Journal of Intelligent & Fuzzy Systems - Volume 41, issue 2

Authors: Chen, Jing

Article Type: Research Article

Abstract: Efficient and reliable fresh agricultural products supply chain is the key to meet the demand of consumers for fresh agricultural products, and also the guarantee for suppliers to realize their economic benefits. Therefore, a multi-dimensional analysis model of agricultural products supply chain competition based on fuzzy mean value is proposed. Firstly, the information distribution model of multi-dimensional analysis of agricultural product supply chain competition is proposed. On this basis, the multi-dimensional analysis information scheduling fusion of agricultural product supply chain competition is processed. Then, the application of mean value fuzzy in agricultural product supply chain is analyzed. According to the …identification module of agricultural product information code, the fuzzy comprehensive evaluation model of supply chain and the mean fuzzy analytic hierarchy process, the competition of agricultural product supply chain is established Dimension analysis model. The experimental results show that the performance score of agricultural product supply chain is higher, the accuracy of supply chain information diagnosis is higher, and the clustering of agricultural product supply chain information diagnosis is better. Show more

Keywords: Mean fuzzy, agricultural product supply chain, competition multidimensional analysis model, mean fuzzy analytic hierarchy process

DOI: 10.3233/JIFS-210962

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 3591-3602, 2021

Authors: Dong, Jin | Wang, Jian | Chen, Sen

Article Type: Research Article

Abstract: Manufacturing industry is the foundation of a country’s economic development and prosperity. At present, the data in manufacturing enterprises have the problems of weak correlation and high redundancy, which can be solved effectively by knowledge graph. In this paper, a method of knowledge graph construction in manufacturing domain based on knowledge enhanced word embedding model is proposed. The main contributions are as follows: (1) At the algorithmic level, this paper proposes KEWE-BERT, an end-to-end model for joint entity and relation extraction, which superimposes the token embedding and knowledge embedding output by BERT and TransR so as to improve the effect …of knowledge extraction; (2) At the application level, knowledge representation model ManuOnto and dataset ManuDT are constructed based on real manufacturing scenarios, and KEWE-BERT is used to construct knowledge graph from them. The knowledge graph constructed has rich semantic relations, which can be applied in actual production environment. Other than that, KEWE-BERT can extract effective knowledge and patterns from redundant texts in the enterprise, which providing a solution for enterprise data management. Show more

Keywords: BERT, knowledge graph construction, TransR, manufacturing, knowledge extraction

DOI: 10.3233/JIFS-210982

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 3603-3613, 2021

Authors: Guo, Wenbo | Huang, Cheng | Niu, Weina | Fang, Yong

Article Type: Research Article

Abstract: In the software development process, many developers learn from code snippets in the open-source community to implement specific functions. However, few people think about whether these code have vulnerabilities, which provides channels for developing unsafe programs. To this end, this paper constructs a source code snippets vulnerability mining system named PyVul based on deep learning to automatically detect the security of code snippets in the open source community. PyVul builds abstract syntax tree (AST) for the source code to extract its code feature, and then introduces the bidirectional long-term short-term memory (BiLSTM) neural network algorithm to detect vulnerability codes. If …it is vulnerable code, the further constructed a multi-classification model could analyze the context discussion contents in associated threads, to classify the code vulnerability type based the content description. Compared with traditional detection methods, this method can identify vulnerable code and classify vulnerability type. The accuracy of the proposed model can reach 85%. PyVul also found 138 vulnerable code snippets in the real public open-source community. In the future, it can be used in the open-source community for vulnerable code auditing to assist users in safe development. Show more

Keywords: Open-source community, vulnerability mining, content analysis, BiLSTM

DOI: 10.3233/JIFS-211011

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 3615-3628, 2021

Authors: Atmaca, S. | Zorlutuna, I.

