Journal of Intelligent & Fuzzy Systems - Volume 42, issue 3

Authors: Suthanthiradevi, P. | Karthika, S.

Article Type: Research Article

Abstract: Social networks have become a popular communication tool for information sharing. Twitter offers access to data and provides a significant opportunity to analyze data. During pandemics, Twitter becomes a big source for the dispersal of unverified information. In social media, it is difficult to find the sources of rumors. To tackle this problem the authors have developed a hybrid rumor centrality algorithm for rumor source detection in social networks. The authors propose an S-RSI algorithm for identifying a single rumor centre and an M-RSI algorithm for identifying the propagations of multiple rumor centres in the thread of conversation. The proposed …rumor centrality algorithm efficiently predicts the rumor disseminating possibilities in a conversation tree with the aid of graph theoretical approach. The authors have evaluated the performance of the algorithms on the PHEME dataset containing seven real-time event conversational trees based on the tweet messages. The results show that the proposed is best suitable in finding the rumor source centre with a high probability in social media during a crisis. Show more

Keywords: Social network, general tree, general graph, rumor source identifier, rumor centrality

DOI: 10.3233/JIFS-210540

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 3, pp. 1421-1431, 2022

Authors: Rashid, Ismat | Nazeer, Irfan | Rashid, Tabasam

Article Type: Research Article

Abstract: Connectivity parameters have a crucial role in the study of different networks in the physical world. The notion of connectivity plays a key role in both theory and application of different graphs. In this article, a prime idea of connectivity concepts in intuitionistic fuzzy incidence graphs (IFIGs) with various examples is examined. IFIGs are essential in interconnection networks with influenced flows. Therefore, it is of paramount significance to inspect their connectivity characteristics. IFIGs is an extended structure of fuzzy incidence graphs (FIGs). Depending on the strength of a pair, this paper classifies three different types of pairs such as an …α  - strong , β  - strong , and δ -pair. The benefit of this kind of stratification is that it helps to comprehend the fundamental structure of an IFIG thoroughly. The existence of a strong intuitionistic fuzzy incidence path among vertex, edge, and pair of an IFIG is established. Intuitionistic fuzzy incidence cut pairs (IFICPs) and intuitionistic fuzzy incidence trees (IFIT) are characterized using the idea of strong pairs (SPs). Complete IFIG is defined, and various other structural properties of IFIGs are also investigated. The proof that complete IFIG does not contain any δ -pair is also provided. A real-life application of these concepts related to the network of different computers is also provided. Show more

Keywords: Fuzzy sets, incidence graphs, fuzzy incidence graphs, intuitionistic fuzzy graph

DOI: 10.3233/JIFS-210590

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 3, pp. 1433-1443, 2022

Authors: Zhou, Lexin | Yang, Wenzhong | Wang, Ting | Wu, Yongzhi

Article Type: Research Article

Abstract: Aspect-based sentiment analysis (ABSA) contains three subtasks, namely aspect term extraction, opinion term extraction and aspect-level sentiment classification. In order to make full use of the relationship between the three subtasks, some recent studies have successfully tried to use a unified framework to solve the problem of aspect-based sentiment analysis. However, these studies have not yet integrated domain knowledge into the model. Inspired by the post-training task, we propose a joint model (RACL-BERT-PT). This model combines the pre-training model BERT-PT with domain knowledge and the unified joint training framework RACL. The experimental results show that our model has achieved better …results than previous experiments on three public data. Show more

