Journal of Intelligent & Fuzzy Systems - Volume 42, issue 4

Authors: Zhou, Wei | Jiang, Xing | Guo, Bingli | Meng, Lingyu

Article Type: Research Article

Abstract: Currently, Quality-of-Service (QoS)-aware routing is one of the crucial challenges in Software Defined Network (SDN). The QoS performances, e.g. latency, packet loss ratio and throughput, must be optimized to improve the performance of network. Traditional static routing algorithms based on Open Shortest Path First (OSPF) could not adapt to traffic fluctuation, which may cause severe network congestion and service degradation. Central intelligence of SDN controller and recent breakthroughs of Deep Reinforcement Learning (DRL) pose a promising solution to tackle this challenge. Thus, we propose an on-policy DRL mechanism, namely the PPO-based (Proximal Policy Optimization) QoS-aware Routing Optimization Mechanism (PQROM), to …achieve a general and re-customizable routing optimization. PQROM can dynamically update the routing calculation by adjusting the reward function according to different optimization objectives, and it is independent of any specific network pattern. Additionally, as a black-box one-step optimization, PQROM is qualified for both continuous and discrete action space with high-dimensional input and output. The OMNeT ++ simulation experiment results show that PQROM not only has good convergence, but also has better stability compared with OSPF, less training time and simpler hyper-parameters adjustment than Deep Deterministic Policy Gradient (DDPG) and less hardware consumption than Asynchronous Advantage Actor-Critic (A3C). Show more

Keywords: PQROM, SDN, QoS-aware routing

DOI: 10.3233/JIFS-211787

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 4, pp. 3605-3614, 2022

Authors: Chen, Lijun | Luo, Damei | Wang, Pei | Li, Zhaowen | Xie, Ningxin

Article Type: Research Article

Abstract:  An approximation space (A -space) is the base of rough set theory and a fuzzy approximation space (FA -space) can be seen as an A -space under the fuzzy environment. A fuzzy probability approximation space (FPA -space) is obtained by putting probability distribution into an FA -space. In this way, it combines three types of uncertainty (i.e., fuzziness, probability and roughness). This article is devoted to measuring the uncertainty for an FPA -space. A fuzzy relation matrix is first proposed by introducing the probability into a given fuzzy relation matrix, and on this basis, it is expanded to an FA …-space. Then, granularity measurement for an FPA -space is investigated. Next, information entropy measurement and rough entropy measurement for an FPA -space are proposed. Moreover, information amount in an FPA -space is considered. Finally, a numerical example is given to verify the feasibility of the proposed measures, and the effectiveness analysis is carried out from the point of view of statistics. Since three types of important theories (i.e., fuzzy set theory, probability theory and rough set theory) are clustered in an FPA -space, the obtained results may be useful for dealing with practice problems with a sort of uncertainty. Show more

Keywords: FPA-space, fuzzy relation, uncertainty, measure, information granulation, entropy, effectiveness

DOI: 10.3233/JIFS-211790

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 4, pp. 3615-3638, 2022

Authors: Zhao, Mujie | Zhang, Tao | Wang, Di

Article Type: Research Article

Abstract: Aiming at the nonlinear filter problem in Ultra Wide Band (UWB) navigation and position, a high-order Unscented Kalman Filter (UKF) position method is proposed. On the one hand, the position and velocity are used as state variables to establish a nonlinear filtering model based on UWB position system. On the other hand, based on the fifth order cubature transform (CT), the analytical solution of the high-order unscented Kalman filter is obtained by introducing a free parameter δ . To verify the effectiveness of the proposed method, the Time of Arrival (TOA) location method, the least square method and fifth order …CKF method are introduced as comparison methods. The simulation and experimental results show that the proposed high-order UKF method has good positioning accuracy in both static and dynamic UWB positioning methods. Show more

