Journal of Intelligent & Fuzzy Systems - Volume 45, issue 3

Authors: Zheng, Zhangqi | Liu, Yongshan | Zhang, Bing | Ren, Jiadong | Zong, Yongsheng | Wang, Qian | Yang, Xiaolei | Liu, Qian

Article Type: Research Article

Abstract: A software defect is a common cyberspace security problem, leading to information theft, system crashes, and other network hazards. Software security is a fundamental challenge for cyberspace security defense. However, when researching software defects, the defective code in the software is small compared with the overall code, leading to data imbalance problems in predicting software vulnerabilities. This study proposes a heterogeneous integration algorithm based on imbalance rate threshold drift for the data imbalance problem and for predicting software defects. First, the Decision Tree-based integration algorithm was designed following sample perturbation. Moreover, the Support Vector Machine (SVM)-based integration algorithm was designed …based on attribute perturbation. Following the heterogeneous integration algorithm, the primary classifier was trained by sample diversity and model structure diversity. Second, we combined the integration algorithms of two base classifiers to form a heterogeneous integration model. The imbalance rate was designed to achieve threshold transfer and obtain software defect prediction results. Finally, the NASA-MDP and Juliet datasets were used to verify the heterogeneous integration algorithm’s validity, correctness, and generalization based on the Decision Tree and SVM. Show more

Keywords: Software defect, imbalance rate, heterogeneous, integration, threshold shift

DOI: 10.3233/JIFS-224457

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 3, pp. 4807-4824, 2023

Authors: Jin, Xiu | Li, He | Hou, Yuting

Article Type: Research Article

Abstract: Emerging markets, such as the Chinese financial market, are occasionally subject to extreme risk events that result in investor losses during the investment process. To address the challenge of investment selection amidst market fluctuations, considering the fuzzy uncertainty and tail risk compensation based on the asymmetric perspective, we propose to use the lower VaR ratio and the upper VaR ratio as investment objectives to construct a multi-period credibilistic portfolio selection model. The study reveals that the cumulative returns and terminal wealth of the constructed model surpassed those of the benchmark models, delivering greater social and economic welfare to investors. During …extreme events, investors could promptly adjust their portfolio structure to achieve higher investment returns. Investors who prefer the lower VaR ratio tend to make conservative investment decisions and allocate a higher proportion to defensive assets, such as bonds and risk-free assets. Conversely, investors who favor the upper VaR ratio are inclined to adopt aggressive investment strategies and allocate a larger proportion to high-risk stocks. The findings demonstrate that the proposed model offers differentiated investment decisions, and the research conclusions serve as valuable references for investors engaged in multi-period asset allocation and risk management. Show more

Keywords: Lower VaR ratio, upper VaR ratio, multi-period portfolio selection, generalized fuzzy numbers, credibility measure

DOI: 10.3233/JIFS-224517

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 3, pp. 4825-4845, 2023

Authors: Onat Bulak, Fatma | Bozkurt, Hacer

Article Type: Research Article

Abstract: In this study, we define soft quasilinear functionals on soft normed quasilinear spaces and we examine some of its qualities. By using the soft quasilinear operator defined in [6 ] we specify and prove some theorem related to the continuity and boundedness of soft quasilinear operators and functionals. Furthermore, we give some examples in favor of the soft quasilinear functionals.

Keywords: Soft set, soft quasilinear space, soft normed quasilinear space, soft quasilinear operator, soft quasilinear functional

DOI: 10.3233/JIFS-230035

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 3, pp. 4847-4856, 2023

Authors: Zhang, Hengshan | Wang, Yun | Chen, Tianhua

Article Type: Research Article

Abstract: Methods on the basis of the consensus reaching process are prevalent in Group Decision Making (GDM), which typically forces some evaluators to revise initial opinions in order to reach group consensus without being able to precisely reflect original viewpoints. Furthermore, in case the correct opinion is embedded in the hand of the minority, existing methods may not reach the correct consensus. With the aim to tackle these observations, a novel approach of the Positive and Negative Prediction Selection Rate (PNPSR) is proposed on the basis of the Pythagorean Fuzzy Preference Relation (PFPR) which enables to present individuals’ opinions in a …pairwise manner using the linguistic preference relation. The PFPR expressed opinions then serve as input for the computation of the proposed PNPSR, the minimum of which is subsequently selected as the correct one. Finally, the full ranking of the alternatives can be calculated through the proposed iterative algorithm. In the process, the evaluators’ original opinions are not required to modify, and the correct result can be achieved when the minority evaluators provide the correct opinions. Experimental results demonstrate the efficacy of the proposed approach in comparison with two state-of-the-art methods. Show more

Keywords: Group decision making, Pythagorean fuzzy preference relation, positive and negative prediction selection rate, consensus measure, consensus reaching process