Keywords: Aspect-based sentiment analysis, post-training, domain knowledge

DOI: 10.3233/JIFS-210632

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 3, pp. 1445-1454, 2022

Authors: Guo, Hai | Song, Yifan | Tang, Haoran | Zhao, Jingying

Article Type: Research Article

Abstract: In recent years, lakes pollution has become increasingly serious, so water quality monitoring is becoming increasingly important. The concentration of total organic carbon (TOC) in lakes is an important indicator for monitoring the emission of organic pollutants. Therefore, it is of great significance to determine the TOC concentration in lakes. In this paper, the water quality dataset of the middle and lower reaches of the Yangtze River is obtained, and then the temperature, transparency, pH value, dissolved oxygen, conductivity, chlorophyll and ammonia nitrogen content are taken as the impact factors, and the stacking of different epochs’ deep neural networks (SDE-DNN) …model is constructed to predict the TOC concentration in water. Five deep neural networks and linear regression are integrated into a strong prediction model by the stacking ensemble method. The experimental results show the prediction performance, the Nash-Sutcliffe efficiency coefficient (NSE) is 0.5312, the mean absolute error (MAE) is 0.2108 mg/L, the symmetric mean absolute percentage error (SMAPE) is 43.92%, and the root mean squared error (RMSE) is 0.3064 mg/L. The model has good prediction performance for the TOC concentration in water. Compared with the common machine learning models, traditional ensemble learning models and existing TOC prediction methods, the prediction error of this model is lower, and it is more suitable for predicting the TOC concentration. The model can use a wireless sensor network to obtain water quality data, thus predicting the TOC concentration of lakes in real time, reducing the cost of manual testing, and improving the detection efficiency. Show more

Keywords: Water quality monitoring, total organic carbon (TOC) concentration, ensemble learning, deep learning

DOI: 10.3233/JIFS-210708

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 3, pp. 1455-1482, 2022

Authors: Mehmood, Arif | Al Ghour, Samer | Abdullah, Saleem | Park, Choonkil | Rye Lee, Jung

Article Type: Research Article

Abstract: This paper concerns the study of the notion of vague soft β -open set and vague soft separation axioms in vague soft topological spaces. By using such notions and that of the vague soft pints, we study the separation axioms β i  (with  i  = 0, 1, 2, 3, 4) in vague soft topological spaces. We give some peculiar examples about them and we prove some relationships between them. The relationship of β i  (with  i  = , 1, 2, 3, 4) spaces with the closer of vague soft β -open set by means of soft points, vague soft countable …spaces and their relationship with β i  (with  i  = , 1, 2) spaces by means of soft points are addressed. In continuation, vague soft topological, vague soft inverse topological spaces properties, Bolzano Weirstrass Property(BVP) and its topological characteristics, compact spaces and sequentially compact spaces and their relationship with separation axioms by means soft points are addressed in vague soft topological spaces. Show more

Keywords: Vague soft set (VSS), vague soft point (VSP), vague soft β-open set and vague soft β-separation axioms.

DOI: 10.3233/JIFS-210828

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 3, pp. 1483-1499, 2022

Authors: Li, Maodong | Xu, Guanghui | Fu, Yuanwang | Zhang, Tingwei | Du, Li

Article Type: Research Article

Abstract: In this paper, a whale optimization algorithm based on adaptive inertia weight and variable spiral position updating strategy is proposed. The improved algorithm is used to solve the problem that the whale optimization algorithm is more dependent on the randomness of the parameters, so that the algorithm’s convergence accuracy and convergence speed are insufficient. The adaptive inertia weight, which varies with the fitness of individual whales, is used to balance the algorithm’s global search ability and local exploitation ability. The variable spiral position update strategy based on the collaborative convergence mechanism is used to dynamically adjust the search range and …search accuracy of the algorithm. The effective combination of the two can make the improved whale optimization algorithm converge to the optimal solution faster. It had been used 18 international standard test functions, including unimodal function, multimodal function, and fixed-dimensional function to test the improved whale optimization algorithm in this paper. The test results show that the improved algorithm has faster convergence speed and higher algorithm accuracy than the original algorithm and several classic algorithms. The algorithm can quickly converge to near the optimal value in the early stage, and then effectively jump out of the local optimal through adaptive adjustment, and has a certain ability to solve large-scale optimization problems. Show more

Keywords: Whale optimization algorithm, adaptive inertia weight, convergence speed, variable spiral position update, cooperative convergence mechanism

DOI: 10.3233/JIFS-210842

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 3, pp. 1501-1517, 2022

Authors: Xu, Xinliang | Yan, Fu

Article Type: Research Article

Abstract: Autonomous groups of particles swarm optimization (AGPSO), inspired by individual diversity in biological swarms such as insects or birds, is a modified particle swarm optimization (PSO) variant. The AGPSO method is simple to understand and easy to implement on a computer. It has achieved an impressive performance on high-dimensional optimization tasks. However, AGPSO also struggles with premature convergence, low solution accuracy and easily falls into local optimum solutions. To overcome these drawbacks, random-walk autonomous group particle swarm optimization (RW-AGPSO) is proposed. In the RW-AGPSO algorithm, Levy flights and dynamically changing weight strategies are introduced to balance exploration and exploitation. The …search accuracy and optimization performance of the RW-AGPSO algorithm are verified on 23 well-known benchmark test functions. The experimental results reveal that, for almost all low- and high-dimensional unimodal and multimodal functions, the RW-AGPSO technique has superior optimization performance when compared with three AGPSO variants, four PSO approaches and other recently proposed algorithms. In addition, the performance of the RW-AGPSO has also been tested on the CEC’14 test suite and three real-world engineering problems. The results show that the RW-AGPSO is effective for solving high complexity problems. Show more

