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

Authors: Yang, Songyue | Yu, Guizhen | Meng, Zhijun | Wang, Zhangyu | Li, Han

Article Type: Research Article

Abstract: In the intelligent unmanned systems, unmanned aerial vehicle (UAV) obstacle avoidance technology is the core and primary condition. Traditional algorithms are not suitable for obstacle avoidance in complex and changeable environments based on the limited sensors on UAVs. In this article, we use an end-to-end deep reinforcement learning (DRL) algorithm to achieve the UAV autonomously avoid obstacles. For the problem of slow convergence in DRL, a Multi-Branch (MB) network structure is proposed to ensure that the algorithm can get good performance in the early stage; for non-optimal decision-making problems caused by overestimation, the Revise Q-value (RQ) algorithm is proposed to …ensure that the agent can choose the optimal strategy for obstacle avoidance. According to the flying characteristics of the rotor UAV, we build a V-Rep 3D physical simulation environment to test the obstacle avoidance performance. And experiments show that the improved algorithm can accelerate the convergence speed of agent and the average return of the round is increased by 25%. Show more

Keywords: UAV, obstacle avoidance, DQN, overestimation, convergence rate

DOI: 10.3233/JIFS-211192

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 4, pp. 3323-3335, 2022

Authors: Zhu, Wuqiang | Lu, Yang | Zhang, Yongliang | Wei, Xing | Wei, Zhen

Article Type: Research Article

Abstract: End-to-end deep learning has gained considerable interests in autonomous driving vehicles. End-to-end autonomous driving uses the deep convolutional neural network to establish input-to-output mapping. However, existing end-to-end driving models only predict steering angle with front-facing camera data and poorly extract spatial-temporal information. Based on deep learning and attention mechanism, we propose an end-to-end driving model which combines the multi-stream attention module with the multi-stream network. As a multimodal multitask model, the proposed end-to-end driving model not only fully extracts spatial-temporal information from multimodality, but also adopts the multitask learning method with hard parameter sharing to predict the steering angle and …speed. Furthermore, the proposed multi-stream attention module predicts the attention weights of streams based on the multimodal feature fusion, which encourages the proposed end-to-end driving model to pay attention to streams that positively impact the prediction result. We demonstrate the efficiency of the proposed driving model on the public Udacity dataset compared to existing models. Experimental results show that the proposed driving model has better performances than other existing methods. Show more

Keywords: End-to-end autonomous driving, attention mechanism, multimodal, multitask

DOI: 10.3233/JIFS-211206

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 4, pp. 3337-3348, 2022

Authors: Işık, Gürkan | Kaya, İhsan

Article Type: Research Article

Abstract: Although traditional acceptance sampling plans (ASPs) need certain mass quality characteristics, it is not easy to define them as crisp value in some real case problems. The fuzzy set theory (FST) is one of the popular techniques to model uncertainties of the process and therefore fuzzy ASPs have been offered in the literature. Fuzzy set extensions have been proposed recently for better modeling of the uncertainties having different sources and characteristics. One of these extensions named neutrosophic sets (NSs) can be used to increase the sensitiveness and flexibility of ASPs. The ASPs based on NSs can give ability to classify …the items as defective, non-defective and indeterminate. Since the operator can become indecisive for slightly defective items, these plans can provide a good representation of human evaluations under uncertainty. In this study, single and double ASPs are designed based on NSs by using binomial and poisson distributions that are also re-analyzed based on NSs. For this aim, some characteristics functions of ASPs such as probability of accepting a lot (P a ), average outgoing quality (AOQ ), average total inspection (ATI ) and average sample number (ASN ) have also been analyzed based on NSs. Numerical examples are presented to analyze the proposed plans. Show more

Keywords: Acceptance sampling plans, fuzzy sets, neutrosophic sets, neutrosophic poisson distribution

