Journal of Intelligent & Fuzzy Systems - Volume Pre-press, issue Pre-press

Authors: Xie, Zhixin | Wang, Xiaofeng | Yang, Lan | Pang, Lichao | Zhao, Xingyu | Yang, Yi

Article Type: Research Article

Abstract: The survey propagation algorithm is the most effective information propagation algorithm for solving the 3-SAT problem. It can effectively solve the satisfiability problem when it converges. However, when the factor graph structure is complex, the algorithm often does not converge and the solution fails. In order to give a theoretical explanation to this phenomenon and to analyze the convergence of the survey propagation algorithm effectively, a connected treewidth model of the propositional formula was constructed by using the connected tree decomposition method, and the connected treewidth of the factor graph was calculated. The relationship between the connected treewidth and the …convergence of the survey propagation algorithm is established, and the convergence judgment condition of the survey propagation algorithm based on the connected tree width is given. Through experimental analysis, the results show that the method is effective, which is of great significance for analyzing the convergence analysis of other information propagation algorithms. Show more

Keywords: Survey propagation algorithm, convergence, connected treewidth, propositional formula, satisfiability problem

DOI: 10.3233/JIFS-223779

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2023

Authors: Zhang, Ning | Jung, Kwansue

Article Type: Research Article

Abstract: High-quality development of socio-economic, ecological environment, tourism industry and natural resources in the Yellow River Basin is a major strategic task for national development. High-quality development in the Yellow River Basin still has a lot of room for improvement, so it is important for the coupled and coordinated development of water resources-socio-economic-ecological environment-tourism industry in the Yellow River Basin region. In this study, we focus on the major strategic issues of high quality development in the Yellow River Basin in the context of the above-mentioned background and the current forms and policies of sustainable development in China, and conduct research …on the theory and methods of assessing the sustainable development of regional water resources-socio-economic-ecological environment-tourism industry. However, by analyzing the existing research literature on sustainable development assessment, we find that most of them focus on a single area or two combinations of modal development studies, and focus on exploring micro-coupling mechanisms, so the generality of macro policy support is rather mediocre, which we fill this gap through this study. The study relies on an innovative macroscopic research perspective that draws pioneeringly on the quality function deployment (QFD) theory in the field of product quality management in marketing, which, it is worth stating, allows for a framework of research perspectives from a systematic and holistic perspective. In this framework, we will propose a G1-entropy value method for indicator importance (weight) assessment. It is worth stating that the G1 method used in this paper is different from the traditional G1 method in that we will introduce the identity information weights of experts to improve the reliability of the subjective assignment method. We will also construct an indicator system for studying the regional sustainable development issues in the Yellow River Basin on this basis, so as to complete the ranking and analysis of the nine provinces and the importance of indicators in the Yellow River Basin. This study will provide a comprehensive theoretical basis for Chinese government and related departments to formulate policies for the high-quality development of water resources, socio-economic, ecological environment and tourism industry in the Yellow River Basin, and also provide theoretical and empirical references for the analysis and assessment of similar international regional sustainability cases. Show more

Keywords: Analytical theory of sustainable development, quality function deployment, G1-entropy method, yellow river basin

DOI: 10.3233/JIFS-230920

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-24, 2023

Authors: Nguyen, Phu Xuan-Vinh | Nguyen, Thu Hoang-Thien | Van Nguyen, Kiet | Nguyen, Ngan Luu-Thuy

Article Type: Research Article

Abstract: Multilingual pre-trained language models have achieved impressive results on most natural language processing tasks. However, the performance is inhibited due to capacity limitations and their under-representation of pre-training data, especially for languages with limited resources. This has led to the creation of tailored pre-trained language models, in which the models are pre-trained on large amounts of monolingual data or domain specific corpus. Nevertheless, compared to relying on multiple monolingual models, utilizing multilingual models offers the advantage of multilinguality, such as generalization on cross-lingual resources. To combine the advantages of both multilingual and monolingual models, we propose KDDA - a framework …that leverages monolingual models to a single multilingual model with the aim to improve sentence representation for Vietnamese. KDDA employs teacher-student framework and cross-lingual transfer that aims to adopt knowledge from two monolingual models (teachers) and transfers them into a unified multilingual model (student). Since the representations from the teachers and the student lie on disparate semantic spaces, we measure discrepancy between their distributions by using Sinkhorn Divergence - an optimal transport distance. We conduct experiments on two Vietnamese natural language understanding tasks, including machine reading comprehension and natural language inference. Experimental results show that our model outperforms other state-of-the-art models and yields competitive performances. Show more

Keywords: Natural language understanding, machine reading comprehension, natural language inference, knowledge distillation, optimal transport

DOI: 10.3233/JIFS-231485

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2023

Authors: Liu, Yang | Yi, Fulong | Ma, Yuhua | Wang, Yongfu

Article Type: Research Article

Abstract: To solve the problem that the existing semantic segmentation method is challenging to balance the two indicators of reasoning speed and accuracy under low-light conditions, a lightweight real-time semantic segmentation method that can run on embedded vehicle terminals under low-light conditions, namely, LCG-BiSeNetV2 is proposed. Firstly, the Zero-DCE++ method is introduced to preprocess the low-light video frames; Secondly, by improving the module of the BiSeNetV2 method and optimizing the downsampling convolution in the encoder structure, the semantic feature extraction ability of the BiSeNetV2 method has been significantly improved; Finally, the self-made road scene semantic segmentation dataset and the CAMVID dataset …were used for training and testing, the mIoU coefficient reaches 72.37% and 76.73%, and the reasoning speed reaches 148.91 Frames Per Second (FPS) and 136.75 FPS, which shows that the LCG-BiSeNetV2 method has achieved fast reasoning and precise semantic segmentation. Show more

