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

Authors: Chen, Yenming J. | Tsai, Jinn-Tsong | Huang, Wei-Tai | Ho, Wen-Hsien

Article Type: Research Article

Abstract: The uncertainty issue in real-work optimization affects the level of optimization significantly. Because most future uncertainties cannot be foreseen in advance, the optimization must take the uncertainties as a risk in an intelligent way in the process of computation algorithm. Based on our risk-sensitive filtering algorithm, this study adopts a model-predictive control to construct a risk-averse, predictable model that can be used to regulate the level of a real-world system. Our model is intelligent in that the predictive model needs not to identify the system parameters in advance, and our algorithm will learn the parameters through data. When the real-world …system is under the disturbance of unexpected events, our model can still maintain suitable performance. Our results show that the intelligent model designed in this study can learn the system parameters in a real-world system and minimize unexpected real-world disturbances. Through the learning process, our model is robust, and the optimal performance can still be retained even the system parameters deviate from expected, e.g., material shortage in a supply chain due to earthquake. When parameter error risks occur, the control rules can still drive the overall system with a minimal performance drop. Show more

Keywords: Intelligent optimization, model-predictive control, risk-sensitive filtering, robust algorithm

DOI: 10.3233/JIFS-189608

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7863-7873, 2021

Authors: Lee, Bor-Hon | Yang, Albert Jing-Fuh | Chen, Yenming J.

Article Type: Research Article

Abstract: A large categories of time series fluctuate dramatically, for example, prices of agriculture produce. Traditional methods in time series and stochastic prediction may not capture such dynamics. This paper tries to use machine learning to tune the model for a real situation by establishing a price determination mechanism on the model of stochastic automata (SA) and evolutionary game (EG). Time series volatility attributed to the chaotic process can be obtained through the learning algorithm of Markov Chain Monte Carlo (MCMC). Using machine learning through the chaotic analysis of stochastic automata and evolutionary games, we find that a more spatially aggregated …distribution (smaller entropy) leads to larger time series fluctuations, regardless of the initial distribution of crops. By integrating the factors discovered in this study, we can develop a better learning algorithm in a highly volatile time series in agriculture prices. Show more

Keywords: Distribution entropy, spatial diffusion, stochastic automata (SA), evolutionary game (EG), machine learning

DOI: 10.3233/JIFS-189609

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7875-7881, 2021

Authors: Chen, Yao-Mei | Chen, Yenming J. | Tsai, Yun-Kai | Ho, Wen-Hsien | Tsai, Jinn-Tsong

Article Type: Research Article

Abstract: A multi-layer convolutional neural network (MCNN) with hyperparameter optimization (HyperMCNN) is proposed for classifying human electrocardiograms (ECGs). For performance tests of the HyperMCNN, ECG recordings for patients with cardiac arrhythmia (ARR), congestive heart failure (CHF), and normal sinus rhythm (NSR) were obtained from three PhysioNet databases: MIT-BIH Arrhythmia Database, BIDMC Congestive Heart Failure Database, and MIT-BIH Normal Sinus Rhythm Database, respectively. The MCNN hyperparameters in convolutional layers included number of filters, filter size, padding, and filter stride. The hyperparameters in max-pooling layers were pooling size and pooling stride. Gradient method was also a hyperparameter used to train the MCNN model. …Uniform experimental design approach was used to optimize the hyperparameter combination for the MCNN. In performance tests, the resulting 16-layer CNN with an appropriate hyperparameter combination (16-layer HyperMCNN) was used to distinguish among ARR, CHF, and NSR. The experimental results showed that the average correct rate and standard deviation obtained by the 16-layer HyperMCNN were superior to those obtained by a 16-layer CNN with a hyperparameter combination given by Matlab examples. Furthermore, in terms of performance in distinguishing among ARR, CHF, and NSR, the 16-layer HyperMCNN was superior to the 25-layer AlexNet, which was the neural network that had the best image identification performance in the ImageNet Large Scale Visual Recognition Challenge in 2012. Show more

Keywords: Convolutional neural network, hyperparameter, human electrocardiogram, PhysioNet, uniform experimental design approach

