 78% of energy consumption as compared to the traditional AC power grid system. The proposed DC power grid system presents 3% of voltage drop and maximum power loss of 1.25%. The statistics of battery charger and LED drives are also represented experimentally. Show more

Keywords: Energy efficient, wireless sensor networks, power consumption, artificial intelligence (AI), smart grid, fuzzy rough set

DOI: 10.3233/JIFS-189640

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8173-8183, 2021

Authors: Zhou, Zaohong | Zou, Yongwen

Article Type: Research Article

Abstract: Problems involving decision-making and management of engineering projects call for attention from different quarters and the issue of decision-making for projects under the state planning in particular should be the major concern of project management. This study takes a traditional village protection project —- the preservation of Zaoshi Village, Xingan County, Jiangxi Province, China—- as a case in point. Treating the decision-making process as a system, the study employs ISM model to examine the system-level relationship between engineering projects. Artificial Intelligence is utilized for analyzing the planning of project structure and Fuzzy TOPSIS model is useful in estimating the weights …of the scenario and find the ranking of structure finally. Then, using the analytical data thus derived, the research focuses on identifying the optimum option for decision-making. By this process, the study intends to gain and share some insight into the issue and establish precedents for similar engineering projects. Show more

Keywords: Planning engineering, Artificial Intelligence (AI), ISM, Grey situation decision-making, Fuzzy TOPSIS

DOI: 10.3233/JIFS-189641

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8185-8195, 2021

Authors: Yu, Guo | Li, Weijian | Zhou, Xiaobo

Article Type: Research Article

Abstract: The Belt and Road (abbreviated as B&R) creates opportunities for the economy and trade development and the improvement of national relations of the Belt and Road countries. Development of service trade plays an important role in the Belt and Road. Henan Province takes the opportunity of B&R to develop the international service industry and makes some achievements. In the new era of development, analyzing the trade competitiveness of international service in Henan Province under the background of the Belt and Road is of great significance to help Henan Province recognize its own strengths and weaknesses in service trade development and …make targeted improvements. Studies have shown that the share of international market, revealed, advantages of comparative competitiveness trade and service trade openness of service trade in Henan Province under the background of the Belt and Road are constantly improving, but the overall development level is still low and slow development occurs. We utilize the concept of fuzzy embedded along with Analytic Network Process (ANP) which makes it suitable for managing vagueness of the linguistics information of assessment system. Therefore, in order to further improve the international competitiveness of service trade in Henan Province, it is necessary to optimize the international market share, competitiveness, and degree of openness. Specifically, it is necessary to transform and upgrade the traditional service trade industry, continue to expand the breadth and depth of service trade openness, strengthen the talent team building to improve the quality of employees, and promote the brand construction of service industry to enhance the industry’s development potential. Show more

Keywords: The belt and road, henan province, service trade, international competitiveness, fuzzy, analytic network process (ANP)

DOI: 10.3233/JIFS-189642

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8197-8206, 2021

Authors: Jing, Wu | Jie, Tian

Article Type: Research Article

Abstract: China remains one among largest agricultural countries in the world and one of the fastest growing Internet countries in the world. The further thorough and penetration of the Internet into the rural hinterland indicates that the combination of the Internet and the rural areas already has the technical foundation. The transformation of rural economy with Internet as medium is the future direction of rural development. Starting from the current situation of rural Internet development, based on the annotation of “Internet plus”, this paper explores the theoretical and practical application of rural e-commerce development. We utilize Intuitionistic Fuzzy Sets operator for …modelling multiple attribute issues related to decision making to estimate influence of e-commerce in industries. This paper puts forward the measure method of industrial transformation and proves that “Internet plus” e-commerce has exerted a great influence on the commercial civilization, industrial structure and economic structure transformation of rural areas. The steady and lasting impact of this continuous release may become a new paradigm of technological economy. It is of great significance to the formation of the “four modernizing” linkage mechanism with information as media and the innovation of the conventional path of rural economic development and the rapid growth of rural economy. Show more

Keywords: Rural e-commerce, industrial structure, transformation, artificial intelligence (AI), “Internet plus”, fuzzy sets

DOI: 10.3233/JIFS-189643

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8207-8215, 2021

Authors: Wang, Xiaodong | Wang, Xiaoming | Wu, Junfeng | Zheng, Kai | Pang, Yanhong | Gang, Song

