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

Authors: Yao, Jian | Wang, Lisong | Liu, Ying | kui, Ying

Article Type: Research Article

Abstract: In order to improve the recognition accuracy of students’ psychological stress data in the English MOOC classroom teaching process, this paper improves the traditional fuzzy C-means algorithm, and uses the deviation value to represent the difference between the average algebraic distance of the neighborhood point and the center pixel. By calculating the deviation value, the influence of the neighborhood point on the center point can be measured, and the noise resistance of the algorithm can be improved. Moreover, this paper constructs a quantitative identification model of student stress data based on the needs of English MOOC teaching stress analysis, and …uses image database to verify the basic performance of the algorithm, and constructs a data analysis system of student stress in English MOOC classroom, which is used in practice. In addition, this paper uses student facial expression recognition as a basis for quantitative identification of student stress, and designs experiments to analyze the reliability of the system. From the statistical results, it can be seen that the data analysis system of the students’ psychological stress in the English MOOC classroom teaching process constructed in this paper is effective. Show more

Keywords: Fuzzy C-means algorithm, English MOOC, student pressure, data analysis

DOI: 10.3233/JIFS-219048

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2021

Authors: Gao, Ya

Article Type: Research Article

Abstract: The network provides a convenient mechanism for publishing and obtaining documents, and has now become a gathering place for all kinds of information. In the network, the amount of information increases exponentially, and how to dig useful patterns or knowledge from the massive network culture has become a hot topic for scholars. In data mining, in order to enable readers to quickly obtain the content of interest, research text classification, and automatically classify text data according to a certain classification model. Internet cultural text data has the characteristics of unstructured, subjective, high-dimensional, etc., which makes it difficult for text mining …algorithms to extract effective and easy-to-understand classification rules, and the computational complexity is too high. This paper proposes a feature selection method based on robust features, using sample deviation and variance as the criteria for feature attributes to rank the importance of feature attributes, and select the best feature attribute subset. The experimental results show that the classification accuracy of the feature selection method based on sample deviation and variance proposed in this paper is higher than the traditional word frequency as the feature selection method, which proves the feasibility and superiority of the feature selection method proposed in this paper. Show more

Keywords: Classification, feature selection, robust feature set

DOI: 10.3233/JIFS-219077

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2021

Authors: Wu, Ze

Article Type: Research Article

Abstract: With the advancement of information construction, as an important part of smart city, the construction of smart society is invested. As a new mode of social management innovation under the new situation, the advantage of smart society is that it can complete the full integration of existing public resources and infrastructure, realize the knowledge mining of appearance information, so as to make social services and management more information-based and intelligent based on the common needs of smart social management, this paper analyzes the overall function of social management system in detail, puts forward the architecture and simulation of social management …service system based on internet of things information model, and realizes the smart social management system, so as to make social service more high-quality and efficient, and social management more standardized and scientific. This paper describes how to promote social management services, and the specific needs of social information as the research basis of this paper, realize the application of social information integrated management service platform, and then give play to the advantages of information technology, realize the transformation of social management work mode, facilitate the social management work, improve the overall quality of life of the community, and reduce the cost of management. Show more

Keywords: Social management services, internet of things, management information system, performance testing

DOI: 10.3233/JIFS-219071

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2021

Authors: Li, Jing | Li, Xinfang | Ning, Yuwen

Article Type: Research Article

Abstract: At present, many exciting results have been achieved in the application of deep learning to image recognition. However, there are still many problems to be overcome before deep learning is used in practical applications such as image retrieval, image annotation, and image-text conversion. This paper studies the structure of deep learning, improves the commonly used training algorithms, and proposes two new neural network models for different application scenarios. This paper uses Support Vector Machine (SVM) as the main classifier for Internet of Things image recognition and uses the database of this paper to train SVM and CNN. At the same …time, the effectiveness of the two for image recognition is tested, and the trained classifier is used for image recognition. The result surface: In the labeled data set, the rank-1 accuracy of CNN is 85.77%, which is higher than 90.28% of the SVM method. In the detection data, CNN’s rank-1 accuracy rate is 83.11%, which also exceeds SVM’s 80.22%. SVM+CNN has a rank 1 value of 84.69% for the detection data set. This shows that deep learning can map the feature representation of the image and the feature representation of the word to the same space, making the calculation of the similarity and correlation between the image and the text easier and more straightforward. Show more

Keywords: Deep learning, image recognition, image retrieval, multi-task learning

DOI: 10.3233/JIFS-219080

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2021

Authors: Noorullah, R.M. | Mohammed, Moulana

Article Type: Research Article

Abstract: Topic models are widely used in building clusters of documents for more than a decade, yet problems occurring in choosing the optimal number of topics. The main problem is the lack of a stable metric of the quality of topics obtained during the construction of topic models. The authors analyzed from previous works, most of the models used in determining the number of topics are non-parametric and the quality of topics determined by using perplexity and coherence measures and concluded that they are not applicable in solving this problem. In this paper, we used the parametric method, which is an …extension of the traditional topic model with visual access tendency for visualization of the number of topics (clusters) to complement clustering and to choose the optimal number of topics based on results of cluster validity indices. Developed hybrid topic models are demonstrated with different Twitter datasets on various topics in obtaining the optimal number of topics and in measuring the quality of clusters. The experimental results showed that the Visual Non-negative Matrix Factorization (VNMF) topic model performs well in determining the optimal number of topics with interactive visualization and in performance measure of the quality of clusters with validity indices. Show more

Keywords: Interactive visualization, visual non-negative matrix factorization model, an optimal number of topics, cluster validity indices, twitter data clustering

DOI: 10.3233/JIFS-202707

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2021

Authors: Bao, Yanli

Article Type: Research Article

Abstract: This paper takes the application of workflow technology in a multi-smart IOT message-driven practical training execution system as the research background, analyzes the current situation and problems of the practical training execution system, and reconstructs and optimizes the original on-site practical training model and business methods according to the future development needs of the practical training execution system. This study draws on the theoretical perspective of the computer knowledge body to deeply recognize and understand the connotation of computing ability from the levels of knowledge, skills, and attitude, forms a basic understanding of computing ability through literature combing, and refines …the core elements of computing ability through a combination of enterprise case study, content analysis, and questionnaire survey, strives to form a more systematic and in-depth understanding of the connotation and elements of computing ability. It also provides a reference for the clarification of computing ability training objectives of computer science teachers under the trend of intelligence. Facing the enhancement of computing ability of engineering students majoring in computer science at the undergraduate level, the objectives of computing ability cultivation are clarified, the key points of computing ability cultivation mode are refined from three levels: curriculum design, teaching operation, management, and control, and three typical computing ability cultivation modes embedded in undergraduate computer education are constructed: knowledge module combination mode, computing context experience mode, and intelligent industry-leading mode. The operational strategies and implementation paths of the models are discussed in depth. This study emphasizes that, based on the analysis of the characteristics of the trend of intelligence, the computing ability cultivation model is not static. Show more

Keywords: Multiple intelligent Internet of things, innovative, computer practical training education, model construction