DOI: 10.3233/JIFS-189610

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7883-7891, 2021

Authors: Chou, Fu-I | Ho, Wen-Hsien | Chen, Yenming J. | Tsai, Jinn-Tsong

Article Type: Research Article

Abstract: This study proposes a framework implementing triangular estimation for better modeling and forecasting time series. In order to improve the performance of estimation, we employ two sources of triangulation to generate a time series, which is statistically indistinguishable with the latent time series hidden in a system. Thanks to Bayesian hierarchical estimation, which is akin to deep learning but more sophisticate and longer history, the framework has been validated by a large amount of records in vegetable auctions. The hierarchical Bayesian estimation and Monte Carlo Markov Chain particle filters used in hidden Markov model are appreciated during the massive bootstrapping …of data. Our results demonstrate excellent estimation performance in discovering hidden states. Show more

Keywords: Generative estimation, time series forecasting, triangulation data assimilation

DOI: 10.3233/JIFS-189611

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7893-7899, 2021

Authors: Ouyang, Chen-Sen | Chen, Yenming J. | Tsai, Jinn-Tsong | Chang, Yiu-Jen | Huang, Tian-Hsiang | Hwang, Kao-Shing | Ho, Yuan-Chih | Ho, Wen-Hsien

Article Type: Research Article

Abstract: Atrial fibrillation (AF) is a type of paroxysmal cardiac disease that presents no obvious symptoms during onset, and even the electrocardiograms (ECG) results of patients with AF appear normal under a premorbid status, rendering AF difficult to detect and diagnose. However, it can result in deterioration and increased risk of stroke if not detected and treated early. This study used the ECG database provided by the Physionet website (https://physionet.org ), filtered data, and employed parameter-extraction methods to identify parameters that signify ECG features. A total of 31 parameters were obtained, consisting of P-wave morphology parameters and heart rate variability parameters, …and the data were further examined by implementing a decision tree, of which the topmost node indicated a significant causal relationship. The experiment results verified that the P-wave morphology parameters significantly affected the ECG results of patients with AF. Show more

Keywords: Atrial fibrillation, electrocardiogram (ECG), data mining, decision tree

DOI: 10.3233/JIFS-189612

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7901-7908, 2021

Authors: Ko, Joonho | Cho, Hyun Woong | Kim, Jung In | Kim, Hyunmyung | Lee, Young-Joo | Suh, Wonho

Article Type: Research Article

Abstract: Transportation system management and traveler information systems evolve with the development of data communications and intelligence of traffic simulations. Variety of roadside and mobile sensing platforms will be deployed to allow communication between vehicles with Dedicated Short Range Communications (DSRC). Traffic data received from moving vehicles will be transmitted to each individual vehicle and traffic management center to provide real time traffic information. Microscopic traffic simulation models will be used for generating intelligence from real time data in the form of traffic analysis and prediction, since they have the highest detailed level of prediction such as vehicle / driver characteristics …and have the capability to capture dynamically changing traffic conditions through the simulation. In this study, three communication methods for data communication and intelligence in traffic simulation environments are used including Ethernet, off-the-shelf wireless network, and one commercial network provider for data communication. Simulation time is measured and statistically analyzed using three different communication methods and one non-communication case. Also, traffic simulation performance is investigated to demonstrate the intelligence of traffic simulation tools in modeling traffic congestion. Show more

Keywords: Traffic simulation environments, data communication, intelligence of traffic simulation, simulation analysis, network simulation

DOI: 10.3233/JIFS-189613

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7909-7916, 2021

Authors: Ko, Joonho | Cho, Hyun Woong | Kim, Jung In | Kim, Hyunmyung | Lee, Young-Joo | Suh, Wonho