Article Type: Research Article

Abstract: For the weak part of the quality traceability ability of cigarette logistics and products, this paper proposes a quality traceability method which integrates PDCA quality cycle with information strategy. This method firstly establishes the quality cycle process of cigarette logistics through PDCA quality cycle process, and then constructs IS-PDCA process based on information strategy (IS) to analyze the quality traceability process of cigarette products. The key links are determined according to the traceability process of cigarette logistics, and the traceability resource scheduling function is determined through the product. Then, according to the determined scheduling function and RFID technology, the optimal …allocation strategy is constructed to complete the feature extraction and classification identification of cigarette quality labels. For assessing the quality of cigarette evaluation, classification based on fuzzy is proposed and artificial neural network are utilized for calculating the grade of cigarette. Finally, a process of cigarette quality traceability combining PDCA quality cycle and information strategy is formed, and the quality traceability results are constructed by means of QR code technology, so as to realize the process system of cigarette quality traceability and improve the quality control ability of cigarettes. The simulation results show that the cigarette quality traceability method constructed in this paper can obtain the cigarette quality control with good adaptive performance, and the control process shows a strong ability, which improves the feasibility and effectiveness of the cigarette quality traceability. Show more

Keywords: Information strategy, Artificial Intelligence (AI), PDCA quality cycle, cigarette logistics, quality traceability, fuzzy, artificial neural network

DOI: 10.3233/JIFS-189644

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8217-8226, 2021

Authors: Luo, Xiaolin

Article Type: Research Article

Abstract: Along with improvement of technology in network and continuous expansion of network economy and network applications, the Internet has gradually become an indispensable part of the modern society. However, an endless stream of hacker attacks and network virus events make network security issues stand out. Therefore, network security has become a hot spot in computer network research and development. This paper aims at establishing a real-time detection and dynamic defense security system and makes an in-depth study of intrusion detection technology and defense decision-making technology. The strategy involved in finding the intrusion behavior since the fuzzy base contains the better …group of rules. We have utilized an automated fuzzy rule generation strategy. An adaptive network intrusion detection and defense system model is established, and the architecture of the model is discussed in detail. The platform independence, good self-adaptability, expansibility, multi-level data analysis and dynamic defense decision-making are expounded. The experiment proves that the model proposed in this article has a good self-adaptability and open construction, and effectively combines the functions of intrusion detection and defense decision-making. Show more

Keywords: Artificial intelligence, adaptive network, defense system, fuzzy rule

DOI: 10.3233/JIFS-189645

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8227-8235, 2021

Authors: Jiang, Sai

Article Type: Research Article

Abstract: With the rapid development of artificial intelligence and big data technology, the traditional audit method has been constantly impacted by big data. In the era of big data, enterprises actively explore and build a financial sharing service model, and through this model, build audit methods based on big data. In this paper, based on the financial sharing service model, we elaborate the preprocessing process of big data collection, clarity and storage, and build the simulation process framework of big data audit under the service model. Evaluation model is developed based on fuzzy analytic hierarchy process (AHP) and methodology for order …estimation by similarity of solution. Finally, on the basis of the implementation process framework, the specific content of each link of big data audit is briefly given. Under the financial sharing service mode, it provides theoretical guidance and practical significance for the implementation of big data audit Show more

Keywords: Financial sharing services, artificial intelligence (AI), big data audit, data processing, process framework, fuzzy analytic hierarchy

DOI: 10.3233/JIFS-189646

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8237-8246, 2021

Authors: Tao, Zou | Si Jun, Bai | Xi Bai, Rong

Article Type: Research Article

Abstract: The rapid development of cloud computing, big data, AI, BI and other information technologies has accelerated the process of enterprise modernization and informatization. The combination of computer technology and management science promoted the formation of modern enterprise management technology. Especially in today’s era of big data, in the face of massive data, how to quickly and accurately find out the required information, analyze the memory relation of data, find out the inherent business law hidden under massive information, and provide an important reference for enterprises to make business decisions and seek for market opportunities. A methodology that exhibits fuzzy TOPSIS …model has been incorporated in this study. Fuzzy weights and fuzzy judgment about the management systems have employed to estimate the scores of evaluation. In order to solve this problem, this paper integrates independent ERP and BI, and studies and develops a marketing management system by using advanced technologies such as data warehouse, online analysis and data mining; The system extracts useful data from ERP data sources, and analyzes the internal rules and statistical results that can be used to guide the enterprise’s actions, so as to effectively improve the enterprise’s competitiveness. Show more