DOI: 10.3233/JIFS-230395

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 3, pp. 4857-4870, 2023

Authors: Hu, Hongqiang | Zhai, Ce | Chu, Yunxia | Feng, Jiu | Shi, Jianfeng | Liu, Xuning | Zhang, Genshan

Article Type: Research Article

Abstract: The prediction of coal and gas outburst is very necessary for the prevention of gas disaster, so an outburst prediction model coupled with feature extraction and feature weighting using optimized classifier is proposed. First, Pearson correlation coefficient(PCC) and symmetric uncertainty(SU) are employed to measure the effective information in outburst sample data. Second, Kernel principal component analysis(KPCA) and linear discriminant analysis(LDA) methods are used to extract the exiting discriminate information, and the extracted linear and nonlinear feature information can effectively reflect significant information of outburst influencing factors. Third, the combination of gradient boost decision tree(GBDT) and grey relation analysis(GRA) is used …to weight and fuse the extracted linear and nonlinear feature components, then form a new feature set as important discriminant information. Forth, the weighted and fused features of the coal and gas outburst influencing factors are used as the input of support vector machine(SVM) classifier with optimized parameters, it can classify outburst states, and the achieved classification accuracy can obtain 95%. Finally, the proposed model and the existing outburst classification models in literatures are used to predict outburst, then the experiment results verify the effectiveness of the proposed model and conclude that the performance of the proposed predication model are significant than present outburst prediction models. Show more

Keywords: Coal and gas outburst, KPCA, LDA, GBDT, GRA, SVM

DOI: 10.3233/JIFS-222979

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 3, pp. 4871-4884, 2023

Authors: Liu, Weiling | Xu, Jinliang | Ren, Guoqing | Xiao, Yanjun

Article Type: Research Article

Abstract: Due to the dynamic nature of work conditions in the manufacturing plant, it is difficult to obtain accurate information on process processing time and energy consumption, affecting the implementation of scheduling solutions. The fuzzy flexible job shop scheduling problem with uncertain production parameters has not yet been well studied. In this paper, a scheduling optimization model with the objectives of maximum completion time, production cost and delivery satisfaction loss is developed using fuzzy triangular numbers to characterize the time parameters, and an improved quantum particle swarm algorithm is proposed to solve it. The innovations of this paper lie in designing …a neighborhood search strategy based on machine code variation for deep search; using cross-maintaining the diversity of elite individuals, and combining it with a simulated annealing strategy for local search. Based on giving full play to the global search capability of the quantum particle swarm algorithm, the comprehensive search capability of the algorithm is enhanced by improving the average optimal position of particles. In addition, a gray target decision model is introduced to make the optimal decision on the scheduling scheme by comprehensively considering the fuzzy production cost. Finally, simulation experiments are conducted for test and engineering cases and compared with various advanced algorithms. The experimental results show that the proposed algorithm significantly outperforms the compared ones regarding convergence speed and precision in optimal-searching. The method provides a more reliable solution to the problem and has some application value. Show more

Keywords: Fuzzy flexible job shop scheduling, PSO, QPSO, simulated annealing, local search

DOI: 10.3233/JIFS-231640

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 3, pp. 4885-4905, 2023

Authors: Yang, Juan

Article Type: Research Article

Abstract: In order to improve the accuracy of English online course teaching effect evaluation results, a paper proposed an English online course teaching effect evaluation method based on ResNet algorithm. The effect of College English online teaching was evaluated from five aspects: pre-class preparation, teaching content, basic skills, ability training, and teaching methods. Each evaluation item was set with seven levels of scoring standards. An evaluation model of the classroom teaching effect was constructed based on convolutional neural network according to the internal relationship between facial expression recognition and classroom teaching effect evaluation. The problem of network depth deepening affecting the …accuracy of evaluation in convolutional neural network models was innovatively solved by utilizing the ResNet algorithm. The evaluation of the effectiveness of English online course teaching was achieved. The experimental results showed that this method could effectively improve the effect of English online course teaching evaluation and improve the teaching quality of English online courses. Show more

Keywords: ResNet algorithm, English online teaching, teaching evaluation, face recognition, convolutional neural network