Article Type: Research Article

Abstract: In 2020, r-near topological spaces on Near Approximation Spaces were introduced by Atmaca [1 ]. In this study, we introduce the concept of continuity on r-near topological spaces and examine some properties of it.

Keywords: Near set, r-near topology, continuity

DOI: 10.3233/JIFS-211017

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 3629-3633, 2021

Authors: Shi, Zhanhong | Zhang, Dinghai

Article Type: Research Article

Abstract: Attribute significance is very important in multiple-attribute decision-making (MADM) problems. In a MADM problem, the significance of attributes is often different. In order to overcome the shortcoming that attribute significance is usually given artificially. The purpose of this paper is to give attribute significance computation formulas based on inclusion degree. We note that in the real-world application, there is a lot of incomplete information due to the error of data measurement, the limitation of data understanding and data acquisition, etc. Firstly, we give a general description and the definition of incomplete information systems. We then establish the tolerance relation for …incomplete linguistic information system, with the tolerance classes and inclusion degree, significance of attribute is proposed and the corresponding computation formula is obtained. Subsequently, for incomplete fuzzy information system and incomplete interval-valued fuzzy information system, the dominance relation and interval dominance relation is established, respectively. And the dominance class and interval dominance class of an element are got as well. With the help of inclusion degree, the computation formulas of attribute significance for incomplete fuzzy information system and incomplete interval-valued fuzzy information system are also obtained. At the same time, results show that the reduction of attribute set can be obtained by computing the significance of attributes in these incomplete information systems. Finally, as the applications of attribute significance, the attribute significance is viewed as attribute weights to solve MADM problems and the corresponding TOPSIS methods for three incomplete information systems are proposed. The numerical examples are also employed to illustrate the feasibility and effectiveness of the proposed approaches. Show more

Keywords: MADM, incomplete information systems, dominance relation, attribute significance

DOI: 10.3233/JIFS-211046

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 3635-3651, 2021

Authors: Wang, Zhenjie | Cui, Wenxia | Jin, Wenbin

Article Type: Research Article

Abstract: This paper mainly considers the finite-time synchronization problem of fuzzy inertial cellular neural networks (FICNNs) with time-varying delays. By constructing the suitable Lyapunov functional, and using integral inequality techniques, several sufficient criteria have been proposed to ensure the finite-time synchronization for the addressed (FICNNs). Without applying the known finite-time stability theorem, which is widely used to solve the finite-time synchronization problems for (FICNNs). In this paper, the proposed method is relatively convenient to solve finite-time synchronization problem of the addressed system, this paper extends the research works on the finite-time synchronization of (FICNNs). Finally, numerical simulations illustrated verify the effectiveness …of the proposed results. Show more

Keywords: Finite-time synchronization, complex networks, time-varying delays, integral inequality

DOI: 10.3233/JIFS-211065

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 3653-3666, 2021

Authors: Zhang, Xilong | Han, Meng | Wu, Hongxin | Li, Muhang | Chen, Zhiqiang

Article Type: Research Article

Abstract: With the rapid development of information technology, data streams in various fields are showing the characteristics of rapid arrival, complex structure and timely processing. Complex types of data streams make the classification performance worse. However, ensemble classification has become one of the main methods of processing data streams. Ensemble classification performance is better than traditional single classifiers. This article introduces the ensemble classification algorithms of complex data streams for the first time. Then overview analyzes the advantages and disadvantages of these algorithms for steady-state, concept drift, imbalanced, multi-label and multi-instance data streams. At the same time, the application fields of …data streams are also introduced which summarizes the ensemble algorithms processing text, graph and big data streams. Moreover, it comprehensively summarizes the verification technology, evaluation indicators and open source platforms of complex data streams mining algorithms. Finally, the challenges and future research directions of ensemble learning algorithms dealing with uncertain, multi-type, delayed, multi-type concept drift data streams are given. Show more

Keywords: Overview, ensemble classification, complex data streams, evaluation technology, domain data streams

