Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Purchase individual online access for 1 year to this journal.
Price: EUR 315.00Impact Factor 2023: 2
The purpose of the Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology is to foster advancements of knowledge and help disseminate results concerning recent applications and case studies in the areas of fuzzy logic, intelligent systems, and web-based applications among working professionals and professionals in education and research, covering a broad cross-section of technical disciplines.
The journal will publish original articles on current and potential applications, case studies, and education in intelligent systems, fuzzy systems, and web-based systems for engineering and other technical fields in science and technology. The journal focuses on the disciplines of computer science, electrical engineering, manufacturing engineering, industrial engineering, chemical engineering, mechanical engineering, civil engineering, engineering management, bioengineering, and biomedical engineering. The scope of the journal also includes developing technologies in mathematics, operations research, technology management, the hard and soft sciences, and technical, social and environmental issues.
Authors: Uma, K. | Sathya Bama, B. | Sabarinathan, D. | Mansoor Roomi, S. Md.
Article Type: Research Article
Abstract: Plant species identification is essential for healthy survival as well as the preservation and protection of biodiversity. Manual identification is time-consuming, hence to address this issue deep learning algorithms for automated plant species identification have been developed. A Novel Architecture comprising of EfficientB4Net, Convolutional Block Attention Module (CBAM) and Residual Block Decoder is proposed to act as Autoencoder for identification and retrieval of twenty distinct groups of medicinal plants, widely available in southern India. The EfficientB4 encoder compresses and encodes the input features along with channel and spatial features to the Residual Block Decoder for efficient learning. Residual Block Decoders …work to reconstruct the data from the encoded form to be as close to the original input as possible, by eliminating noise. The information-rich encoded features and the global features from the CBAM are transferred to the fully connected layer and stored in the database for retrieval of the plants. When a query image is received, the encoded feature of the query image and the database images are compared using similarity measurement, and the related images are retrieved. From the retrieved images, the query image is identified and the experimental results clearly show that the proposed method has achieved 95% accuracy when compared with other methods. Show more
Keywords: EfficientB4Net, convolutional block attention module, residual block decoder, autoencoder, fully connected layer
DOI: 10.3233/JIFS-211426
Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5097-5112, 2022
Authors: Panda, S. | Dash, J.K. | Panda, G.B.
Article Type: Research Article
Abstract: Integral of a stochastic process with respect to Brownian motion is called Ito integral. Here the stochastic process and Brownian motion are random as well as fuzzy. Hence the Ito integral is fuzzy Ito integral. This paper deals with the properties of fuzzy Ito integral for simple adapted process with respect to fuzzy Brownian motion. The quadratic variance and covariance of FII are discussed. The concept of fuzzy simple adapted process, fuzzy martingale, fuzzy functions are used to derive the properties of fuzzy Ito integrals.
Keywords: Fuzzy Ito integral(FII), fuzzy Brownian motion(FBM), fuzzy simple adapted process(FSAP), quadratic variance and covariance of fuzzy Ito integral, fuzzy martingale(FM)
DOI: 10.3233/JIFS-211478
Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5113-5124, 2022
Authors: Qian, Zichen | Zhao, Chihang | Zhang, Bailing | Lin, Shengmei | Hua, Liru | Li, Hao | Ma, Xiaogang | Ma, Teng | Wang, Xinliang
Article Type: Research Article
Abstract: Classification of vehicle types using surveillance images is a challenging task in Intelligent Transportation Systems (ITS). In this paper, Convolutional Neural Networks for Vehicle types classification are comparatively studied. Firstly, GoogLeNet, ResNet50 and InceptionV4 are exploited as baselines for comparison. Secondly, we proposed a new network architecture based on GoogLeNet, ResNet50 and InceptionV4, named Fused Deep Convolutional Neural Networks (FDCNN), to take advantage of the ‘Inception’ module on parameter optimization and ‘Residual’ module on avoiding gradient vanishing, and applied the model to vehicle types classification. Thirdly, we created a vehicle dataset under the conditions of complicated and varied weather and …lighting conditions, and conducted comparative experiments using the SEU vehicle dataset. Experimental results show much better performance of the proposed FDCNN with RMSprop optimizer on recognizing vehicle types. Specifically, the average classification accuracies of six vehicle types, such as truck, coach, sedan, minivan, pickup and SUV, are over 96.8%. Among the six classes of vehicle types, sedan is the most difficult to classify and the proposed FDCNN achieved over 93.81% accuracy in comparative experiments. Show more
Keywords: Vehicle types, convolutional neural networks, fused deep convolutional neural networks, intelligent transportation systems
DOI: 10.3233/JIFS-211505
Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5125-5137, 2022
Authors: Brikaa, M.G. | Zheng, Zhoushun | Dagestani, Abd Alwahed | Ammar, El-Saeed | AlNemer, Ghada | Zakarya, M.