DOI: 10.3233/JIFS-219065

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2021

Authors: Brás, Glender | Silva, Alisson Marques | Wanner, Elizabeth Fialho

Article Type: Research Article

Abstract: This paper introduces a new approach to build the rule-base on Neo-Fuzzy-Neuron (NFN) Networks. The NFN is a Neuro-Fuzzy network composed by a set of n decoupled zero-order Takagi-Sugeno models, one for each input variable, each one containing m rules. Employing Multi-Gene Genetic Programming (MG-GP) to create and adjust Gaussian membership functions and a Gradient-based method to update the network parameters, the proposed model is dubbed NFN-MG-GP. In the proposed model, each individual of MG-GP represents a complete rule-base of NFN. The rule-base is adjusted by genetic operators (Crossover, Reproduction, Mutation), and the consequent parameters are updated by …a predetermined number of Gradient method epochs, every generation. The algorithm uses Elitism to ensure that the best rule-base is not lost between generations. The performance of the NFN-MG-GP is evaluated using instances of time series forecasting and non-linear system identification problems. Computational experiments and comparisons against state-of-the-art alternative models show that the proposed algorithms are efficient and competitive. Furthermore, experimental results show that it is possible to obtain models with good accuracy applying Multi-Gene Genetic Programming to construct the rule-base on NFN Networks. Show more

Keywords: Neo-fuzzy-neuron, genetic programming, multi-gene, NFN-MG-GP, forecasting, non-linear system identification

DOI: 10.3233/JIFS-202146

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-18, 2021

Authors: Chen, Xianhui

Article Type: Research Article

Abstract: This paper adopts the decentralized model of e-commerce model through edge computing for in-depth analysis and discussion, and designs and implements the decentralized e-commerce model. Based on the background of the e-commerce environment formed by the development and application of Internet technology, the research starts from the core role of innovation management in business model innovation; based on analyzing the mechanism and path of business model innovation, the research is conducted and theoretical support is provided for business model innovation management, aiming to provide practical and feasible operational solutions for commercial enterprises to adapt to the development of e-commerce and …carry out business model innovation. Based on clarifying the idea and composition of the evaluation of business model innovation capability of commercial enterprises based on e-commerce environment, the paper analyzes and constructs the evaluation index system of business model innovation capability of commercial enterprises, and proposes the evaluation method based on gray theory and fuzzy evaluation theory. Show more

Keywords: Edge computing, decentralization, e-commerce model, design implementation

DOI: 10.3233/JIFS-219066

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2021

Authors: Ge, Yi | Zhang, Jing

Article Type: Research Article

Abstract: This paper analyzes the dynamics modelling and robust control of the robotic arm by using a model-based defines method. Firstly, the motion coupling relationship between the front and rear joints of the robotic arm is analyzed, and two kinds of motion decoupling modules based on planetary gear and pulley system are proposed, and the decoupling principle of the motion decoupling module is analyzed to realize the mechanical decoupling of the joint motion of the robotic arm. After that, a comprehensive test bench of two-degree-of-freedom robotic arm joint motion is constructed, and the factors influencing the decoupling effect of the mechanical …decoupling module are analyzed through experiments to verify the effectiveness of the motion decoupling module. At the same time, the analysis also shows that: with the increase of the number of robotic arm joints, the number and volume of required decoupling modules increase, and the application of decoupling modules will significantly increase the volume, weight, and torque loss of the robotic arm, thus leading to the robotic arm’s large load to weight ratio which is not an advantage, therefore, mechanical decoupling is not suitable for robotic arms with more than 3 degrees of freedom. The design of a fuzzy incremental controller based on the model dialectic method is proposed for application in parallel robot control; it has universal approximation characteristics and can self-organize the velocity and position information of the parallel robot legs, and dynamically adjust the output of the controller by the designed affiliation function and control rules. Show more

Keywords: Model identification methods, robotic arm dynamics, space grab, robust control

DOI: 10.3233/JIFS-219069

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2021

Authors: Pan, Wei | Liu, Fengwei

Article Type: Research Article

Abstract: Combined with the actual characteristics of risk identification in electric power enterprises, a convolutional neural network model suitable for load sequence data prediction is determined. Particle Swarm Optimization (PSO) algorithm is used to transform the convolutional neural network (convolutional neural network) to improve the global Optimization ability and convergence speed. Simulation results show that CNN can effectively extract sample information through its convolutional layer and pool layer. After particle swarm optimization, it also achieves good results in prediction accuracy and prediction speed. Secondly, classical interpretation combination model (ISM) is used to analyze the structure of the risk system of electric …power enterprises, and the link relationship model of the risk of electric power enterprises is constructed. Through the structural analysis of risk and risk factors, the paper finds out the mutual influence relationship between risk and risk factors, and further finds out the risk chain and risk source. The classical explanatory structure model is extended to the fuzzy set, and then the influence intensity model of power enterprise risk is built. This model considers the influence of risk intensity when analyzing the risk relationship of electric power enterprises, and gives different risk link relations based on different impact intensity. Through comparative analysis, the relationship between the link relationship model and the influence intensity model of the risk of electric power enterprises is obtained. Put forward the sequence similarity matching algorithm based on adaptive search window (ADTW), average algorithm using Piecewise gathered (Piecewise Aggregate Approximation, PAA) strategy for sequence sampling sequence, low precision and low calculation precision sequence alignment of paths, and according to the change of gradient on the low precision of distance matrix forecast path deviation, expand the scope of limiting path search window; Then, the algorithm gradually improves the sequence accuracy, corrects the path in the search window, calculates the new search window, and finally realizes the fast solution of DTW distance and similarity alignment path. Show more

Keywords: Convolutional neural network, similarity search, time series measurement, risk of electric power enterprise, sequence similarity alignment algorithm

DOI: 10.3233/JIFS-219068

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2021

Authors: Wang, Shengwei | Li, Ping | Ji, Hao | Zhan, Yulin | Li, Honghong

Article Type: Research Article

Abstract: Intelligent algorithms using deep learning can help learn feature data with nonlinearity and uncertainty, such as time-series particle concentration data. This paper proposes an improved particle swarm optimization (IPSO) algorithm using nonlinear decreasing weights to optimize the hyperparameters, such as the number of hidden layer neurons, learning rate, and maximum number of iterations of the long short-term memory (LSTM) neural network, to predict the time series for air particulate concentration and capture its data dependence. The IPSO algorithm uses nonlinear decreasing weights to make the inertia weights nonlinearly decreasing during the iteration process to improve the convergence speed and capability …of finding the global optimization of the PSO. This study addresses the limitations of the traditional method and exhibits accurate predictions. The results of the improved algorithm reveal that the root means square, mean absolute percentage error, and mean absolute error of the IPSO-LSTM model predicted changes in six particle concentrations, which decreased by 1.59% to 5.35%, 0.25% to 3.82%, 7.82% to 13.65%, 0.7% to 3.62%, 0.01% to 3.55%, and 1.06% to 17.21%, respectively, compared with the LSTM and PSO-LSTM models. The IPSO-LSTM prediction model has higher accuracy than the other models, and its accurate prediction model is suitable for regional air quality management and effective control of the adverse effects of air pollution. Show more

Keywords: Particle concentration, particle swarm optimization, long short-term memory network, nonlinear decreasing weight, air pollution

DOI: 10.3233/JIFS-210603

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-17, 2021

Authors: Lei, Yu | Nazir, Babar | Ali Khan, Imran | Hongdan, Shen | Haining, Gao | Yinling, Wang