DOI: 10.3233/JIFS-211232

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 4, pp. 3349-3366, 2022

Authors: Khalil, Ahmed Mostafa

Article Type: Research Article

Abstract: In this article, we will define the new notions (e.g., semi-θ-neighbor-hood system of point, semi-θ-closure (interior) of a set and semi-θ-closed (open) set) based on fuzzy logic (i.e., fuzzifying topology). Then, we will explain the interesting properties of above five notions in detail. Several basic results (for instance, Definition 2.3, Theorem 2.5 (iii), (v) and (vi), Theorem 2.10, Theorem 2.14 and Theorem 4.6) in classical topology are generalized to the fuzzy case based on Łukasiewicz logic. In addition to, we will show that every fuzzifying semi-θ-closed set is fuzzifying semi-closed set (by Theorem 2.5 (vi)). Further, we will study the …notion of fuzzifying semi-θ-derived set and fuzzifying semi-θ-boundary set, and discuss several of their fundamental basic relations and properties. Also, we will present a new type of fuzzifying strongly semi-θ-continuous mapping between two fuzzifying topological spaces. Finally, several characterizations of fuzzifying strongly semi-θ-continuous mapping, fuzzifying strongly semi-θ-irresolute mapping, and fuzzifying weakly semi-θ-irresolute mapping along with different conditions for their existence are obtained. Show more

Keywords: Fuzzy logic, fuzzifying topology, fuzzifying semi-θ-closure of a set, fuzzifying semi-θ-closed sets, fuzzifying strongly semi-θ-continuous mapping

DOI: 10.3233/JIFS-211301

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 4, pp. 3367-3379, 2022

Authors: Gong, Zengtai | Xiao, Zhiyong

Article Type: Research Article

Abstract: This article has been retracted. A retraction notice can be found at https://doi.org/10.3233/JIFS-219433 .

DOI: 10.3233/JIFS-211306

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 4, pp. 3381-3391, 2022

Authors: Cai, Qian | Xiong, Xingliang | Gong, Weiqiang | Wang, Haixian

Article Type: Research Article

Abstract: BACKGROUND: Classification of action intention understanding is extremely important for human computer interaction. Many studies on the action intention understanding classification mainly focus on binary classification, while the classification accuracy is often unsatisfactory, not to mention multi-class classification. METHOD: To complete the multi-class classification task of action intention understanding brain signals effectively, we propose a novel feature extraction procedure based on thresholding graph metric. RESULTS: Both the alpha frequency band and full-band obtained considerable classification accuracies. Compared with other methods, the novel method has better classification accuracy. CONCLUSIONS: Brain activity of action intention understanding …is closely related to the alpha band. The new feature extraction procedure is an effective method for the multi-class classification of action intention understanding brain signals. Show more

Keywords: Action intention understanding, EEG, classification, feature extraction, graph metric

DOI: 10.3233/JIFS-211333

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 4, pp. 3393-3403, 2022

Authors: Jiang, Zhiwei | Wei, Guiwu | Guo, Yanfeng

Article Type: Research Article

Abstract: In the garment manufacturing industry, purchasing management is an important link. The materials of making clothes often need high cost. In addition, customers put forward a request in the quality of clothes. Thus, choosing an optimal supplier is an essential part of job. Reaching cooperation with an optimal supplier not only can help garment manufacturer improve the quality of clothes but also is benefit to reduce the cost of producing. Most importantly, it can improve the competitiveness of manufacture enterprises. So, it is important for managers to find an optimal supplier and make a cooperation with it. In this paper, …we analysis an issue about choosing an optimal supplier during four different suppliers. With analyzing this problem, we can introduce an extended method under picture fuzzy environment to evaluate and choose an optimal supplier. In this article, we describe some basic knowledges about picture fuzzy sets (PFSs) and picture fuzzy numbers (PFNs). Then, we introduce the extension of MABAC method which is on the basis of prospect theory (PT) with picture fuzzy numbers (PF-PT-MABAC) and utilize the PF-PT-MABAC model to evaluate different suppliers to choose an optimal supplier. Finally, we compare the result of PF-PT-MABAC with the result of traditional MABAC, PFWG operators and traditional TODIM method to test the efficiency of PF-PT-MABAC model. Show more

Keywords: Multiple attribute group decision making (MAGDM), picture fuzzy sets (PFSs), MABAC method, prospect theory (PT), suppliers selection