Keywords: ERP, artificial intelligence (AI), data mining, marketing management, computer technology, fuzzy TOPSIS, fuzzy weights, fuzzy judgment

DOI: 10.3233/JIFS-189647

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8247-8255, 2021

Authors: Gang, Song | Xiaoming, Wang | Junfeng, Wu | Shufang, Li | Zhuowen, Liu | Wang, Xiaodong

Article Type: Research Article

Abstract: In view of the production quality management of filter rods in the manufacturing and execution process of cigarette enterprises, this paper analyzes the necessity of implementing the manufacturing execution system (MES) in the production process of filter rods. In this paper, the filter rod quality system of cigarette enterprise based on MES is fully studied, and the constructive information management system demand analysis, cigarette quality control process, system function module design, implementation and test effect are given. This paper utilizes the Fuzzy analytic hierarchy process to find the optimal system for processing the manufacturing of cigarette. The implementation of MSE …based filter rod quality information management system for a cigarette enterprise ensures the quality control in the cigarette production process. Through visualization, real-time and dynamic way, the information management of cigarette production is completed, which greatly improves the quality of cigarette enterprise manufacturing process. Show more

Keywords: AI, cigarette, filter rod, quality management, information management system, Fuzzy

DOI: 10.3233/JIFS-189648

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8257-8267, 2021

Authors: Tan, Chengfang | Cui, Lin | Wu, Xiaoyin

Article Type: Research Article

Abstract: With the rapid development of mobile terminal devices, mobile user activities can be carried out anytime and anywhere through various mobile terminals. The current research on mobile communication network is mainly focused on extracting useful and interesting information for mobile user from massive and disordered information. However, the sparsity of scoring data matrix results in low quality of recommendation algorithm. In order to overcome this drawback, the traditional collaborative filtering algorithm is improved. First, the user-interest matrix and item-feature matrix were obtained by analyzing mobile user behavior and item attributes. Fuzzy trust based model is utilized for collaborative filtering analysis …for mobile user preferences. Then, the similarity between different mobile users was calculated by weighted calculation. With this method, mobile user preference can be predicted effectively, making it possible to recommend rational resource and waste less time in extracting resources out of the massive information. Experimental results show that the proposed algorithm reduces the mean absolute error (MAE) and the impact of sparse scoring matrix data compared with the traditional collaborative filtering algorithm, and improves the recommendation effect to a certain extent. Show more

Keywords: Collaborative filtering, AI, mobile user, user interest, similarity calculation, fuzzy trust

DOI: 10.3233/JIFS-189649

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8269-8275, 2021

Authors: Wang, Qian | Zhang, Bo

Article Type: Research Article

Abstract: Hotel industry, as the pillar industry of the tertiary industry, is developing at a rapid pace under the background of rapid economic growth and strong support for the tourism industry. At the same time, it also faces fierce competition at home and abroad. In the information age, more and more hotels choose informationalized management, in order to reflect the competitive advantage of the enterprise with better services, higher efficiency and lower costs. The current hotel management system has been widely used in all aspects of hotel management, integrating reception, backstage financial processing and material procurement functions in one, which basically …meets the needs of the daily management of the hotel. With the advancement of the hotel information process, hotel business data also shows explosive growth. However, these data have not been effectively developed and used. This research proposes Fuzzy based Analytic Hierarchical Process (FAHP), which is utilized for considering user perception to access the making of decision. The business data processing of the management of hotels is limited to simple collection, storage, and statistics. The information obtained is superficial and regular, which cannot meet the current “customer-centered” marketing strategy of the hotel. This topic is based on the conventional hotel management system, using data mining technology to extract useful information from the existing hotel business data to establish customer segmentation model and support the decision layer to analyze the data from multi-angle and multi-level around the decision-making topic, so as to truly realize the “customer-centered” concept, improve hotel service level and improve the core competitiveness of enterprises. Show more

Keywords: Data mining, CRM, hotel management system, customer, AI, fuzzy based analytic hierarchical process (FAHP)