Article Type: Research Article

Abstract: This paper studies the implementation of distributed building smart construction technology. We analyze the role of building information models, Internet of Things, and pervasive computing in smart construction. Based analysis, we use integrated ideas and integrated frameworks for integration construction in the full life cycle of distributed buildings, and research from the perspective of full life cycle on distributed architectural intelligence construction management concepts. Equipment modeling and data storage management mainly include the establishment of equipment models and the storage and management of equipment real-time data. We design the database table structure by analyzing personnel, equipment, virtual space and the …relationship between them, and establish the corresponding E-R model. We research and investigate the types and operating characteristics of equipment in buildings, classify IoT equipment, model several commonly used building networking equipment, and build equipment model libraries. We analyze the business process and data flow of building networked equipment management, and conduct research on the application of equipment virtualization management to realize the intelligent and personalized management of IoT equipment. Taking three smart buildings based on building information models as examples for empirical analysis, the evaluation grades of three projects are obtained by calculating the correlation degree, and then the projects are sorted according to the evaluation grades and the best projects are selected. Show more

Keywords: Distributed building, smart construction, integrated management, Internet of Things

DOI: 10.3233/JIFS-219070

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2021

Authors: Zhang, Qi

Article Type: Research Article

Abstract: Based on the comprehensive application and bibliometrical analysis of the non-cooperative equilibrium theory of game theory, this paper takes the construction project group as the research background, analyzes the obstacles to the application of management informatization in the construction project, and conducts a pair game study on the application of management informatization by single or group subjects. Aims to provide a valuable reference for the application of management information in construction projects, in line with the policy orientation, and has a certain practical significance. On the basis of combing the relevant literature on the application of management information in the …field of construction industry and game analysis, this paper first analyzes the appeal, current situation and obstacles of the application of management information in construction projects. The game results show that there are specific management inspirations for different subjects: the designer should change the way of thinking, control the cost of management information application, and carry out in-depth communication with other subjects on building information to ensure consistency; Contractors need to improve their own ability to apply management information, but also to coordinate and control the relative importance of the three objectives, so that efforts can be more easily converted into positive results. Show more

Keywords: Game theory, noncooperative equilibrium method, construction project management, informatization

DOI: 10.3233/JIFS-219078

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2021

Authors: Li, Tao | Yang, Yongqing

Article Type: Research Article

Abstract: The nuclear magnetic resonance spectrum contains a variety of effective information, and most of the current clinical medicine uses nuclear magnetic resonance images as a diagnostic basis, but the spectral information is still not effectively explored. In order to improve the diagnostic results of nuclear magnetic resonance spectrum, this study uses DNN neural network as a technical support to extract effective information of nuclear magnetic resonance spectrum. Simultaneously, in order to improve the ability to describe the local features of the image, the traditional Crow algorithm is improved, and a similar target localization algorithm based on F-CroW is proposed. In …addition, starting from the animal model of nasopharyngeal carcinoma and the serum and urine samples of patients with clinical nasopharyngeal carcinoma, this study designed a comparative study to study the performance of the proposed algorithm. According to the research and analysis, the DNN neural network proposed in this study has certain effects in the nuclear magnetic resonance spectrum analysis, which can be applied to clinical practice. Show more

Keywords: DNN neural network, nuclear magnetic resonance, spectrum analysis, target localization, characterization

DOI: 10.3233/JIFS-219060

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2021

Authors: Dong, Chao | Guo, Yan

Article Type: Research Article

Abstract: The wide application of artificial intelligence technology in various fields has accelerated the pace of people exploring the hidden information behind large amounts of data. People hope to use data mining methods to conduct effective research on higher education management, and decision tree classification algorithm as a data analysis method in data mining technology, high-precision classification accuracy, intuitive decision results, and high generalization ability make it become a more ideal method of higher education management. Aiming at the sensitivity of data processing and decision tree classification to noisy data, this paper proposes corresponding improvements, and proposes a variable precision rough …set attribute selection standard based on scale function, which considers both the weighted approximation accuracy and attribute value of the attribute. The number improves the anti-interference ability of noise data, reduces the bias in attribute selection, and improves the classification accuracy. At the same time, the suppression factor threshold, support and confidence are introduced in the tree pre-pruning process, which simplifies the tree structure. The comparative experiments on standard data sets show that the improved algorithm proposed in this paper is better than other decision tree algorithms and can effectively realize the differentiated classification of higher education management. Show more

Keywords: Variable precision, scaling function, higher education management, decision tree

DOI: 10.3233/JIFS-219036

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2021

Authors: Hongmei, Wan | Songlin, Tang

Article Type: Research Article

Abstract: In order to improve the efficiency of sentiment analysis of students in ideological and political classrooms, under the guidance of artificial intelligence ideas, this paper combines data mining and machine learning algorithms to improve and propose a method for quantifying the semantic ambiguity of sentiment words. Moreover, this paper designs different quantitative calculation methods of sentiment polarity intensity, and constructs video image sentiment recognition, text sentiment recognition, and speech sentiment recognition functional modules to obtain a combined sentiment recognition model. In addition, this article studies student emotions in ideological and political classrooms from the perspective of multimodal transfer learning, and …optimizes the deep representation of images and texts and their corresponding deep networks through single-depth discriminative correlation analysis. Finally, this paper designs experiments to verify the model effect from two perspectives of single factor sentiment analysis and multi-factor sentiment analysis. The research results show that comprehensive analysis of multiple factors can effectively improve the effect of sentiment analysis of students in ideological and political classrooms, and enhance the effect of ideological and political classroom teaching. Show more

Keywords: Artificial intelligence, data mining, ideological and political, student emotion, sentiment analysis

DOI: 10.3233/JIFS-219047

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2021

Authors: Cao, Shuting | Chen, Rui | Liu, Haiyuan | Shi, Ruolin

Article Type: Research Article

Abstract: The main goal of college English education is to cultivate the students’ language ability of listening, speaking, reading and writing, and to promote the formation of individualized learning and autonomous ability of college students. At present, the new curriculum reform in our country has put forward a new educational requirement to college English teaching, which requires the innovation of college English teaching idea, and under the background of the development of new media, it proposes to use new media equipment to carry out teaching activities. However, college English education in our country is influenced by examination-oriented education mode, and the …traditional education method is still used, which is not good for college students to improve their comprehensive quality of English. In view of this development situation, the Ministry of Education of China Based on the development of new media, a multimodal discourse analysis approach to college English education is proposed to enhance the level of College English teaching. Show more

Keywords: New media, college English, teaching multiple modes, discourse analysis, The Empirical Research

DOI: 10.3233/JIFS-219037

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-5, 2021

Authors: Abd El-Latif, Ahmed A. | Tawalbeh, Loai A.