DOI: 10.3233/JIFS-211359

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 4, pp. 3405-3415, 2022

Authors: Kashif, Agha | Rashid, Tabasam | Noor, Bibi | Sindhu, Muhammad Sarwar

Article Type: Research Article

Abstract: Motivated by intuitionistic fuzzy sets and soft sets, a novel concept of lattice ordered interval-valued intuitionistic fuzzy soft sets (LOIVIFSSs) is introduced in this article. Operational rules like union, intersection, complement and some properties of LOIVIFSSs are demonstrated with examples. In this regard, an algorithm is developed to solve the multiple criteria decision-making (MCDM) problems based on LOIVIFSSs. Further, a benchmark problem concerning medical diagnosis have been investigated and a comparative analysis with existing technique is furnished to strengthen our approach.

Keywords: Fuzzy sets, intuitionistic fuzzy sets, soft sets, lattice

DOI: 10.3233/JIFS-211376

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 4, pp. 3417-3430, 2022

Authors: Jiang, Tianhua | Zhu, Huiqi | Gu, Jiuchun | Liu, Lu | Song, Haicao

Article Type: Research Article

Abstract: This paper presents a discrete animal migration optimization (DAMO) to solve the dual-resource constrained energy-saving flexible job shop scheduling problem (DRCESFJSP), with the aim of minimizing the total energy consumption in the workshop. A job-resource-based two-vector encoding method is designed to represent the scheduling solution, and an energy-saving decoding approach is given based on the left-shift rule. To ensure the quality and diversity of initial scheduling solutions, a heuristic approach is employed for the resource assignment, and some dispatching rules are applied to acquire the operation permutation. In the proposed DAMO, based on the characteristics of the DRCESFJSP problem, the …search operators of the basic AMO are discretized to adapt to the problem under study. An animal migration operator is presented based on six problem-based neighborhood structures, which dynamically changes the search scale of each animal according to its solution quality. An individual updating operator based on crossover operation is designed to obtain new individuals through the crossover operation between the current individual and the best individual or a random individual. To evaluate the performance of the proposed algorithm, the Taguchi design of experiment method is first applied to obtain the best combination of parameters. Numerical experiments are carried out based on 32 instances in the existing literature. Computational data and statistical comparisons indicate that both the left-shift decoding rule and population initialization strategy are effective in enhancing the quality of the scheduling solutions. It also demonstrate that the proposed DAMO has advantages against other compared algorithms in terms of the solving accuracy for solving the DRCESFJSP. Show more

Keywords: Dual-resource constraint, energy-saving scheduling, flexible job shop, discrete animal migration optimization

DOI: 10.3233/JIFS-211399

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 4, pp. 3431-3444, 2022

Authors: Joshi, Pallavi | Raghuvanshi, Ajay Singh

Article Type: Research Article

Abstract: The abrupt changes in the sensor measurements indicating the occurrence of an event are the major factors in some monitoring applications of IoT networks. The prediction-based approach for data aggregation in wireless sensor networks plays a significant role in detecting such events. This paper introduces a prediction-based aggregation model for sensor selection named the Grey prediction model and the Kalman filter-based data aggregation model with rank-based mutual information (GMKFDA-MI) that has a dual synchronization mechanism for aggregating the data and selecting the nodes based on prediction and cumulative error thresholds. Furthermore, the nodes after deployment are clustered using K-medoids clustering …along with the Salp swarm optimization algorithm to obtain an optimized aggregator position concerning the base station. An efficient clustering promises energy efficiency and better connectivity. The experiments are accomplished on real-time datasets of air pollution monitoring applications and the results for the proposed method are compared with other similar state-of-the-art techniques. The proposed method promises high prediction accuracy, low energy consumption and enhances the throughput of the network. The energy-saving is recorded to be more than 10 to 30% for the proposed model when compared with other similar approaches. Also, the proposed method achieves 97.8% accuracy as compared to other methods. The method proves its best working efficiency in the applications like event reporting, target detection, and event monitoring. Show more

Keywords: IoT, wireless sensor networks, data aggregation, grey model, kalman filter, mutual information, K-medoids clustering, salp swarm optimization

DOI: 10.3233/JIFS-211436

Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 4, pp. 3445-3464, 2022