DOI: 10.3233/JIFS-189650

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8277-8285, 2021

Authors: Lifang, Guo | Yuwen, Cui | Yamin, Wu | Jiaqi, Ma

Article Type: Research Article

Abstract: The innovation and development of manufacturing supply chain alliance is an important way for enterprises to meet the increasing market demand and maintain the competitive advantage. From the perspective of embeddedness, the research model of relation embeddedness on innovation performance of manufacturing supply chain was constructed based on AMOS. Shared mental model was selected as intermediary variable to study the influence of relation embeddedness, shared mental model and innovation performance of manufacturing supply chain alliances. Expert fuzzy rule based system is utilized for measuring the performance of manufacturing supply chain alliances. The conclusion shows that relation embeddedness is significantly positive …shared mental model and innovation performance. Shared mental model is positively affects alliance innovation performance and plays a part of intermediary role between relational embedding and alliance innovation performance. Practice implicates that enhance the level of relation embeddedness can promote the formation of shared mental model and improve the innovation performance of manufacturing supply chain alliance. Show more

Keywords: Artificial Intelligence (AI), relation embeddedness, shared mental model, innovation performance, structure equations, fuzzy rule

DOI: 10.3233/JIFS-189651

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8287-8294, 2021

Authors: Lan, Chongfeng

Article Type: Research Article

Abstract: Considering the ubiquity of consumer balking behavior (CBB) in real-life economics and the importance of product quality control (QC) to supply chain (SC) competitiveness, this paper explores the SC coordination under both the QC and the CBB. Specifically, the consumer’s loss aversion behavior was illustrated at a fixed balking probability, and the SC models were created for centralized and decentralized decision-making modes. After that, the optimal strategies for the retailer and the manufacturer were identified, and the comparative static analysis was adopted to explore the effects of the CBB and QC on the optimal decision-making of the SC. The research …results show that the QC-based SC under the CBB cannot be coordinated by wholesale price contract alone, but can be coordinated perfectly by this contract when the retailer shares the quality effort and the manufacturer shares the oversupply cost and analyzed through the fuzzy environment with the formulation. This finding sheds new light on the theory and application of wholesale price contract in SC coordination. Finally, the parameter sensitivity analysis was performed on balking probability and product qualification rate (PQR) through numerical experiments, which further discloses the impacts of the CBB and product QC on the optimal decision-making and profit of the SC. Show more

Keywords: Quality control (QC), fuzzy formulation, consumer balking behavior (CBB), supply chain (SC), cost sharing, coordination

DOI: 10.3233/JIFS-189652

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8295-8305, 2021

Authors: Jia, Yufang

Article Type: Research Article

Abstract: China’s tourism industry has made remarkable achievements since reframing and beginning, but the imbalanced expansion of regional tourism has become increasingly severe. This paper involves the analysis of combining index analysis and factor analysis and employs SPSS software to make a quantitative analysis on the differences and the contributory factors of the tourism economy in Yangtze River Delta in China from 2006 to 2016. The results have demonstrated that there exists an imbalance in the development of tourism economy in the Yangtze River Delta, and that there is a significant spatial difference with a yearly trend of decrease. Besides, a …major gap lies among the comprehensive development level of tourism economy of the cities in the Yangtze River Delta. In this paper, Fuzzy analytic hierarchy process is used for making decision based analysis process for tourism economy. The comprehensive development level of tourism economy in Shanghai, Suzhou and Nanjing is much higher than that in other cities. Tourism resources endowment, tourism reception facilities and the development level of regional economy are important contributory factors of the regional differences of economy based on tourism in river delta of Yangtze, and there exists an extremely obvious positive correlation. Show more

Keywords: Tourism economy, Yangtze River Delta Region, Regional differences, Contributory factors, Fuzzy

DOI: 10.3233/JIFS-189653

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8307-8315, 2021

Authors: Chen, Shu | Xiang, Lei | Jin, Lianghai

Article Type: Research Article

Abstract: Public-Private Partnership (PPP) has been adopted extensively in public infrastructures in China. Numerous studies have explored development patterns for future PPP projects success based on either literature review or case studies. This paper aims to probe into the spatiotemporal dynamics of China’s PPP and clarify regional differentiation by frequency analysis, coefficient of variation and cluster analysis. The result shows that the implementation rate has a slight increase along with time series although PPP projects gradually return to rational development. The fuzzy set is utilized to handle with ambiguity in some linguistic risk allocation criteria to lower the fuzziness and bias …in knowledge expert which is qualitative that handles real time decision making. The municipal sector has been occupied the largest share of PPP projects while state-owned enterprises still dominate the biggest PPP marketed components. Local governments prefer viability gap subsidies although central government encourages user payment. Spatial difference coefficient is so high reflecting obvious regional differentiation of provincial PPP development. Recommendations are ultimately put forward to enhance China’s future PPP promotion, which will provide a valuable direction for government to make PPP customized policies. Show more