Article Type: Research Article

Abstract: Traffic simulation tools are becoming more popular as complexity and intelligence are growing in transportation systems. The need for more accurate and intelligent traffic modeling is increasing rapidly as transportation systems are having more congestion problems. Although traffic simulation models have been continuously updated to represent various traffic conditions more realistically, most simulation models still have limitations in overcapacity congested traffic conditions. In traditional traffic simulation models, when there is no available space due to traffic congestion, additional traffic demand may never be allowed to enter the network. The objective of this paper is to investigate one possible method to …address the issue of unserved vehicles in overcapacity congested traffic conditions using the VISSIM trip chain. The VISSIM trip chain is used for this analysis as it has the advantage of holding a vehicle without eliminating it when traffic congestion prevents its entrance onto a network. This will allow the vehicle to enter when an acceptable gap becomes available on the entry link. To demonstrate the difference between the simulation using standard traffic input and the trip chain method, a sample congested traffic network is built and congested traffic scenarios are created. Also, simulations with different minimum space headway parameters in the priority rules are analyzed to model congested traffic conditions more realistically. This will provide the insight about the sensitivity of the model to this parameter. Based on the analysis conducted it is concluded that, with appropriate calibrations, the trip chain feature in VISSIM has the potentials to be useful in modeling overcapacity congested traffic conditions more realistically. Show more

Keywords: Traffic simulation environments, traffic congestion modeling, intelligence of traffic simulation, simulation analysis, network simulation

DOI: 10.3233/JIFS-189614

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7917-7923, 2021

Authors: Chen, Joy Iong-Zong | Hengjinda, P.

Article Type: Research Article

Abstract: Smart Robot embedded with GMM-UBM (Gaussian mixture model- universal background model) based on the machine learning scheme is presented in the article. Authors have designed a smart robot for the farmer and which is designed controlled by the concept of machine learning. On the other hand, the techniques of machine learning are applied to develop a smart robot for helping farmers recognize the environment conditions, e.g . weather, and disease protection in rice or plant. The smart robot is implemented to detect and to recognize the environment conditions around a fixed area. The sensing way through vision devices, such as …camera, look like a human’s eye to distinguish various types of target. The QR code is deployed to simulate working conditions allows the robot to separate conditions and act according to conditions precisely. Besides, the smart robot is embedded with GMM-UBM algorithm for promoting the accuracy of recognition from the deployment of machine learning. The smart robot, mainly combines with AI (Artificial intelligence) techniques, consists of the following equipments: 1) a control movement subsystem, 2) a sensor control subsystem, and 3) an analysis subsystem. The researcher has determined the condition of the message options via QR code. In addition, the contents of the QR code tag will be processed a text message and saved to a memory device, once the reading is finished. The data analysis subsystem then reads the text and recommends the robot to move according to the specified conditions. The results from QR code data allow the smart robot to accurately collect many kinds of prefer data (e.g ., climate data) in the farm at the specified location. Show more

Keywords: Artificial intelligence, GMM-UBM, machine learning, smart robot, vision devices

DOI: 10.3233/JIFS-189615

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7925-7937, 2021

Authors: Yu, Meng | Lu, Bao | Li, Xiong | Li, Wenfeng

Article Type: Research Article

Abstract: Online Distance teaching for multiple smart classrooms by famous teachers, as an effective solver for the problem of lack of excellent teachers, has become a new popular teaching mode. However, one of the key problems to be solved urgently for this teaching mode is how to monitor children’s class status and effectively feedback their listening standing to teachers. Installation of intelligent pressure cushion on the chair of smart classroom to monitor children’s classroom state can be a powerful way to improve teaching effectiveness for the online distance teaching mode. This paper presents a new method for monitoring children’s classroom behavior …based on intelligent cushion, which can identify basic children’s classroom behavior by classifying the original intelligent cushion pressure signal and evaluating the effectiveness of the classifier. To be concrete, the present method uses intelligent pressure cushion to collect data and denoises the original data by digital filter, and then extracts the time-domain and frequency-domain features of time-series pressure signals based on sliding time window. Finally, it uses machine learning to identify children’s status. In addition, by feature selection to reduce the data dimension, integrating different classifier to classify the extracted features, the efficiency of the present method is greatly improved. Show more

Keywords: Smart cushion, child behavior recognition, pressure sensor

DOI: 10.3233/JIFS-189616

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7939-7949, 2021

Authors: Pan, Nan | Jiang, Xuemei | Pan, Dilin | Liu, Yi

Article Type: Research Article

Abstract: This article has been retracted, and the online PDF has been watermarked “RETRACTED”. The retraction notice is available at https://doi.org/10.3233/JIFS-219327 .

DOI: 10.3233/JIFS-189617

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7951-7956, 2021

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