Keywords: UWB positioning, UKF, TOA, least square method

DOI: 10.3233/JIFS-211810

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 4, pp. 3639-3652, 2022

Authors: Ali, Zeeshan | Mahmood, Tahir | Ullah, Kifayat | Chinram, Ronnason

Article Type: Research Article

Abstract: The major contribution of this analysis is to analyze the confidence complex q-rung orthopair fuzzy weighted averaging (CCQROFWA) operator, confidence complex q-rung orthopair fuzzy ordered weighted averaging (CCQROFOWA) operator, confidence complex q-rung orthopair fuzzy weighted geometric (CCQROFWG) operator, and confidence complex q-rung orthopair fuzzy ordered weighted geometric (CCQROFOWG) operator and invented their feasible properties and related results. Future more, under the invented operators, we diagnosed the best crystalline solid from the family of crystalline solids with the help of the opinion of different experts in the environment of decision-making strategy. Finally, to demonstrate the feasibility and flexibility of the invented …works, we explored the sensitivity analysis and graphically shown of the initiated works. Show more

Keywords: Complex q-rung orthopair fuzzy sets, aggregation operators, confidence levels, decision-making methods

DOI: 10.3233/JIFS-211840

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 4, pp. 3653-3675, 2022

Authors: Gupta, Punit | Bhagat, Sanjit | Rawat, Pradeep

Article Type: Research Article

Abstract: The evolution of cloud computing is increasing exponentially which provides everything as a service. Clouds made it possible to move a huge amount of data over the networks on-demand. It removed the physical necessity of resources as resources are available virtually over the networks. Emerge of new technologies improvising the cloud system and trying to overcome cloud computing challenges like resource optimization, securities etc. Proper utilization of resources is still a primary target for the cloud system as it will increase the cost and time efficiency. Cloud is a pay-per-uses basis model which needs to perform in a flexible manner …with the increase and decrease in demand on every level. In general, cloud is assumed to be non-faulty but faulty is a part of any system. This article focuses on the hybridization of Neural networks with the harmony Search Algorithm (HSA). The hybrid approach achieves a better optimal solution in a feasible time duration in the faulty environment to improve the task failure and improve reliability. The harmony Search approach is inspired from the music improvisation technique, where notes are adjusted until perfect harmony is matched. HS (Harmony search) is chosen, as it is capable to provide an optimal solution in a feasible time, even for complex optimization problems. An ANN-HS model is introduced to achieve optimal resource allocation. The presented model is inspired by Harmony Search and ANN. The proposed model considers multi-objective criteria. The performance criteria include execution time, task failure count and power consumption(Kwh). Show more

Keywords: Cloud infrastructure, HS (Harmony Search), metaheuristic, neural network, task scheduling

DOI: 10.3233/JIFS-211846

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 4, pp. 3677-3689, 2022

Authors: Chen, Junying | Liu, Shipeng | Zhao, Liang | Chen, Dengfeng | Zhang, Weihua

Article Type: Research Article

Abstract: Since small objects occupy less pixels in the image and are difficult to recognize. Small object detection has always been a research difficulty in the field of computer vision. Aiming at the problems of low sensitivity and poor detection performance of YOLOv3 for small objects. AFYOLO, which is more sensitive to small objects detection was proposed in this paper. Firstly, the DenseNet module is introduced into the low-level layers of backbone to enhance the transmission ability of objects information. At the same time, a new mechanism combining channel attention and spatial attention is introduced to improve the feature extraction ability …of the backbone. Secondly, a new feature pyramid network (FPN) is proposed to better obtain the features of small objects. Finally, ablation studies on ImageNet classification task and MS-COCO object detection task verify the effectiveness of the proposed attention module and FPN. The results on Wider Face datasets show that the AP of the proposed method is 11.89%higher than that of YOLOv3 and 8.59%higher than that of YOLOv4. All of results show that AFYOLO has better ability for small object detection. Show more

Keywords: Small object detection, YOLOv3, DenseNet, attention mechanism, FPN

DOI: 10.3233/JIFS-211905

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 4, pp. 3691-3703, 2022

Authors: Talebi, A.A. | Muhiuddin, G. | Sadati, S.H. | Rashmanlou, Hossein

Article Type: Research Article

Abstract: Fuzzy graphs have a prominent place in the mathematical modelling of the problems due to the simplicity of representing the relationships between topics. Gradually, with the development of science and in encountering with complex problems and the existence of multiple relationships between variables, the need to consider fuzzy graphs with multiple relationships was felt. With the introduction of the graph structures, there was better flexibility than the graph in dealing with problems. By combining a graph structure with a fuzzy graph, a fuzzy graph structure was introduced that increased the decision-making power of complex problems based on uncertainties. The previous …definitions restrictions in fuzzy graphs have made us present new definitions in the fuzzy graph structure. The domination of fuzzy graphs has many applications in other sciences including computer science, intelligent systems, psychology, and medical sciences. Hence, in this paper, first we study the dominating set in a fuzzy graph structure from the perspective of the domination number of its fuzzy relationships. Likewise, we determine the domination in terms of neighborhood, degree, and capacity of vertices with some examples. Finally, applications of domination are introduced in fuzzy graph structure. Show more