Keywords: Public-private partnership, development characteristics, regional differentiation, statistical analysis, China, fuzzy set

DOI: 10.3233/JIFS-189654

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8317-8331, 2021

Authors: Xu, Xinpeng | Li, Xun | Gao, Fuxia

Article Type: Research Article

Abstract: The “Belt and Road” initiative (BRI) enhances the cooperation between China and countries in Central and Eastern Europe (CEE), and expands the scale of China-invested enterprises in CEE countries continuously. But it also results in the increase in investment risks. Meanwhile, large differences between the international labor market and the domestic employment environment have led to the inadaptability of some enterprises’ overseas employment policies, triggering many labor disputes, and producing adverse effects on their overseas business expansion. To resolve the problems, this paper attempts to study the measures to prevent labor employment risks using fuzzy inference system for China-invested enterprises …in CEE. For this, it performs analysis for the scale, structure, labor quality, wages and benefits, and labor law system of labor employment in CEE countries, and proposes to prevent and resolve the labor employment risks by strengthening government labor cooperation, familiarizing with local labor law systems, and respecting local management culture etc. Show more

Keywords: Belt and road initiative, investment, Central and Eastern Europe, labor employment risk, prevention, fuzzy Inference system

DOI: 10.3233/JIFS-189655

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8333-8344, 2021

Authors: Yan, Chunxiao | Huang, Ziyue

Article Type: Research Article

Abstract: This paper relates the illustration of policy related to monetary announcement on various international commodity price and explore the similarities and differences of the effect in QE1, QE2, QE3, exit stage and interest hike stage through event study method and the whole sample VAR model and rolling sample VAR model. Results show that: (1) the implementation of unconventional monetary policy has a significant positive effect on the international commodity market, while the exit plan and the interest rate increase policy have some negative effects on the commodity markets, but the effects are not significant. (2) In terms of the VAR …whole samples, it can be seen that unconventional policies of monetary simulated by reserve of federal have an importance in impact on international commodity prices. This paper developed a approach of fuzzy binomial that can be utilized in various projects using commodity prices using uncertainty. In terms of the analysis of the rolling samples, the cumulative effect on commodity prices during QE1 and QE2 are stronger than that of QE3, exit stage and interest rate hike stage in general. Show more

Keywords: Monetary policy, commodity price, event study, VAR model, fuzzy binomial

DOI: 10.3233/JIFS-189656

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8345-8357, 2021

Authors: Lin, Chuan | Chen, Yinzhong | Liao, Jing | Liu, Dongxuan

Article Type: Research Article

Abstract: Stimulated by the “Belt and Road” Initiative (BRI), Chinese enterprises are participating in the markets of Central and Eastern European Countries (CEECs). With the Chinese local SOEs from 2007 to 2017 as samples, this paper empirically verified the impact of the introduction of foreign-invested shares (foreign shares for short) on the international competitiveness of these enterprises, as well as the mediation effect of the BRI strategy. In this paper, we propose neuro -fuzzy network based correlation analysis and empirical analysis found that there’s a significant positive correlation between the introduction of foreign shares and the international competitiveness of Chinese local …SOEs, that is, compared with local SOEs without foreign shares, those with foreign shares enjoy stronger international competitiveness when participating in the Central and Eastern European market; after the mediation effect of BRI has been taken into consideration, the introduction of foreign shares further strengthened the positive impact on the international competitiveness of these enterprises. This is because the BRI has significantly promoted the participation of Chinese SOEs in the Central and Eastern European market. Show more

Keywords: International competitiveness, Foreign-invested shares (foreign shares), “Belt and Road” initiative (BRI), Central and Eastern European Countries (CEECs), SOEs (SOEs)