Article Type: Research Article
Abstract: The principal objective of this article is to develop an effective approach to solve matrix games with payoffs of single-valued trapezoidal neutrosophic numbers (SVTNNs). In this approach, the concepts and suitable ranking function of SVTNNs are defined. Hereby, the optimal strategies and game values for both players can be determined by solving the parameterized mathematical programming problems, which are obtained from two novel auxiliary SVTNNs programming problems based on the proposed Ambika approach. In this approach, it is verified that any matrix game with SVTNN payoffs always has a SVTNN game value. Moreover, an application example is examined to verify …the effectiveness and superiority of the developed algorithm. Finally, a comparison analysis between the proposed and the existing approaches is conducted to expose the advantages of our work. Show more
Keywords: Matrix games, neutrosophic set, mathematical programming, trapezoidal neutrosophic number, ambika approach
DOI: 10.3233/JIFS-211604
Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5139-5153, 2022
Authors: Xu, Yan | Wang, Yanyun | Huang, Jiani | Qin, Hong
Article Type: Research Article
Abstract: Traditional visual SLAM algorithms run robustly under the assumption of a static environment, but always fail in dynamic scenes, since moving objects will impair camera pose tracking. Given this, this paper presents an efficient semantic dynamic SLAM (ESD-SLAM), which is suitable for dynamic scenarios. Based on the ORB-SLAM2 framework, the ESD-SLAM we proposed employs lightweight semantic segmentation network FcHarDNet to extract semantic information, and uses the region growing algorithm to optimize the semantic segmentation boundary. Then dynamic objects are removed by combining semantic information with multi-view geometry, and it further improves the localization accuracy. Combining semantic information and depth information, …a dense point cloud map of static scene is constructed to serve the planning task of mobile robot. We conduct the experiments on the public TUM RGB-D dataset and in the real-world environment. Experimental results show that the proposed algorithm can improve the performance of the ORB-SLAM2 system in dynamic scenes, and significantly improve the real-time performance compared with other same type dynamic SLAM algorithms. Show more
Keywords: Visual SLAM, dynamic scenarios, multi-view geometry, lightweight semantic segmentation
DOI: 10.3233/JIFS-211615
Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5155-5164, 2022
Authors: Hamidi, Mohammad | Faraji, Fatemeh
Article Type: Research Article
Abstract: In this paper we introduce the concept of (weak) fuzzy subsupermodules based on (thin) supermodules different from fuzzy subhypermodules. In this study, the concept of α -cuts play a main role for constructing of extended (weak) fuzzy subsupermodules. In final, we introduce a notation of residual quotients of (weak) fuzzy subsupermodules and obtain some conditions to be a (weak) fuzzy subsupermodule. Also obtained some applied results in residual quotients of (weak) fuzzy subsupermodules of superrings as specially subsupermodules.