Keywords: Autonomous groups of particle swarm optimization, particle swarm optimization, levy flights, dynamically changing weight, function optimization

DOI: 10.3233/JIFS-210867

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 3, pp. 1519-1545, 2022

Authors: Chen, Kuen-Suan | Yu, Chun-Min

Article Type: Research Article

Abstract: Industry 4.0 has fostered innovation in industries around the world. Manufacturing industries in particular are advancing towards smart manufacturing by integrating and applying relevant technologies. The output value of machine tools in Taiwan is among the top of the world and the central region is a key area for this industry chain, which supplies manufacturers in Taiwan and their international downstream customers. To support innovation in this industry, the current study used the Six Sigma quality indices for smaller-the-better, larger-the-better, and nominal-the-best quality characteristics to construct a fuzzy decision-making model. Based on this model, we propose a process quality fuzzy …analysis chart (PQFAC) for process quality improvement. Our use of fuzzy decision values to replace lower confidence limits decreases the probability of misjudgment made by sampling errors. The proposed fuzzy model also offers a more accurate assessment of process improvement requirements. We provide a real-world example to demonstrate the applicability of the proposed approach. Machine tool manufacturers can apply the platform and proposed model to evaluate their process capabilities for the vital parts suppliers and downstream customers, determine optimal machine parameter settings for processes with inadequate accuracy or precision, establish more suitable machine repair and maintenance systems, and combine the improvement experiences of customers to create an improvement knowledge base. This will enhance product value and industry competitiveness for the entire machine tool industry chain. Show more

Keywords: Fuzzy decision-making model, six sigma quality index, quality characteristic, production data, process quality fuzzy analysis chart

DOI: 10.3233/JIFS-210868

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 3, pp. 1547-1558, 2022

Authors: Zhang, Jun | Qin, Yanping | Zhang, Xinyu | Che, Gen | Sun, Xuan | Duo, Huaqiong

Article Type: Research Article

Abstract: Non-equidistant GM(1,1) (abbreviated as NEGM) model is widely used in building settlement prediction because of its high accuracy and outstanding adaptability. To improve the building settlement prediction accuracy of the NEGM model, the fractional-order non-equidistant GM(1,1) model (abbreviated as FNEGM) is established in this study. In the modeling process of the FNEGM model, the fractional-order accumulated generating sequence is extended based on the first-order accumulated generating sequence, and the optimal parameters that increase the prediction precision of the model are obtained by using the whale optimization algorithm. The FNEGM model and the other two grey prediction models are applied to …three cases, and five prediction performance indexes are used to evaluate the prediction precision of the three models. The results show that the FNEGM model is more suitable for predicting the settlement of buildings than the other two grey prediction models. Show more

Keywords: Non-equidistant GM(1, 1) model, fractional-order accumulation, grey prediction model

DOI: 10.3233/JIFS-210936

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 3, pp. 1559-1573, 2022

Authors: Xu, Guoteng | Lu, Tingjie | Chen, Xia | Liu, Yiman

Article Type: Research Article

Abstract: The paper constructs a research model mainly based on the Deng’s correlation analysis model on the convergence level measurement, the GM (1,1) coordinated development prediction model and PLS-Structural Equation Model (PLS-SEM) analysis model on the influencing factors. The data about China’s digital economy and real economy from 2005 to 2019 (totaled 2,250) is adopted to conduct an empirical analysis of the convergence level from 2005 to 2019 and predict the development trend from 2020 to 2029. The paper could further analyze the influencing factors of convergence, in an attempt to put forward relevant development suggestions. We hope the study could …provide an objective reference and theoretical basis for improving the convergence level in China in some extent. Show more

Keywords: Grey model, PLS-structural equation model, convergence of digital economy and real economy, influencing factors

DOI: 10.3233/JIFS-210981

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 3, pp. 1575-1605, 2022