DOI: 10.3233/JIFS-189657

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8359-8369, 2021

Authors: Lv, Zhongguo | Wang, Liping | Zhang, Wei

Article Type: Research Article

Abstract: At present, the development of China’s economy is inseparable from the promotion of innovation and entrepreneurship. However, there are huge differences in the level of entrepreneurship in different regions, so it is urgent to analyze the influencing factors of entrepreneurship. This paper uses panel data of 31 provinces in 2008–2017 to test the impact of urban unemployment rate, regional financial development level, market scale, agglomeration effect, entrepreneurial cost, scientific and technological innovation level, government support and other factors on entrepreneurial level. To solve the issue of factors influencing the enterprises, we utilised an effective way of fuzzy logic along with …decision estimation strategy. The empirical results show that regional financial development level, agglomeration effect, technological innovation ability, government support and so on have a positive role in promoting the level of entrepreneurship, while urban unemployment rate has no significant effect on the level of entrepreneurship. Based on the empirical conclusion, the paper puts forward some policy suggestions. Show more

Keywords: Entrepreneurship level, influencing factors, regional difference, panel data, fuzzy logic

DOI: 10.3233/JIFS-189658

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8371-8377, 2021

Authors: Wu, Min | Xu, Junhua | Zhu, Shanshan | Lei, Jinzhi | Gao, Jie

Article Type: Research Article

Abstract: Analysis of single-cell RNA sequencing (scRNA-seq) data is often complicate due to the sparsity and high data dimensionality. In this work, we proposed Fuzzy C-means based linear stable-exponential distribution (LSED) model for analyzing scRNA-seq count data of chronic myeloid leukemia (CML) patients. We propose pipelines stages for analysis in which noisy and inconsistent data form sequencing is removed during data preprocessing, this process data then form the cluster of gene feature using fuzzy c-means (FCM) clustering, relevant features are extracted during feature extraction approach. These extracted features are then fed into LSED model in order to difference feature data of …gene expression. Finally we evaluate the performance for proposed analysis model based on parameter estimation, distribution comparison and parameter analysis. From the result analysis it was observed that proposed analysis model parameter reflect change in condition of patient more effectively as well as this model fits difference data of gene expression in more better way in comparison to Cauchy and stable distribution. Additional, the results of Gene-set enrichment analysis specify the affinity of proposed model can replicate the distinct enhancement of BCR-ABL+ stem cell as well as BCR-ABL- stem cells. Significantly, proposed FCM based LSED analysis model studies CML from the perspective of statistical models, which present a new sight for CML scientific research. Show more

Keywords: Chronic Myeloid Leukemia (CML), Alignment, Fuzzy C-Means (FCM), Linear Stable-Exponential Distribution Model (LSED model), stable distribution, feature extraction, gene expression, cauchy distribution

DOI: 10.3233/JIFS-189659

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8379-8388, 2021

Authors: Yu, Jiagen

Article Type: Research Article

Abstract: As we know, AI is deeply integrated with all walks of life. While upgrading traditional products and transforming traditional industries, a large number of new products, new industries and new formats have emerged in large numbers, and new industrial space has been further expanded. The potential for steady economic growth remains huge. However, the influence of merelygrowing capital asset and labor force dimension in terms of boosting economic progress has been waning globally. Considering the China’s data panel data outlying areas during 1978–2017 as the research sample, possible economic growing rate of Chinahas been calculated in detail according to the …labor-intensive structural time-varying elastic model. It shows a U-shaped development track during 2018–2027, with an average growth rate between 5.00%and 6.00%. There are also great variances in the probable economy growing rates in different regions in China. It shows that relying solely on traditional factors of production to drive potential economic growth, China has been unable to maintain the prosperity of stable development over the past few decades. Based on the experience of typical representative countries, this paper also puts forward some relevant countermeasures and suggestions including focusing on a new round of technological revolutions such as big data, new generation AI, 5 G, IOT, cloud computing, robotics, and blockchain to progress economical growing rate of China in the future. Show more

Keywords: Economic growth, potential output, AI, china, fuzzy rule, artificial neural network (ANN)

