Journal of Intelligent & Fuzzy Systems - Volume 40, issue 1

Authors: You, Shuang | Zhou, Yaping

Article Type: Research Article

Abstract: The traffic flow prediction using cellular automata (CA) is a trendy research domain that identified the potential of CA in modelling the traffic flow. CA is a technique, which utilizes the basic units for describing the overall behaviour of complicated systems. The CA model poses a benefit for defining the characteristics of traffic flow. This paper proposes a modified CA model to reveal the prediction of traffic flows at the signalised intersection. Based on the CA model, the traffic density and the average speed are computed for studying the characteristics and spatial evolution of traffic flow in signalised intersection. Moreover, …a CA model with a self-organizing traffic signal system is devised by proposing a new optimization model for controlling the traffic rules. The Sunflower Cat Optimization (SCO) algorithm is employed for efficiently predicting traffic. The SCO is designed by integrating the Sunflower optimization algorithm (SFO) and Cat swarm optimization (CSO) algorithm. Also, the fitness function is devised, which helps to guide the control rules evaluated by traffic simulation using the CA model. Thus, the cellular automaton is optimized using the SCO algorithm for predicting the traffic flows. The proposed Sunflower Cat Optimization-based cellular automata (SCO-CA) outperformed other methods with minimal travel time, distance, average traffic density, and maximal average speed. Show more

Keywords: Traffic flow prediction, signalized intersection, cellular automata, average speed, traffic density

DOI: 10.3233/JIFS-192099

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 1, pp. 1547-1566, 2021

Authors: Xin, Xian-Wei | Song, Ji-Hua | Xue, Zhan-Ao | Peng, Wei-Ming

Article Type: Research Article

Abstract: As an important expanded of the classical formal concept, the three-way formal concept analysis integrates more information with the three-way decision theory. However, to the best of our knowledge, few scholars have studied the intuitionistic fuzzy three-way formal concept analysis. This paper proposes an intuitionistic fuzzy three-way formal concept analysis model based on the attribute correlation degree. To achieve this, we comprehensively analyze the composition of attribute correlation degree in the intuitionistic fuzzy environment, and introduce the corresponding calculation methods for different situations, as well as prove the related properties. Furthermore, we investigate the intuitionistic fuzzy three-way concept lattice ((IF3WCL) …of object-induced and attribute-induced. Then, the relationship between the IF3WCL and the positive, negative and boundary domains in the three-way decision are discussed. In addition, considering the final decision problem of boundary objects, the secondary decision strategy of boundary objects is obtained for IF3WCL. Finally, a numerical example of multinational company investment illustrates the effectiveness of the proposed model. In this paper, we systematically study the IF3WCL, and give a quantitative analysis method of formal concept decision along with its connection with three-way decision, which provides new ideas for the related research. Show more

Keywords: Intuitionistic fuzzy, attribute correlation degree, IF3WCL, secondary decision, three-way decision

DOI: 10.3233/JIFS-200002

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 1, pp. 1567-1583, 2021

Authors: Zhongzheng, Xiao | Luktarhan, Nurbol

Article Type: Research Article

Abstract: A webshell is a common tool for network intrusion. It has the characteristics of considerable threat and good concealment. An attacker obtains the management authority of web services through the webshell to penetrate and control web applications smoothly. Because webshell and common web page features are almost identical, it can evade detection by traditional firewalls and anti-virus software. Moreover, with the application of various anti-detection feature hiding techniques to the webshell, it is difficult to detect new patterns in time based on the traditional signature matching method. Webshell detection has been proposed based on deep learning. First, a dataset is …opcoded, and the source code and opcode code features are fused. Second, the processed dataset is reduced using the SRNN and an attention mechanism, and the capsule network improves complete predictions for unknown pages. Experiments prove that the algorithm has higher detection efficiency and accuracy than traditional webshell detection methods, and it can also detect new types of webshell with a certain probability. Show more

Keywords: SRNN, Webshell, attention, CapsNet, opcode

DOI: 10.3233/JIFS-200314

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 1, pp. 1585-1596, 2021

Authors: Bekmezci, Ilker | Ermis, Murat | Cimen, Egemen Berki

Article Type: Research Article

Abstract: Social network analysis offers an understanding of our modern world, and it affords the ability to represent, analyze and even simulate complex structures. While an unweighted model can be used for online communities, trust or friendship networks should be analyzed with weighted models. To analyze social networks, it is essential to produce realistic social models. However, there are serious differences between social network models and real-life data in terms of their fundamental statistical parameters. In this paper, a genetic algorithm (GA)-based social network improvement method is proposed to produce social networks more similar to real-life data sets. First, it creates …a social model based on existing studies in the literature, and then it improves the model with the proposed GA-based approach based on the similarity of the average degree, the k -nearest neighbor, the clustering coefficient, degree distribution and link overlap. This study can be used to model the structural and statistical properties of large-scale societies more realistically. The performance results show that our approach can reduce the dissimilarity between the created social networks and the real-life data sets in terms of their primary statistical properties. It has been shown that the proposed GA-based approach can be used effectively not only in unweighted networks but also in weighted networks. Show more