Article Type: Editorial

DOI: 10.3233/JIFS-219058

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-1, 2021

Authors: Lyu, Yukun

Article Type: Research Article

Abstract: Saxophone playing is also a complex process of mental activity. In the learning process of saxophone performance, it is necessary to understand the role of psychological factors in saxophone performance on physiological factors, correctly understand the fluctuations in performance during practice, and remove various psychological obstacles during practice. This article uses clustering method to extract and analyze performers’ mental state. At the same time, based on the existing clustering evaluation indicator, a new evaluation indicator is proposed, which solves the problem that the original evaluation indicator is not applicable to non-convex data sets. In addition, this paper uses intelligent algorithms …to extract the mental state characteristics of saxophone players, and on this basis, constructs an intelligent system with music education psychology to improve the mental state of saxophone players and stage performance effects. Finally, this paper analyzes the system performance after constructing the system with algorithms. The research results show that the system constructed in this paper has a certain effect. Show more

Keywords: Music education psychology, saxophone, mental state, stage performance

DOI: 10.3233/JIFS-219039

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2021

Authors: Tong-Zhigang,

Article Type: Research Article

Abstract: In the decision-making system of sports assistant teaching and training, the performance of such system is not robust to different situations with a low accuracy. To solve the problems in the decision-making system, we proposed a decision-making method combining association rules and support vector machine (SVM) in this paper. First of all, we give a computer-aided decision support system for sports assistant learning and teaching training, which is fully elaborated from three aspects: virtual reality (VR) technology, VR based sports assistant learning and teaching and situational cognition, and VR based sports assistant learning and teaching mode. After that, the paper …gives the feature extraction of sports auxiliary teaching training through association rules and the decision-making of the extracted association rules by SVM. We have done two different experiments for both association rules mining and SVM on both experiment group and control group of databases. Experimental results have shown that the training characteristics of sports auxiliary teaching very well. In the decision support of association rules, compared with the existing BP neural network, linear discriminant analysis and naive Bayes and other methods, the SVM method has better effect of action recognition in decision support system of sports assistant teaching and training. The robustness is the best for the application of SVM. We provide a new perspective for the decision support of sports auxiliary teaching training by using association rules and SVM. Through the method of this paper, we can obtain better decision-making effect and more robust process of sports auxiliary teaching and training. Show more

Keywords: Association rules, SVM, sports assistant teaching training, decision support, VR

DOI: 10.3233/JIFS-219035

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2021

Authors: Liu, Shengnan | Zhang, Tingting

Article Type: Research Article

Abstract: Music psychology can play an important role in the diagnosis and rehabilitation of mental health patients. Under the guidance of music psychology, this paper combines fuzzy models to process data, which effectively solves the problem that the number of categories in the fuzzy c-means algorithm needs to be manually given. The AFCC algorithm effectively combines the idea of semi-supervised clustering with the CA algorithm. Through two sets of must-link and cannot-link, this paper introduces the constraint penalty item into the objective function, which greatly improves the clustering accuracy. On this basis, this paper constructs a fuzzy model of psychological rehabilitation …and diagnosis based on music psychology, designs experiments to verify the performance of this model, and conducts research results statistics from two aspects of diagnosis and rehabilitation. The research results show that the model constructed in this paper has certain practical effects. Show more

Keywords: Fuzzy model, mental health, music psychology, feature extraction

DOI: 10.3233/JIFS-219040

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2021

Authors: Xue, Kai | Liang, Xiaolin | Gao, Min

Article Type: Research Article

Abstract: Under the initiative of “co-construction and sharing, health for all”, the natural condition of coastal area in Qingdao becomes the key area of the national fitness. Based on the health-oriented theory, authors analyze the health-oriented connotation of the coastal fitness environment, and suggest that the realization of health-oriented coastal fitness environment needs to meet the spatial demand of health-oriented behaviors and health behaviors. These behaviors should maintain accessibility and friendliness. Based on the present status survey and IPA analysis, it is concluded that the continuity and gradual changes are in urgent need of improvement, followed by smoothness, then convenience and …recognizability need to update. Therefore, in combination with the acceptable time and distance, authors put forward specific optimization strategies from four aspects. That is, coastal fitness environment in Qingdao can be improved by network of coastal footpaths, intelligent management of color lightings, reasonable connecting of road materials and humanized and recognizable fitness site, in order to promote residents’ health activities and national fitness. Show more

Keywords: Health orientation, Coastal areas in Qingdao, Fitness environment, Optimization strategies

DOI: 10.3233/JIFS-219025

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2021

Authors: Hsu, Ching-Hsien | Alavi, AmAmir H. | Dong, Mianxiong | Manogaran, Gunasekaran

Article Type: Editorial

DOI: 10.3233/JIFS-219007

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-2, 2021

Authors: Ma, Shunjiang | Liu, Gaicheng | Huang, Zhiwu

Article Type: Research Article

Abstract: With the development of sports in colleges and universities, the research on innovation reform of sports industry has been deepened. Therefore, based on the above situation, a study of the status quo and development direction of sports industry in colleges and universities based on the Euclid algorithm is proposed. In the research here, according to the traditional sports industry concept to sum up, and then according to the advantages of computer technology to deal with the relevant data. In order to realize good overlap between data, an application of Euclidean algorithm is proposed. In the test of Euclidean algorithm, the …efficiency and function of the algorithm are tested comprehensively, and the test results show that the research is feasible. Show more

Keywords: Euclid algorithm, University sports, innovative measures, development direction

DOI: 10.3233/JIFS-219032

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2021

Authors: Noon, Serosh Karim | Amjad, Muhammad | Ali Qureshi, Muhammad | Mannan, Abdul

Article Type: Research Article

Abstract: Cotton is an important commodity because of its use in various industries across the globe. It is grown in many countries and is imported/exported as a cash crop due to its large utility. However, cotton yield is adversely affected by the existence of pests, viruses and pathogenic bacteria, etc. For the last one decade or so, several image processing/deep learning-based automatic plant leaf disease recognition methods have been developed but, unfortunately, they rarely address the cotton leaf diseases. The proposed work presents a simple yet efficient deep learning-based framework to recognize cotton leaf diseases. The proposed model is capable of …achieving the near ideal accuracy with early convergence to save computational cost of training. Further, due to the unavailability of publicly available datasets for this crop, a dataset is also collected comprising of three diseases namely curl virus, bacterial blight and fusarium wilt in addition to the healthy leaf Images. These images were collected from the Internet and fields of Southern Punjab region in Pakistan where the cotton crop is grown on thousands of acres every year and is exported to the Europe and the US either as a raw material or in the form of knitted industrial/domestic products. Experimental results have shown that almost all variants of our proposed deep learning framework have shown remarkably good recognition accuracy and precision. However, proposed EfficientNet-B0 model achieves 99.95% accuracy in only 152 seconds with best generalization and fast inference. Show more

Keywords: Cotton leaf disease, efficientnet, mobilenet, deep leaning, agriculture

DOI: 10.3233/JIFS-210516

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2021

Authors: Zhang, Ping | Nan Wang, Shiwei

Article Type: Research Article

Abstract: In order to analyze the volatility spillover effect between foreign exchange and stock market, this paper adopts the wavelet multi-resolution analysis method of computer simulation. Firstly, aiming at the problem of high and low frequency oscillation and exchange rate de-noising, we adopts the generalized autoregressive conditional heteroskedasticity (GARCH) model to carry out the oscillation correction and exponential modification of the exchange rate denoising signal based on wavelet multi-resolution, and carries out the corresponding decomposition and fitting combined with the wavelet multi-resolution of the state transition GARCH. Then, through the computer simulation of the modified wavelet multi-resolution analysis, this paper studies …the volatility spillover effect between the foreign exchange market and the stock market from different scales, so as to explore the simultaneous research from the time domain and frequency domain. The empirical results show that the low-frequency signals of RMB exchange rate volatility (RMB-ERV) and stock price volatility (SPV) have co-integration relationship. It is unique in that the volatility spillover effect in different trading cycles is inconsistent: in the short term, it is mainly manifested in the volatility spillover from the stock market (VS-SM) to the foreign exchange market (VS-FEM); and with the extension of the trading cycle, it shows both sides of effects on the VS. Show more