DOI: 10.3233/JIFS-189660

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8389-8402, 2021

Authors: GAO, Yang

Article Type: Research Article

Abstract: With knowledge perspective of industrial technology, in this paper we propose fast ranking score decision making model based on Fuzzy integrated TOPSIS approach to determine economic growth rate of manufacturing industry in China. This research focuses on driving effects of China’s productive service industry on manufacturing technology innovation. The research results show that the manufacturer service industry takes a high level of information diffusion for the manufacturing industry. It transmits a large amount of diverse information through the unconstrained relationship with the manufacturing industry, thereby forming the economic network with proposed Fuzzy integrated TOPSIS economy ranking (FITER) model and improve …the development level of the manufacturing industry. We evaluate the performance of proposed FITER model by comparing ranking score of different manufacturing industry with different existing decision making mode and demonstrate that proposed model represent best ranking score in comparison to existing approach. Result from data analysis motivates driving effect of production services on the technological innovation of manufacturing and sub-sectors. It is found that the innovation and technological advancement in the production industry of services takes drive the overall expansion level of the business industry, as well as make the manufacturing industry the strongest. Show more

Keywords: Technology linkage, innovation drive, economic network, fuzzy-Integrated TOPSIS, technique for order of preference by similarity to ideal solution (TOPSIS)

DOI: 10.3233/JIFS-189661

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8403-8415, 2021

Authors: Li, Ning | Feng, Junwen

Article Type: Research Article

Abstract: Recent year development in each field and area progresses rapidly. For one particular product or service, people have multiple alternative. However, to choose best alternative is most difficult task that most of person facing. VIKOR method is most used approach for choosing best alternative based on different criteria but legging in precision. In this paper, we propose modifier VIKOR with Fuzzy logic integration approach that deal with multiple criteria while making decision as well as integratestriangular fuzzy numbers (TFN) for computing criteria values and weight importance in the processing selecting best alternative. Firstly, positive best points and negative best points …were demarcated in a triangular fuzzy number evaluation matrix. Secondly, we analyze the requirements and properties of the VIKOR-based triangular fuzzy number operation rule. Thirdly, an extension of VIKOR method was proposed for comprehensive evaluation of schemes to reduce the information loss arising from defuzzification of triangular fuzzy numbers; Finally, an example demonstrate the efficiency and viability of the method. In conclusion, the proposed method solves the difficulties that subtractive computation between two triple numbers violate the arithmetic regulation, and propose a reasonable procedure according to decision making problems with triple numbers. Show more

Keywords: Vlse kriterijumska optimizacija I kompromisno resenje(VIKOR), technique for order preference by similarity to ideal solution (TOPSIS) triangular fuzzy number (TFN), positive best points and negative best points

DOI: 10.3233/JIFS-189662

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8417-8425, 2021

Authors: Wang, Guilian | Zhang, Liyan | Guo, Jing

Article Type: Research Article

Abstract: This paper try to fully reveal the key factors affecting the the level of AMT application in micro- and small enterprises (MSEs) from its organizational factors by ordinal logistic regression. The results show that MSEs have a relatively high level of AMT application as a whole due to the maturity and cost reduction of basic technologies such as artificial intelligence, digital manufacturing and industrial robots. In this paper we propose manufacturing world analysis at Application using Logistic Regression and best AMT selection using Fuzzy-TOPSIS Integration approach.Considering the influence mechanism of each factor, the important factors that affect the application level …of AMT are the enterprise’s market pricing power, the main production types, technical, market and management capabilities, organization development incentives and the interaction with external stakeholders. Based on the results above, the following policy implications are proposed: further expanding the customized production in MSEs to gradually improve the market pricing power, expanding the core competence of enterprises, enhancing the employee autonomy, and strengthening the interaction with industry organizations. Show more

Keywords: MSEs, level of AMT application, social-technical system theory, ordinal logistic regression

DOI: 10.3233/JIFS-189663

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8427-8437, 2021

Authors: Zhao, Dongmei | Song, Huiqian | Li, Hong

Article Type: Research Article

Abstract: The element extraction from network security condition is the foundation security awareness. Its excellence directly disturbsentire security system performance. In this paper we introduce fuzzy logic based rough set theory for extracting security conditional factors. The traditional extraction method of network security situation elements relies on a lot of prior knowledge. With the purpose of solving this issue, in this paper we proposed fuzzy rough set theory based featurerank matrix of neighborhood rough set. Additionally, we propose reduction based parallel algorithm that uses the concept of conditional entropy in order to constructs the feature rank matrix as well as, constructs …the core attribute by using reduction rules, takes the threshold of standard deviation as the threshold, and redefines the multi threshold neighborhood of mixed data. The attack type recognition training is carried out on lib SVM, filtered classifier, j48 and random tree classifiers respectively. The results demonstrate that the proposed reduction based parallel algorithm can increase the accuracy of classification, shorten the modeling time, and show increased recall rate and decreased false alarm rate. Show more