Keywords: Genetic algorithm, social network modeling, trust network, online communities

DOI: 10.3233/JIFS-200563

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 1, pp. 1597-1608, 2021

Authors: Yang, Jie | Zhou, Wei | Li, Shuai

Article Type: Research Article

Abstract: Vague sets are a further extension of fuzzy sets. In rough set theory, target concept can be characterized by different rough approximation spaces when it is a vague concept. The uncertainty measure of vague sets in rough approximation spaces is an important issue. If the uncertainty measure is not accurate enough, different rough approximation spaces of a vague concept may possess the same result, which makes it impossible to distinguish these approximation spaces for charactering a vague concept strictly. In this paper, this problem will be solved from the perspective of similarity. Firstly, based on the similarity between vague information …granules(VIGs), we proposed an uncertainty measure with strong distinguishing ability called rough vague similarity (RVS). Furthermore, by studying the multi-granularity rough approximations of a vague concept, we reveal the change rules of RVS with the changing granularities and conclude that the RVS between any two rough approximation spaces can degenerate to granularity measure and information measure. Finally, a case study and related experiments are listed to verify that RVS possesses a better performance for reflecting differences among rough approximation spaces for describing a vague concept. Show more

Keywords: Vague sets, uncertainty measure, vague information granule, rough vague similarity, multi-granularity

DOI: 10.3233/JIFS-200611

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 1, pp. 1609-1621, 2021

Authors: Iqbal, Shahid | Ullah Khan, Hikmat | Ishfaq, Umar | Alghobiri, Mohammed | Iqbal, Saqib

Article Type: Research Article

Abstract: The social web appears to enrich human lives by providing effective applications for online social interactions. Microblogs are one of the most important applications of the social Web. The Microbloggers who influence the social community users through their content in the form of tweets are known as the influential microbloggers. The identification of such influential microbloggers has vast applications in advertising, online marketing, corporate communication, information dissemination, etc. This paper investigates the problem of identifying influential microbloggers by proposing MIPPLA (Model to identify Influential using Productivity, Popularity and Link Analysis) model which integrates the modules of Productivity and …Popularity . The Productivity module considers a micro-blogger’s activity and the Popularity module identifies a microbloggers influence in an online social community. In addition, we modify the classic PageRank by utilizing the Twitter features such as retweet, mention, and reply for ranking the influential users. The proposed approaches are evaluated using real-world social networks. The results prove that the MIPPLA model efficiently identifies and ranks the top influential users in an effective manner as compared to the existing techniques. Show more

Keywords: Social web, online social networks, microblogs, influential users, big data, data mining

DOI: 10.3233/JIFS-201036

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 1, pp. 1623-1637, 2021

Authors: Qahremani, E. | Allahviranloo, T. | Abbasbandy, S. | Ahmady, N.

Article Type: Research Article

Abstract: This paper is concerned with aspects of the analytical fuzzy solutions of the parabolic Volterra partial integro-differential equations under generalized Hukuhara partial differentiability and it consists of two parts. The first part of this paper deals with aspects of background knowledge in fuzzy mathematics, with emphasis on the generalized Hukuhara partial differentiability. The existence and uniqueness of the solutions of the fuzzy Volterra partial integro-differential equations by considering the type of [gH  - p ]-differentiability of solutions are proved in this part. The second part is concerned with the central themes of this paper, using the fuzzy Laplace transform method for …solving the fuzzy parabolic Volterra partial integro-differential equations with emphasis on the type of [gH  - p ]-differentiability of solution. We test the effectiveness of method by solving some fuzzy Volterra partial integro-differential equations of parabolic type. Show more

Keywords: Fuzzy laplace transform, generalized hukuhara partial differentiable, fuzzy parabolic volterra partial integro-differential equation, fuzzy triangular functions