Keywords: Superrings, (thin) supermodule, (weak) fuzzy subsupermodules
DOI: 10.3233/JIFS-211655
Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5165-5176, 2022
Authors: Hu, Kekun | Dong, Gang | Zhao, Yaqian | Li, Rengang | Jiang, Dongdong | Chao, Yinyin | Liu, Haiwei | Ge, Yuan
Article Type: Research Article
Abstract: Vertex classification is an important graph mining technique and has important applications in fields such as social recommendation and e-Commerce recommendation. Existing classification methods fail to make full use of the graph topology to improve the classification performance. To alleviate it, we propose a D ual G raph W avelet neural N etwork composed of two identical graph wavelet neural networks sharing network parameters. These two networks are integrated with a semi-supervised loss function and carry out supervised learning and unsupervised learning on two matrixes representing the graph topology extracted from the same graph dataset, respectively. One matrix embeds the …local consistency information and the other the global consistency information. To reduce the computational complexity of the convolution operation of the graph wavelet neural network, we design an approximate scheme based on the first type Chebyshev polynomial. Experimental results show that the proposed network significantly outperforms the state-of-the-art approaches for vertex classification on all three benchmark datasets and the proposed approximation scheme is validated for datasets with low vertex average degree when the approximation order is small. Show more
Keywords: Big graph mining, vertex classification, semi-supervised learning, graph convolutional networks, graph wavelet transform
DOI: 10.3233/JIFS-211729
Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5177-5188, 2022
Authors: Gao, Pei
Article Type: Research Article
Abstract: The results of the nation-wide public college English tests and some other English tests held by the college itself are very valuable data for the assessment of the English teaching level. In the light of the selected and processed data and some other auxiliary approaches, the writer suggests that a modernized monitoring system be established to improve English teaching quality. Under this system, teachers’ and students’ English level can be evaluated in an objective way. Consequently, the subsequent measures such as teachers’ promotion as well as students’ development and employment and the evaluation of the quality of test-papers can be …taken scientifically. We can solve the above issues with help of multi-attribute group decision making (MAGDM) method. Depending on the VIKOR steps and given intuitionistic fuzzy sets (IFSs), this paper devises the IF-VIKOR to assess the teaching quality of college English. In addition, the weights of attribute are derived through CRITIC method. Then, the VIKOR method is extended to IFSs to derive the order of each alternative. Therefore, all alternatives could be ranked and the best one can be identified. Eventually, we give an example of college English teaching quality evaluation, according to some comparison with other methods to make an analysis, the results show that the method proposed in such paper is effective and easy to compute. Show more
Keywords: Multi-attribute group decision-making (MAGDM), Intuitionistic fuzzy sets (IFSs), VIKOR method, CRITIC model, teaching quality
DOI: 10.3233/JIFS-211749
Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5189-5197, 2022
Authors: Li, Jiwen | Lan, Fengchong | Chen, Jiqing
Article Type: Research Article
Abstract: In view of the disadvantages of the existing pose estimation algorithm, which has low real-time performance and the positioning accuracy will be greatly reduced in dynamic scene, a compound deep learning and parallel computing algorithm (DP-PE) is proposed. The detection algorithm based on deep learning is used to detect dynamic objects in the environment, and the dynamic feature points are removed before the matching of feature points to reduce the impact of dynamic objects on the positioning accuracy; A method for distinguishing “pseudo-dynamic objects” is proposed to solve the problem that the stationary vehicles and pedestrians in the environment are …regarded as dynamic objects. The parallel computing framework for feature point extraction and matching is established on CPU-GPU heterogeneous platform to speed up DP-PE; In the localization part of DP-PE, we propose a 3D interior point detection strategy to achieve parallel search of map points, and the saturated linear kernel function is used to act on reprojection error to realize the parallelization of pose optimization. We verify the algorithm on KITTI dataset, the experimental results show that average speedup ratio of feature point extraction and matching is 6.5 times, and the overall computational efficiency of DP-PE is about 7 times higher than that before acceleration, which can realize high precision and efficient pose estimation in dynamic scene. Show more
Keywords: Intelligent vehicle, visual pose estimation, deep learning, parallel computing
DOI: 10.3233/JIFS-211771
Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5199-5213, 2022
Authors: Xu, Juncai | Zhang, Jingkui | Shen, Zhenzhong
Article Type: Research Article
Abstract: Conventional intelligent recognition methods highly depend on artificial feature extraction and expert knowledge to recognize concrete structures’ internal defects. For solving this problem, one intelligent recognition method for internal concrete structure defects is proposed, based on a one-dimensional, convolutional neural network (1D-CNN). First, the impact echo detection signals are acquired, to establish the training and testing of samples for various internal concrete structure defects. Then, the convolutional network structure is used to achieve the adaptive, hierarchical extraction of the impact echo signals’ features. Finally, the Softmax classifier is used to provide the diagnosis result at the output end. The experimental …results of four types of internal defects (including voids, water-filled, imperfect solids, and sound) show that the 1D-CNN classifier, with the predicted signals as the training set, enables the successful identification of the internal defects of the concrete structure and achieves more than 90% defect-recognition accuracy. In addition, the 1D-CNN classifier has strong anti-interference ability and feasibility in practical applications. This work improves the performance of ‘impact echo’ in identifying internal defects in concrete and realizes the intelligent analysis of impact echo signals. Show more
Keywords: Impact echo, concrete structure, convolutional neural network, adaptive hierarchy
DOI: 10.3233/JIFS-211784
Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5215-5226, 2022
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
[email protected]
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office [email protected]
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
如果您在出版方面需要帮助或有任何建, 件至: [email protected]