Keywords: Computer simulation, wavelet multi-resolution analysis, exchange rate denoising, stocks, foreign exchanges, market volatility spillover effect

DOI: 10.3233/JIFS-219034

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2021

Authors: Zhongyang, Rao | Chunyuan, Feng

Article Type: Research Article

Abstract: In winter, driving is a difficult due to road icing. It is one of the most unfavorable weather conditions that endangers traffic safety. We gathered data on pavement temperature, freezing point temperature, friction coefficient, pavement water film thickness, ice content, and pavement condition using sensors. Those data are feed into Long Short-Term Memory (LSTM) to predict road icing in the city. Here the primary issue is forecasting the pavement icing of the traffic zone. Our work is an endeavor to use the deep learning method on LSTM to forecast pavement icing on Ji’nan in China. Those Sequential data of pavement …icing can process and memorize by LSTM at a specific time. Finally, research results indicate that the performance of the model is very precise. With LSTM model parameters’ help, the sequential data on road icing prediction can also predict the pavement temperature. Show more

Keywords: Long short-term memory, pavement icing forecasting, deep learning, pavement temperature

DOI: 10.3233/JIFS-219022

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2021

Authors: Wang, H.Y. | Wang, J.S. | Zhu, L.F.

Article Type: Research Article

Abstract: Fuzzy C-means (FCM) clustering algorithm is a widely used method in data mining. However, there is a big limitation that the predefined number of clustering must be given. So it is very important to find an optimal number of clusters. Therefore, a new validity function of FCM clustering algorithm is proposed to verify the validity of the clustering results. This function is defined based on the intra-class compactness and inter-class separation from the fuzzy membership matrix, the data similarity between classes and the geometric structure of the data set, whose minimum value represents the optimal clustering partition result. The proposed …clustering validity function and seven traditional clustering validity functions are experimentally verified on four artificial data sets and six UCI data sets. The simulation results show that the proposed validity function can obtain the optimal clustering number of the data set more accurately, and can still find the more accurate clustering number under the condition of changing the fuzzy weighted index, which has strong adaptability and robustness. Show more

Keywords: Fuzzy C-means clustering algorithm, clustering validity function, membership matrix, intra-class compactness, inter-class separation

DOI: 10.3233/JIFS-210555

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-22, 2021

Authors: Bao, Rong | Lin, Jun

Article Type: Research Article

Abstract: This paper takes 11-year 5-minute high-frequency trading data of the Shanghai and Shenzhen 300 Index (CSI300) as a research sample. First, it proposes a method to define the normal state and the state of attention of the financial market based on multi-fractal characteristics, and randomly owes it Sampling (RU), synthetic minority oversampling (SMOTE) and traditional support vector machine (SVM) are combined to propose an improved SVM model—RU-SMOTE-SVM model to predict extreme risks in China’s financial market, and compare Traditional SVM, SMOTE-SVM, RU-SMOTE-NN and RU-SMOTE-DT are compared. The empirical results show that the price fluctuations of China’s emerging financial markets have …significant multi-fractal characteristics; the normal and concerned states defined based on the multi-fractal feature parameters are not only accurate, but also have obvious statistical test significance and clear practical significance; and traditional SVM and Compared with BP neural network (NN), RU-SMOTE-SVM is not only significantly higher in prediction accuracy, but also in terms of prediction stability. That is, RU-SMOTE-SVM can effectively solve the problems of other early warning models to solve the symmetrical sample problem. Show more

Keywords: Multifractal financial market, asymmetric samples, risk warning, RU-SMOTE-SVM model

DOI: 10.3233/JIFS-219020

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2021

Authors: Liu, Jinpei | Shao, Longlong | Zhou, Ligang | Jin, Feifei

Article Type: Research Article

Abstract: Faced with complex decision problems, Distribution linguistic preference relation (DLPR) is an effective way for decision-makers (DMs) to express preference information. However, due to the complexity of the decision-making environment, DMs may not be able to provide complete linguistic distribution for all linguistic terms in DLPRs, which results in incomplete DLPRs. Therefore, in order to solve group decision-making (GDM) with incomplete DLPRs, this paper proposes expected consistency-based model and multiplicative DEA cross-efficiency. For a given incomplete DLPRs, we first propose an optimization model to obtain complete DLPR. This optimization model can evaluate the missing linguistic distribution and ensure that the …obtained DLPR has a high consistency level. And then, we develop a transformation function that can transform DLPRs into multiplicative preference relations (MPRs). Furthermore, we design an improved multiplicative DEA model to obtain the priority vector of MPR for ranking all alternatives. Finally, a numerical example is provided to show the rationality and applicability of the proposed GDM method. Show more

Keywords: Group decision making, distribution linguistic preference relation, incomplete distribution linguistic preference relation, expected consistency, multiplicative DEA cross-efficiency

DOI: 10.3233/JIFS-210148

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-21, 2021

Authors: Liu, Rui-Lin | Yang, Hai-Long | Zhang, Li-Juan

Article Type: Research Article

Abstract: This paper studies information structures in a fuzzy β -covering information system. We introduce the concepts of a fuzzy β -covering information system and homomorphism between them, and investigate related properties. The concept of information structure of a fuzzy β -covering information system is given. We discuss the relationships between information structures from the view of dependence and separation. Then granularity measures for a fuzzy β -covering information system are studied. Finally, we discuss invariance of fuzzy β -covering information systems under homomorphism and illustrate its application on data compression.

Keywords: Fuzzy β-covering, fuzzy β-covering information system, information structure, homomorphism, invariance property

DOI: 10.3233/JIFS-202824

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-26, 2021

Authors: liang, Taixin | liu, Shifeng

Article Type: Research Article

Abstract: The rapid increase of China’s railway mileage and the effective release of transport capacity provide a basis for the development of tourist-dedicated train. Considering the decision-making between the railway enterprises and the local government on whether the tourist-dedicated train stops at the local station, the length of stay and the market price, the model of its operation plan is designed to solve algorithm problem and provide foundation for railway enterprises to improve the efficiency of operation. Based on the results of experiments, we found that the price sensitivity of consumers is negatively correlated with the pricing and income of tourist-dedicated …train. The higher the sensitivity of prices is, the lower the fares and profits of the tourist railways service will realize. In addition, the initial scale of tourism demand of each region along the railway has a direct impact on whether to build a stop in the area. A larger demand scale will increase the possibility of the tourist-dedicated train stopping. In this case, to develop the Mid-and High Tier tourist-dedicated train, the close contact and strategic cooperation with local governments before its opening should be traded-off and considered as important factors for the China National Rail. Show more