DOI: 10.3233/JIFS-201125

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 1, pp. 1639-1654, 2021

Authors: Cheng, Linhai | Zhang, Yu | He, Yingying | Lv, Yuejin

Article Type: Research Article

Abstract: Classical rough set theory (RST) is based on equivalence relations, and does not have an effective mechanism when the attribute value of the objects is uncertain information. However, the information in actual problems is often uncertain, and an accurate or too vague description of the information can no longer fully meet the actual needs. Interval rough number (IRN) can reflect a certain degree of certainty in the uncertainty of the data when describing the uncertainty of the data, and can enable decision makers to make decisions more in line with actual needs according to their risk preferences. However, the current …research on rough set models (RSMs) whose attribute values are interval rough numbers is still very scarce, and they cannot analyze the interval rough number information system (IRNIS) from the perspective of similar relation. therefore, three new interval rough number rough set models (IRNRSMs) based on similar relation are proposed in this paper. Firstly, aiming at the limitations of the existing interval similarity degree (ISD), new interval similarity degree and interval rough number similarity degree (IRNSD) are proposed, and their properties are discussed. Secondly, in the IRNIS, based on the newly proposed IRNSD, three IRNRSMs based on similar class, β -maximal consistent class and β -equivalent class are proposed, and their properties are discussed. And then, the relationships between these three IRNRSMs and those between their corresponding approximation accuracies are researched. Finally, it can be found that the IRNRSM based on the β -equivalent classes has the highest approximation accuracy. Proposing new IRNRSMs based on similar relation is a meaningful contribution to extending the application range of RST. Show more

Keywords: Interval rough number, rough set model, intervals similarity degree, β-equivalent class, approximation accuracy

DOI: 10.3233/JIFS-191096

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 1, pp. 1655-1666, 2021

Authors: Sun, Kangjian | Jia, Heming | Li, Yao | Jiang, Zichao

Article Type: Research Article

Abstract: Slime mould algorithm (SMA) is a novel metaheuristic that simulates foraging behavior of slime mould. Regarding its drawbacks and properties, a hybrid optimization (BTβ SMA) based on improved SMA is proposed to produce the higher-quality optimal results. Brownian motion and tournament selection mechanism are introduced into the basic SMA to improve the exploration capability. Moreover, a local search algorithm (Adaptive β -hill climbing, Aβ HC) is hybridized with the improved SMA. It is considered from boosting the exploitation trend. The proposed BTβ SMA algorithm is evaluated in two main phases. Firstly, the two improved hybrid variants (BTβ SMA-1 and BTβ …SMA-2) are compared with the basic SMA algorithm through 16 benchmark functions. Also, the performance of winner is further evaluated through comparisons with 7 state-of-the-art algorithms. The simulation results report fitness and computation time. The convergence curve and boxplot visualize the effects of fitness. The comparison results on the function optimization suggest that BTβ SMA is superior to competitors. Wilcoxon rank-sum test is also employed to investigate the significance of the results. Secondly, the applicability on real-world tasks is proved by solving structure engineering design problems and training multilayer perceptrons. The numerical results indicate the merits of the BTβ SMA algorithm in terms of solution precision. Show more

Keywords: Slime mould algorithm, adaptive β-hill climbing, function optimization, structure engineering design, training multilayer perceptron

DOI: 10.3233/JIFS-201755

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 1, pp. 1667-1679, 2021

Authors: Khan, Asif | Li, Jian Ping | Haq, Amin Ul | Memon, Imran | Patel, Sarosh H. | ud. Din, Salah

Article Type: Research Article

Abstract: On-time recovery and treatment of disease is always desirable. The use of Machine learning in health-care has grown very fast to diagnosis the different kinds of diseases in the past few years. In such a diagnosis, past and real-time data are playing very crucial role in using data mining techniques. Still, we are lacking in diagnosing the emotional mental disturbance accurately in the early stages. Thus,the initial diagnosis of depression expressively stances a great problem for both,researchers and clinical professionals. We have addressed the said problem in our proposed work using Pipeline Machine Learning technique where people based on emotional …stages have been effectively classified into different groups in e-healthcare. To implement Hybrid classification, a well known machine learning multi-feature hybrid classifier is used by having the emotional stimulation in form of negative or positive people. In order to improve classification, an Ensemble Learning Algorithm is used which helps in choosing the more suitable features from the available genres-emotion data on online media. Additionally, Hold out validation method has been to split the dataset for training and testing of the predictive model. Further, performance evaluation measures have been applied to check the proposed system evaluation. This study is done on Genres-Tags MovieLens dataset. The experimental results show that applied ensemble method provides optimal classification performance by choosing the best subset of features. The said results proved the excellency of the proposed system which comes from the choosing most related features selected by the Integrated Learning algorithm. Additionally, suggested approach is used to accurately and effectively diagnose the depression in its early stage. It will help in recovery and treatment of depressed people. We conclude that use of the suggested method is highly suitable in all aspects of e-healthcare for depress stimulation. Show more

Keywords: Socialnetworking, human physci, retrieval-ranking, trendprediction, informationretrieval, ML, datascience

DOI: 10.3233/JIFS-201069

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 1, pp. 1681-1694, 2021