DOI: 10.3233/JIFS-230048

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 3, pp. 4907-4916, 2023

Authors: Xu, Wan | Zhang, Yuhao | Yu, Leitao | Zhang, Tingting | Cheng, Zhao

Article Type: Research Article

Abstract: In order to solve the problem that the traditional DWA algorithm cannot have both safety and speed because of the fixed parameters in the complex environment with many obstacles, a parameter adaptive DWA algorithm (PA-DWA) is proposed to improve the robot running speed on the premise of ensuring safety. Firstly, the velocity sampling space is optimized by the current pose of the mobile robot, and a criterion of environment complexity is proposed. Secondly, a parameter-adaptive method is presented to optimize the trajectory evaluation function. When the environment complexity is greater than a certain threshold, the minimum distance between the mobile …robot and the obstacle is taken as the input, and the weight of the velocity parameter is adjusted according to the real-time obstacle information dynamically. The current velocity of the mobile robot is used as input to dynamically adjust the weight of the direction angle parameter. In the Matlab simulation, the total time consumption of PA-DWA is reduced by 47.08% in the static obstacle environment and 39.09% in the dynamic obstacle environment. In Gazebo physical simulation experiment, the total time of PA-DWA was reduced by 26.63% in the case of dynamic obstacles. The experimental results show that PA-DWA can significantly reduce the total time of the robot under the premise of ensuring safety. Show more

Keywords: Speed sampling space, parameter adaptation, DWA, local path planning

DOI: 10.3233/JIFS-221837

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 3, pp. 4917-4933, 2023

Authors: Huang, Haojian | Liu, Zhe | Han, Xue | Yang, Xiangli | Liu, Lusi

Article Type: Research Article

Abstract: Dempster-Shafer theory (DST) has attracted widespread attention in many domains owing to its powerful advantages in managing uncertain and imprecise information. Nevertheless, counterintuitive results may be generated once Dempster’s rule faces highly conflicting pieces of evidence. In order to handle this flaw, a new belief logarithmic similarity measure ( BLSM ) based on DST is proposed in this paper. Moreover, we further present an enhanced belief logarithmic similarity measure ( EBLSM ) to consider the internal discrepancy of subsets. In parallel, we prove that EBLSM satisfies several desirable properties, …like bounded, symmetry and non-degeneracy. Finally, a new multi-source data fusion method based on EBLSM is well devised. Through its best performance in two application cases, specifically those pertaining to fault diagnosis and target recognition respectively, the rationality and effectiveness of the proposed method is sufficiently displayed. Show more

Keywords: Dempster-Shafer theory, basic belief assignment, logarithmic similarity measure, belief entropy, data fusion

DOI: 10.3233/JIFS-230207

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 3, pp. 4935-4947, 2023

Authors: Park, Choonkil | Rehman, Noor | Ali, Abbas | Alahmadi, Reham A. | Khalaf, Mohammed M. | Hila, Kostaq

Article Type: Research Article

Abstract: In clasical logic, it is possible to combine the uniary negation operator ¬ with any other binary operator in order to generate the other binary operators. In this paper, we introduce the concept of (N ∗ , O , N , G )-implication derived from non associative structures, overlap function O , grouping function G and two different fuzzy negations N ∗ and N are used for the generalization of the implication p  → q  ≡ ¬ [p  ∧ ¬ (¬ p  ∨ q )] . We show that (N ∗ , O , N , G )-implication are fuzzy implication without any restricted …conditions. Further, we also study that some properties of (N ∗ , O , N , G )-implication that are necessary for the development of this paper. The key contribution of this paper is to introduced the concept of circledcircG ,N -compositions on (N ∗ , O , N , G )-implications. If ( N 1 ∗ , O ( 1 ) , N 1 , G ( 1 ) ) - or ( N 2 ∗ , O ( 2 ) , N 2 , G ( 2 ) ) -implications constructed from the tuples ( N 1 ∗ , O ( 1 ) , N 1 , G ( 1 ) ) or ( N 2 ∗ , O ( 2 ) , N 2 , G ( 2 ) ) satisfy a certain property P , we now investigate whether circledcircG ,N -composition of ( N 1 ∗ , O ( 1 ) , N 1 , G ( 1 ) ) - and ( N 2 ∗ , O ( 2 ) , N 2 , G ( 2 ) ) -implications satisfies the same property or not. If not, then we attempt to characterise those implications ( N 1 ∗ , O ( 1 ) , N 1 , G ( 1 ) ) -, ( N 2 ∗ , O ( 2 ) , N 2 , G ( 2 ) ) -implications satisfying the property P such that circledcircG ,N -composition of ( M 1 ∗ , O ( 1 ) , M 1 , G ( 1 ) ) - and ( M 2 ∗ , O ( 2 ) , M 2 , G ( 2 ) ) -implications also satisfies the same property. Further, we introduced sup-circledcircO -composition of (N ∗ , O , N , G )-implications constructed from tuples (N ∗ , O , N , G ) . Subsequently, we show that under which condition sup-circledcircO -composition of (N ∗ , O , N , G )-implications are fuzzy implication. We also study the intersections between families of fuzzy implications, including R O -implications (residual implication), (G , N )-implications, QL -implications, D -implications and (N ∗ , O , N , G )-implications. Show more

Keywords: Overlape function, grouping function, fuzzy implication, fuzzy negation

DOI: 10.3233/JIFS-222878

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 3, pp. 4949-4977, 2023