Keywords: Fuzzy graph structure, μi-dominating set, μi-neighborhood, full-dominating set

DOI: 10.3233/JIFS-211923

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 4, pp. 3705-3718, 2022

Authors: Yang, Luting | Li, Yan

Article Type: Research Article

Abstract: Online shopping has gradually become an important way of consumption, and consumers are paying more and more attention to negative reviews. In order to avoid the massive amount of negative review information leading to loss of useful information, this paper proposes a method for evaluating the usefulness of negative online reviews. Firstly, the method constructs an evaluation index system for the usefulness of negative online reviews from three aspects: the form feature, text feature, and reviewer feature of negative reviews, and uses a combination weighting method based on fuzzy analytic hierarchy process (FAHP) and entropy method to determine the weight …of each index. Secondly, the usefulness ranking results of negative online reviews are obtained through the improved TOPSIS method based on the combined weighting method. Finally, the empirical analysis of the proposed model is carried out by crawling the negative online reviews of JD.com Fresh Food platform, and the improved model is compared with the traditional TOPSIS model, which proves the feasibility and effectiveness of the model. Show more

Keywords: Negative reviews, usefulness ranking, FAHP, entropy method, improved TOPSIS

DOI: 10.3233/JIFS-211928

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 4, pp. 3719-3736, 2022

Authors: Cui, ChunSheng | Cao, YanLi

Article Type: Research Article

Abstract: In order to solve the problems of weight solving and information aggregation in the Vague multi-attribute group decision-making, this paper first solves the weight of Vague evaluation value, and then fuses the information of Vague sets through evidence theory, and obtains an information aggregation algorithm for Vague multi-attribute group decision-making. Firstly, The algorithm draws on the idea of solving the weight of evidence in the improved evidence theory algorithm, and calculates the weight of Vague evaluation value, and revises the original evaluation information after obtaining the weight of each Vague evaluation value. Secondly, this algorithm analyzes the mathematical relationship between …the Vague sets and the evidence theory, and uses the evidence theory to fuse the evaluation information to obtain the final Vague evaluation value of each alternative. Finally, this algorithm uses a score function to calculate the score of each alternative to determine the best alternative. The algorithm given in the paper enables decision-makers to make rational decisions in uncertain environments, and then select the best alternative. Show more

Keywords: Vague sets, evidence theory, multi-attribute group decision-making, score function

DOI: 10.3233/JIFS-211937

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 4, pp. 3737-3747, 2022

Authors: Yang, Zuoxi | Dong, Shoubin

Article Type: Research Article

Abstract: Modeling user’s fine-grained preferences and dynamic preference evolution from their chronological behaviors are challenging and crucial for sequential recommendation. In this paper, we develop a Hierarchical Self-Attention Incorporating Knowledge Graph for Sequential Recommendation (HSRec). HSRec models not only the user’s intrinsic preferences but also the user’s external potential interests to capture the user’s fine-grained preferences. Specifically, the intrinsic interest module and potential interest module are designed to capture these two preferences respectively. In the intrinsic interest module, user’s sequential patterns are characterized from their behaviors via the self-attention mechanism. As for the potential interest module, high-order paths can be generated …with the help of the knowledge graph. Therefore, a hierarchical self-attention mechanism is designed to aggregate the semantic information of user interaction from these paths. Specifically, an entity-level self-attention mechanism is applied to capture the sequential patterns contained in the high-order paths while an interaction-level self-attention mechanism is designed to further capture the semantic information from user interactions. Moreover, according to the high-order semantic relevance, HSRec can explore the user’s dynamic preferences at each time, thus describing the user’s dynamic preference evolution. Finally, experiments conducted on three real world datasets demonstrate the state-of-the-art performance of the HSRec. Show more

Keywords: Sequential recommendation, knowledge graph, hierarchical self-attention, fine-grained preferences, dynamic preference evolution

DOI: 10.3233/JIFS-211953

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 4, pp. 3749-3760, 2022