DOI: 10.3233/JIFS-211100

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 3667-3695, 2021

Authors: Ye, Aihui | Zhang, Runtong | Wu, Pei | Xing, Yuping

Article Type: Research Article

Abstract: Since the information quality in the online health community is very important for users to obtain valuable health information, information quality evaluation is a necessary research that involves a multi-attribute decision-making (MADM) problem. However, few researches have been done to address both the construction of evaluation criteria and the expression and processing of fuzzy information, especially in online health community. This paper proposes a novel evaluation framework of information service quality combined principal component analysis (PCA) method with the TOPSIS method under q-rung orthopair fuzzy set (q-ROFS) environment. An accurate evaluation criteria system is optimized by the PCA method, and …the q-ROF TOPSIS method is proposed to process larger space of fuzzy evaluation information and overcome information loss and information distortion, in which a new distance measure between q-ROFSs is defined and an entropy weight model is initiated to determine the unknown weight of attribute. Moreover, a numerical example is performed to prove the practicability and superiority of the method through comparative analysis, which gives clear results of information quality evaluation of four online health communities. This research ends with fuzzy decision-making theory and application, and provides references for standardizing and improving the information quality of online health communities. Show more

Keywords: q-Rung orthopair fuzzy set, TOPSIS method, multi-attribute decision-making, entropy measure, information quality evaluation

DOI: 10.3233/JIFS-211123

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 3697-3714, 2021

Authors: Goraghani, Simin Saidi | Ali Borzooei, Rajab | Ahn, Sun Shin

Article Type: Research Article

Abstract: In recent years, A. Di Nola et al. studied the notions of MV -semiring and semimodules and investigated related results [9, 10, 12, 26 ]. Now in this paper, by using an MV -semiring and an MV -algebra, we introduce the new definition of MV -semimodule, study basic properties and find some examples. Then we study A -ideals on MV -semimodules and Q -ideals on MV -semirings, and by using them, we study the quotient structures of MV -semimodule. Finally, we present the notions of prime A -ideal, torsion free MV -semimodule and annihilator on MV -semimodule and we study …the relations among them. Show more

Keywords: MV-semiring, MV-algebra, MV-module, MV-semimodule, Q-ideal, prime A-ideal, 06D35, 16Y60

DOI: 10.3233/JIFS-211130

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 3715-3726, 2021

Authors: Preethi, P. | Asokan, R. | Thillaiarasu, N. | Saravanan, T.

Article Type: Research Article

Abstract: Classical Handwriting recognition systems depend on manual feature extraction with a lot of previous domain knowledge. It’s difficult to train an optical character recognition system based on these requirements. Deep learning approaches are at the centre of handwriting recognition research, which has yielded breakthrough results in recent years. However, the rapid growth in the amount of handwritten data combined with the availability of enormous processing power necessitates an increase in recognition accuracy and warrants further investigation. Convolutional Neural Networks (CNNs) are extremely good at perceiving the structure of handwritten characters in ways that allow for the automatic extraction of distinct …features, making CNN the best method for solving handwriting recognition problems. In this research work, a novel CNN has built to modify the network structure with Orthogonal Learning Chaotic Grey Wolf Optimization (CNN-OLCGWO). This modification is adopted for evolutionarily optimizing the number of hyper-parameters. This proposed optimizer predicts the optimal values from the fitness computation and shows better efficiency when compared to various other conventional approaches. The ultimate target of this work is to endeavour a suitable path towards digitalization by offering superior accuracy and better computation. Here, MATLAB 2018b has been used as the simulation environment to measure metrics like accuracy, recall, precision, and F-measure. The proposed CNN- OLCGWO offers a superior trade-off in contrary to prevailing approaches. Show more

Keywords: Convolutional neural networks, grey wolf optimization, orthogonal learning, chaotic map, digit recognition

DOI: 10.3233/JIFS-211242

Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 3727-3737, 2021