Keywords: Situation factor extraction, neighborhood rough set, attribute reduction, parallel reduction, fuzzy rough set

DOI: 10.3233/JIFS-189664

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8439-8450, 2021

Authors: Shi, Ruyi | Wang, Di | Zhao, Yueying

Article Type: Research Article

Abstract: From the perspective of external market shocks, this paper proposed fuzzy integrated vector auto regression (FVAR) model that determines the long-term basis and short-term basis interactions of China’s coal price with international energy prices. The proposed FVAR preform coal price fluctuation based on long-term and short term span in six stages including unit root testing, Johansen cointegration test, vector auto regression (VAR) model construction, fuzzification of VAR model, vector error correction (VEC) model and an impulse response function(IRF). It is observed that there is a steady long-term stability and equilibrium bond between the China’s domestic coal price, international coal price …and the international crude (unrefined) oil price. The international coal and international crude oil price have an opposite effect on China’s domestic coal price. In addition, the former has a stronger fuzzy price discovery function on China’s domestic coal market than the latter. In the short term, China’s domestic coal price is more complex to instability reactions and is affected by market expectations. The international energy market is more effective than domestic coal market, and there is a relatively stable price adjustment mechanism between the two, with the international coal price playing a leading role in the fuzzy guidance of China’s coal price. Therefore, in reference to international energy pricing models, the paper proposes a fuzzy pricing model for a coal futures index based on the coal futures trading price and supplemented by the premium and discount agreed to by both trading parties. Show more

Keywords: China’s coal price, international energy market, fuzzy price discovery, shocks, fuzzy linear regression, vector auto regressive (VAR) model, vector error correction (VEC) model, impulse response function(IRF)

DOI: 10.3233/JIFS-189665

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8451-8461, 2021

Authors: Yang, Ling | Li, Linyue

Article Type: Research Article

Abstract: In this work, we study the impact of China’s services sector liberalization reform on the country’s manufacturing sector. In this paper we propose Fuzzy based association between service industry and Manufacturing Industry with performance evaluation of Manufacturing Industry based on different performance criteria. The results analysis of proposed work suggest that there is: a extremely important and constructive relationship between the existence of reserved services suppliers and the efficiency of downstream manufacturing companies; a constructive (yet unsteady) relationship between the existence of overseas services suppliers and manufacturing efficiency; and a important and adverse relationship between the extent of state-owned services …providers and manufacturing productivity. Curiously, our results also suggest that given the unstable association between the presence of foreign services providers and manufacturing performance, overall imported services (including foreign services providers operating in China) have a highly significant and positive association with manufacturing productivity. In addition, taking into account firm heterogeneity, such as AI (artificial intelligence), our results suggest that there is no difference in the above effects of China’s services sector’s liberalization between those manufacturing firms that engage in importing and exporting and the manufacturing firms that do not. Show more

Keywords: Liberalization, services, productivity, manufacturing, firm heterogeneity, AI (artificial intelligence), fuzzy system

DOI: 10.3233/JIFS-189666

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8463-8476, 2021

Authors: Zhu, Chengke | Wang, Junshan

Article Type: Research Article

Abstract: With the development of technology and artificial intelligence(AI), financial leasing is used frequently in China’s equipment manufacturing industries, especially after 2008, which attracts our attention. This paper focuses on the problem. A theoretical model is provided in the paper to explain the motivation that why financial leasing is used in equipment manufacturing industries. In this paper, we employ multi-level fuzzy linear regression model to analyze data of manufacturing equipment industry of China in order to discover impact between sales revenue and financial leasing. We also discover credit sale forecasting using this model. We discover that economic leasing has a constructive …important effect on sales revenue in total samples, which is consistent with the theoretical framework. However, the results are different in sub-industries, which shows that economic leasing has a constructive and important effect on sales profits in some sub-industries, but some of them are not. Furthermore, we also find that asset characteristics has a substantial effect on financial leasing decision. The outcome demonstrates that the more precise the asset, the easier it can be leased. Show more

Keywords: Financial leasing, sales revenue, equipment manufacturing industry, promotion, artificial equipment intelligence, fuzzy linear regression model

DOI: 10.3233/JIFS-189667

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 8477-8484, 2021