Keywords: Tourist dedicated train, decision-making model, game theory

DOI: 10.3233/JIFS-189966

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-10, 2021

Authors: Wang, Zhonghuai | Cheng, Guoping | Xiong, Yu

Article Type: Research Article

Abstract: In the increasingly competitive society, the supply chain, as the third profit center of the enterprise, makes scholars and industry-related with supply chain more and more interesting in the study of relevant issues. Exiting studies believed that an application of predictive analytics could be a tremendous impact on supply chain management. The uncertainty of supply chain demand and bullwhip effect is a challenge in the supply chain. Data fusion can effectively reduce the uncertainty of demand and the amplification effect. In this study, a new conceptual model was established on the traditional supply chain based on data fusion. Results show …that the conceptual model refers to data fusion for solving the uncertain and inconsistent multi-source data by Bayesian estimation and to providing reasonable decision information for supply chain managers. Show more

Keywords: Data Fusion, Bayesian estimation, demand forecasting, supply chain, conceptual model

DOI: 10.3233/JIFS-189947

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-7, 2021

Authors: Shuai, Fu | Kai, Sheng | Qingmin, Si | Xinyao, Guo | Feiyin, Wang

Article Type: Research Article

Abstract: Fatigue failure issues of runway at airports have become one of core tasks in airport safety management. How to recognize fatigue failure risk factors of concrete runways at airports and implement a quantitative assessment on failure risks of runways is a key topic that is studied in the industrial circle and academic circle at present. For this reason, an integral analysis on internal and external causes of fatigue failure of runways was carried out, which recognized and extracted 18 risk factors. Evaluation values of quantitative risk factors were calculated through a threshold method and evaluation values of qualitative factors were …determined by expert scoring. Subsequently, weights of all risk factors were given by G1 method. Finally, the comprehensive risk evaluation value of concrete runways was gained through layer-by-layer coupling. A case study was carried out in the A airport. Results show that the calculated comprehensive risk evaluation value of fatigue failure of concrete runways at airports by the proposed method is basically consistent with engineering objective practical value. The proposed method is expected to be applicable in other airports. The comprehensive risk evaluation value of the concrete runway failure at A airport is 0.49, indicating certain risks of fatigue failure. It is necessary to adopt engineering and management measures according to risk factors with large evaluation values to control the fatigue failure risks. This study concludes that the proposed fatigue failure risk index system of concrete runway of airports is scientific and effective. Moreover, the proposed risk evaluation method is feasible and it provides a new idea and method to fatigue failure risk evaluation of concrete runways at airports. Show more

Keywords: Airport, concrete runway, fatigue failure, risk evaluation

DOI: 10.3233/JIFS-189949

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2021

Authors: Sun, Feifei

Article Type: Research Article

Abstract: With the rapid development of deep learning and parallel computing, deep learning neural network based on big data has been applied to the field of facial nerve recognition. This innovative operation has attracted extensive attention of scholars. The reason why the application of neural network is realized lies in deep learning, which can reduce the error and change the weight by means of back propagation and error optimization, so as to extract more key points and features. In spite of this, data collection and key points extraction is still a very complex problem. This paper mainly aims at the above …problems, studies the way of deep learning and information extraction and its internal structure, and optimizes its application to classroom learning, so as to provide effective help for the realization of distance education. Show more

Keywords: Facial recognition, neural network, classroom learning, expression psychology

DOI: 10.3233/JIFS-189956

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2021

Authors: Adak, Sudip | Mahapatra, G.S.

Article Type: Research Article

Abstract: This paper develops a fuzzy two-layer supply chain for manufacturer and retailer with defective and non-defective types of products. The manufacturer produces up to a specific time, including faulty and non-defective items, and after the screening, the non-defective item sends to the retailer. The retailer’s strategy is to do the screening of items received from the manufacturer; subsequently, the perfect quality items are used to fulfill the customer’s demand, and the defective items are reworked. The retailer considers that customer demand is time and reliability dependent. The supply chain considers probabilistic deterioration for the manufacturer and retailers along with the …strategies such as production rate, unit production cost, cost of idle time of manufacturer, screening, rework, etc. The optimum average profit of the integrated model is evaluated for both the cases crisp and fuzzy environments. Managerial insights and the effect of changes in the parameters’ values on the optimal inventory policy under fuzziness are presented. Show more

Keywords: Two-layer supply chain, deterioration, imperfect items, trapezoidal fuzzy number, reliability, advertisement

DOI: 10.3233/JIFS-200562

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2021

Authors: Ya-Na, Wang | Guo-Hua, Zhou

Article Type: Research Article

Abstract: The aim of this paper is to investigate a profit-maximization firm how to determine the composition and prices of multiple bundles. Bundles are sets of components that must meet some technical constraints; furthermore, customers differ in their quality valuations and choose the bundle that maximizes their utility. A mixed integer non-linear program is proposed to solve this problem. First, a two-step approach is employed to obtain the firm’s optimal decision. The result indicates that when the firm faces deterministic demand, the optimal set of bundles it offers is independent of the distribution of customer valuations and does not contain any …dominated bundle. In addition, dominated components cannot be used to construct the optimal bundles. Second, the impact of demand uncertainty on the firm’s performance is explored. The results suggest that disregarding the demand risk may result in broader assortment and suboptimal prices. Finally, numerical experiments and sensitive analysis are conducted to provide managerial insights for the pricing and composition of multiple bundles. Show more

Keywords: Vertical differentiation, uncertain demand, pricing, composition of bundle, consumer choice model

DOI: 10.3233/JIFS-202799

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-17, 2021

Authors: Yu, Xiaobing | Yu, Xianrui | Zhang, Xueying

Article Type: Research Article

Abstract: Disasters can result in substantial destructive damages to the world. Emergency plan is vital to deal with these disasters. It is still difficult for the traditional CBR to generate emergency plans to meet requirements of rapid responses. An integrated system including Case-based reasoning (CBR) and gravitational search algorithm (GSA) is proposed to generate the disaster emergency plan. Fuzzy GSA (FGSA) is developed to enhance the convergence ability and accomplish the case adaptation in CBR. The proposed algorithm dynamically updates the main parameters of GSA by introducing a fuzzy system. The FGSA-CBR system is proposed, in which fitness function is defined …based on the effectiveness of disaster emergency management. The comparison results have revealed that the proposed algorithm has good performances compared with the original GSA and other algorithms. A gas leakage accident is taken as an empirical study. The results have demonstrated that the FGSA-CBR has good performances when generating the disaster emergency plan. The combination of CBR and FGSA can realize the case adaptation, which provides a useful approach to the real applications. Show more

Keywords: Emergency plan, case-based reasoning, adaptation, gravitational search algorithm

DOI: 10.3233/JIFS-202132

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2021

Authors: Bai, Lijie | Yuan, Zhiming | Zhao, Hongtao | Zhang, Tao

Article Type: Research Article

Abstract: This paper studies the real-time trains routing and platforming problem (RT-TRPP) in railway stations that arises from the unreliable arrival times of freight trains, flexible shunting operations and dynamic station layout caused by equipment failure. The feasibility of station timetable is checked before preparing a route for a train or after updating the station layout. If the station timetable is infeasible, the reassignment of trains is triggered. After introducing a problem formulation for the RT-TRPP, we propose an Integer Linear Program (ILP) that strives to minimize the number of conflicting trains. In resulting timetable, directions, arrival and leaving time remain …the same with networks timetable to prevent traffic disturbance of neighboring territories. If the resulting timetable is still infeasible, conflicting trains are pointed out with the cause analysis. The method is tested on real-world complex station which receives always the overload of trains’ activities. The optimal full-day solution of 249 trains is obtained within 2 seconds. The efficiency of this method meets the time-critical nature of RT-TRPP. Show more

Keywords: Train platforming, train routing, traffic management, integer linear programming

DOI: 10.3233/JIFS-189998

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2021

Authors: Zeng, Shaohua | Wu, Yalan | Wang, Shuai | He, Ping

Article Type: Research Article

Abstract: The segmentation and extraction of the purple soil region from purple soil color image can effectively avoid the influence of background on recognition of soil types. A scale weighted fuzzy c-means clustering algorithm(SWFCM) is proposed for effective segmentation of purple soil color image. The main work is to establish the maximum difference optimization model with the mean of Gaussian distance between each pixel and each peak of the image histogram, and optimize the clustering number and the initial clustering centers. Then, the dispersion of each class is defined to weight the Euclidean distance between the pixel and the clustering center …and improve the optimization model of FCM for raising its clustering performance. Aiming at the problem of removing scattered small soil blocks in the background and filling holes in the purple soil region, the algorithm of extracting the boundary of the purple soil region and the algorithm of filling the purple soil region are proposed. Finally, the normal and robust experiments are carried out on the normal sample set and robust sample set. And the performances of relative algorithms are compared, which involves the previously released FCM algorithms and some methods for the segmentation of purple soil color image and our proposed algorithm. Experimental results show that performance of SWFCM is better and it can provide a high reference for adaptive segmentation of purple soil color images. Especially for robust experiment images, its average segmentation accuracy is improved by 6 . 64% ∼ 8 . 25 % compared with other purple soil segmentation algorithms. Show more

Keywords: color image segmentation, purple soil, fuzzy c-means clustering(FCM)

DOI: 10.3233/JIFS-202401

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2021

Authors: Pei, Huili | Li, Hongliang | Liu, Yankui

Article Type: Research Article

Abstract: In practical decision-making problems, decision makers are often affected by uncertain parameters because the exact distributions of uncertain parameters are usually difficult to determine. In order to deal with this issue, the major contribution in this paper is to propose a new type of type-2 fuzzy variable called level interval type-2 fuzzy variable from the perspective of level-sets, which is a useful tool in modeling distribution uncertainty. With our level interval type-2 fuzzy variable, we give a method for constructing a parametric level interval (PLI) type-2 fuzzy variable from a nominal possibility distribution by introducing the horizontal perturbation parameters. The …proposed horizontal perturbation around the nominal distribution is different from the vertical perturbation discussed in the literature. In order to facilitate the modeling in practical decision-making problems, for a level interval type-2 fuzzy variable, we define its selection variable whose distribution can be determined via its level-sets. The numerical characteristics like expected value and second order moments are important indices in practical optimization and decision-making problems. With this consideration, we establish the analytical expressions about the expected values and second order moments of the selection variables of PLI type-2 trapezoidal, normal and log-normal fuzzy variables. Furthermore, in order to derive the analytical expressions about the numerical characteristics of the selection variable for the sums of the common PLI type-2 fuzzy variables, we discuss the arithmetic about the sums of common PLI type-2 fuzzy variables. Finally, we apply the proposed optimization method to a pricing decision problem to demonstrate the efficiency of our new method. The computational results show that even a small perturbation of the nominal possibility distribution can affect the quality of solutions. Show more

Keywords: Level interval type-2 fuzzy variable, Selection variable, Second order moments, Pricing decision

DOI: 10.3233/JIFS-202421

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2021

Authors: Qingliang, Meng | Yi, Hang | Xiaojun, Chen | Qiaoyi, CAO

Article Type: Research Article

Abstract: As a new business model, crowdsourcing innovation is widely used for enterprises to complete innovation tasks by the external crowds. The enterprises, the external crowds, and the crowdsourcing platform make an alliance and co-create value to achieve the multi-win goal. Based on the operation process analysis of the third-party platform crowdsourcing innovation model, this paper proposes that the essence of crowdsourcing innovation is the value co-creation of multi-agent participation. Based on grounded theory, this paper constructs the theoretical model of the realization mechanism of multi-agent participation value co-creation in crowdsourcing innovation from the three parties’ perspective. This research finds that …value co-creation factors include six factors: task attributes, incentive mechanisms, trust mechanisms, the platform supports, participation motivation, and diversities. The process of value co-creation includes resource integration and interaction. The results of value co-creation include three elements: innovation value, knowledge value, and relationship value. Show more

Keywords: Crowdsourcing innovation, multi-agent participation, value co-creation, grounded theory

DOI: 10.3233/JIFS-189986

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2021

Authors: Wei, Qianjin | Wang, Chengxian | Wen, Yimin

Article Type: Research Article

Abstract: Intelligent optimization algorithm combined with rough set theory to solve minimum attribute reduction (MAR) is time consuming due to repeated evaluations of the same position. The algorithm also finds in poor solution quality because individuals are not fully explored in space. This study proposed an algorithm based on quick extraction and multi-strategy social spider optimization (QSSOAR). First, a similarity constraint strategy was called to constrain the initial state of the population. In the iterative process, an adaptive opposition-based learning (AOBL) was used to enlarge the search space. To obtain a reduction with fewer attributes, the dynamic redundancy detection (DRD) strategy …was applied to remove redundant attributes in the reduction result. Furthermore, the quick extraction strategy was introduced to avoid multiple repeated computations in this paper. By combining an array with key-value pairs, the corresponding value can be obtained by simple comparison. The proposed algorithm and four representative algorithms were compared on nine UCI datasets. The results show that the proposed algorithm performs well in reduction ability, running time, and convergence speed. Meanwhile, the results confirm the superiority of the algorithm in solving MAR. Show more

Keywords: Intelligent optimization, rough set theory, attribute reduction, social spider optimization, opposition-based learning

DOI: 10.3233/JIFS-210133

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2021

Authors: Jing, Zhucui | Song, Shuhong

Article Type: Research Article

Abstract: Most of numerical methods for diffusion equations, refer to vertex unknowns directly or indirectly, and their accuracy is ultimately determined by the approximation to vertex unknowns. Based on the “twin-fitting” method, a simple and high accurate treatment for the vertex unknowns is developed and is applied to the nine-point scheme for diffusion problem. Numerical experiments show that the resulting nine-point scheme is high accurate for diffusion problems with discontinuous diffusion coefficients on distorted meshes.

Keywords: Discontinuous diffusion coefficients, distorted meshes, the “twin-fitting” method, the treatment for the vertex unknowns

DOI: 10.3233/JIFS-219001

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-6, 2021

Authors: Meng, Fanzi | Zhang, Yu

Article Type: Research Article

Abstract: Regarding the increasingly severe energy crisis and environmental issues, a dynamic control of the charging and discharging of electric vehicles into the grid that is universally adapted to optimal control is proposed in this study. When the charging control system is based on the load function of the current distribution network, the electric vehicles connected to the charging station are charged and deployed, and the best fuzzy control is adopted to calculate the electric power to be transmitted to each charging hub, so as to improve the load characteristics of the regional grid to reach the grid The highest efficiency …of use. Finally, after repeated trials and studies, the orderly charging and deployment system when meeting the charging requirements of electric vehicles, the load of electric vehicles can exert its flexibility. Show more

Keywords: Electric vehicle, V2G, adaptive optimal fuzzy control, orderly dynamic control, charge and discharge control

DOI: 10.3233/JIFS-189979

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-8, 2021

Authors: Gasmi, Ibtissem | Azizi, Mohamed Walid | Seridi-Bouchelaghem, Hassina | Azizi, Nabiha | Belhaouari, Samir Brahim

Article Type: Research Article

Abstract: Context-Aware Recommender System (CARS) suggests more relevant services by adapting them to the user’s specific context situation. Nevertheless, the use of many contextual factors can increase data sparsity while few context parameters fail to introduce the contextual effects in recommendations. Moreover, several CARSs are based on similarity algorithms, such as cosine and Pearson correlation coefficients. These methods are not very effective in the sparse datasets. This paper presents a context-aware model to integrate contextual factors into prediction process when there are insufficient co-rated items. The proposed algorithm uses Latent Dirichlet Allocation (LDA) to learn the latent interests of users from …the textual descriptions of items. Then, it integrates both the explicit contextual factors and their degree of importance in the prediction process by introducing a weighting function. Indeed, the PSO algorithm is employed to learn and optimize weights of these features. The results on the Movielens 1 M dataset show that the proposed model can achieve an F-measure of 45.51% with precision as 68.64%. Furthermore, the enhancement in MAE and RMSE can respectively reach 41.63% and 39.69% compared with the state-of-the-art techniques. Show more

Keywords: Collaborative filtering, context, topic modeling, PSO, LDA, sparsity problem

DOI: 10.3233/JIFS-210331

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2021

Authors: Li, Congdong | Yu, Yinyun | Xu, Wei | Sun, Jianzhu

Article Type: Research Article

Abstract: In order to better meet customer needs and respond to market demands more quickly, mounting number of manufacturing companies have begun to bid farewell to the traditional unitary manufacturing model. The collaborative manufacturing model has become a widely adopted manufacturing model for manufacturing companies. Aiming at the problem of partner selection for collaborative manufacturing of complex products in a collaborative supply chain environment, this paper proposes a multi-objective decision-making model that comprehensively considers the maximization of the matching degree of manufacturing capacity and the profits of supply chain, and gives the modeling process and application steps in detail. The method …first uses fuzzy theory to evaluate the manufacturing capabilities of candidate collaborative manufacturing partners. Secondly, Vector Space Model (VSM) is used to calculate the matching degree of manufacturing capacity and manufacturing demand. Then, the paper studied the profit of the supply chain under the “non-cooperative” mechanism and the “revenue sharing” mechanism. Furthermore, the decision-making model is established. Finally, a simulation was carried out by taking complex product manufacturing of Gree enterprise as an example. The research results show the feasibility and effectiveness of the method. Show more

Keywords: Collaborative manufacturing, supply chain collaboration, collaborative partner selection

DOI: 10.3233/JIFS-219000

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2021

Authors: Feng, Yuting | Guo, Xuemeng | Wei, Bolu | Chen, Bingyao

Article Type: Research Article

Abstract: The Public-Private Partnership (PPP mode) has been widely used in the field of transportation infrastructure. It can relieve the debt pressure of local governments and improve the efficiency of resource allocation. However, due to the long life cycle of urban rail transit PPP projects and numerous participants, the potential risks arising from the coordination of multi-party relations have become a major obstacle to the development of urban rail transit PPP mode. Based on the perspective of the PPP project company (SPV), this paper adopts the method of fuzzy analytic hierarchy process, takes Shenzhen Metro Line 4 project as the research …object and constructs the risk index system from nine dimensions to evaluate the risks of PPP project. Political risk, legal risk and project promotion risk are the most important risk indicators, while relationship risk and force majeure risk take the lowest proportion. According to the above results, the risk management system, risk sharing scheme and countermeasures in key risk areas are proposed. The study not only applies the fuzzy analytic hierarchy process to the research of urban rail transit risks, but also provides a systematic risk assessment basis and prevention and control reference for the smooth implementation of PPP projects. Show more

Keywords: Fuzzy analytic hierarchy process, urban rail transit, PPP mode, risk evaluation

DOI: 10.3233/JIFS-189997

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2021

Authors: Xu, Honglei | Wang, Linhuan

Article Type: Research Article

Abstract: In order to improve the accuracy of dynamic detection of wind field in the three-dimensional display space, system software is carried out on the actual scene and corresponding airborne radar observation information data, and the particle swarm algorithm fuzzy logic algorithm is introduced into the wind field dynamic simulation process in three-dimensional display space, to analyze the error of the filtering result in detail, to process the hurricane Lily Doppler radar measurement data with the optimal adaptive filtering according to the error data. The three-dimensional wind field synchronous measurement data obtained by filtering was compared with three-dimensional wind field synchronous …measurement data of the GPS dropsonde in this experiment, the sea surface wind field measurement data of the multi-band microwave radiometer, and the wind field data at aircraft altitude. Show more

Keywords: Hurricane, three-dimensional wind field, airborne doppler radar, kalman filter

DOI: 10.3233/JIFS-189977

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-6, 2021

Authors: Dhanaraj, Rajesh Kumar | Lalitha, K. | Anitha, S. | Khaitan, Supriya | Gupta, Punit | Goyal, Mayank Kumar

Article Type: Research Article

Abstract: In Wireless Sensor Networks (WSNs), effective transmission with acceptable degradation in the power of sensor nodes is a key challenge. In a large network, holdup is bound to occur in communicating superfluous data. The aforementioned issues namely, energy, delay and data redundancy are interdependent on each other and a tradeoff needs to be worked out to improve the overall performance. The extant methods in the literature employ either centralized or distributed approach to select a cluster head (CH). In this paper, sink originated hybrid and dynamic clustering with routing technique is proposed. The proposed routing algorithm works based on node …handling capability of each sensor node in the selection of CH and also helps in identifying the forwarder node. In addition, processing load of a sensor node is also considered for selecting the forwarder. Both space and time correlation is used to collect data from the clusters and then aggregated to provide a proficient communication. The introduced method is evaluated with the performance of the previously available techniques like, Data Routing for In-Network Aggregation (DRINA), Efficient Data Collection Aware of Spatio-Temporal Correlation (EAST), Cluster-Based Data Aggregation (CBDA), Energy-Efficient Data Aggregation and Transfer (EEDAT), and Distributed algorithm for Integrated tree Construction and data Aggregation (DICA). Simulation parameters considered for assess ing the performance of the proposed algorithm are aggregation ratio, routing overhead, packet delivery fraction, throughput, packet delay and consumed energy. The experimental analysis of the introduced algorithm generates paramount outcome of finest aggregation quality with diverse key characteristics and circumstances as required by a sensor network. Show more

Keywords: Wireless sensor networks, clustering algorithms, spatio-temporal phenomena, correlation routing, energy efficiency

DOI: 10.3233/JIFS-201756

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2021