Keywords: End-to-end, real-time, semantic segmentation, autonomous driving system, image enhancement

DOI: 10.3233/JIFS-230643

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2023

Authors: Chang, Jingjing | Zhao, Hui

Article Type: Research Article

Abstract: In recent years, implicit sentiment analysis, which aims to detect sentiment of a sentence that don’t contain obvious sentiment words, has become an attractive research topic. This paper focuses on event-centric implicit sentiment analysis, which utilizes the sentiment-aware event to infer the sentiment polarity of the sentence. Existing event-based implicit sentiment analysis methods typically treat entities or noun phrases in the text as events, or model contextual information to indirectly infer events using sophisticated models, but these methods fail to fully capture event information. To address these issues, this paper defines events as <subject, predicate, object>. Based on this event …representation, neural tensor network was used to model the interaction between event elements and extract high-level semantic features of events. In addition, a novel affective enhanced graph model was proposed to capture sentiment-related dependencies between context words. Furthermore, this paper considers the case where a sentence contains multiple events, and constructs an event-centric implicit sentiment analysis dataset, where each sentence contains at least one event triplet. Experimental results on the constructed dataset demonstrate the effectiveness of our proposed approach. Show more

Keywords: Implicit sentiment analysis, affective knowledge, event information, neural tensor network

DOI: 10.3233/JIFS-231778

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2023

Authors: Chandra, Harshit | Bajpai, Shrish | Alam, Monauwer | Chandel, Vishal Singh | Pandey, Amit Kumar | Pandey, Digvijay

Article Type: Research Article

Abstract: Hyperspectral (HS) images contain rich spatial and spectral information. Due to its large size, it is difficult to store, process, analyze, or transmit the critical information contained in it. The compression of hyperspectral images is inevitable. Many transform based Hyper Spectral Image Compression Algorithms (HSICAs) have been proposed in the past that work for both lossy and lossless compression processes. The transform based HSICA uses linked lists or dedicated markers or array structure to keep track of significant and insignificant sets or coefficients of a transformed HS image. However, these algorithms either suffered from low coding efficiency, high memory requirements, …or high coding complexity. This work proposes a transform based HSICA using a curvelet transform to improve the directional elements and the ability to represent edges and other singularities along curves. The proposed HSICA aims to provide superior quality compressed HS images by representing HS images at different scales and directions and to achieve a high compression ratio. Experimental results show that the proposed algorithm has a low coding memory requirement with a 2% to 5% increase in coding gain compared to the other state of art compression algorithms. Show more

Keywords: Complexity theory, curvelet transform, hyperspectral image, hyperspectral image compression, transform coding

DOI: 10.3233/JIFS-231684

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-25, 2023

Authors: Deng, Ming | Zhou, Zhiheng | Liu, Guoqi | Zeng, Delu | Zhang, Mingyue

Article Type: Research Article

Abstract: Some active contour models proposed based on intensity inhomogeneity are sensitive to initialization and cannot achieve ideal segmentation results for real images. An adaptive active contour model based on local bias field estimation and saliency is proposed in this paper. First of all, this model proposes an adaptive multi-local search algorithm, which avoids the initialization sensitivity by adaptively setting of the initial contour; Secondly, the local bias field is estimated by fusing the saliency map and fuzzy c-means clustering; Finally, the new bias field and the corrected energy fitting constant are used to define the new energy functional. The desired …target object is obtained by minimizing the energy functional. The experimental results show that the segmentation accuracy of the model proposed in this paper is higher than that of the models participating in the comparison. The proposed model can not only avoid the interference of initialization and redundant information, but also segment images with intensity inhomogeneity effectively. Show more

Keywords: Active contour model, intensity inhomogeneity, bias field, saliency map

DOI: 10.3233/JIFS-231741

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2023

Authors: Yang, Lei | Gao, Ge

Article Type: Research Article

Abstract: As China’s economic and social development enters a new stage, the role of innovation and entrepreneurship is becoming increasingly prominent, and its importance is also being emphasized. As the main force for future employment and national economic construction, college students naturally become the new force for innovation and entrepreneurship. Therefore, it is imperative for universities to carry out in-depth innovation and entrepreneurship education (IEE) for college students. Then, with the continuous development of social development needs and the professional growth needs of college students, the “innovation and entrepreneurship” education for college students should also be adjusted in a timely manner …in terms of educational concepts, models, and methods. The IEE environment evaluation in universities under the background of “ Double Innovation” is looked as multiple attribute decision-making (MADM). In this paper, the information entropy model is employed to calculate the objective weight of the evaluation attribute. Then, interval-valued intuitionistic fuzzy Combined Compromise Solution (IVIF-CoCoSo) is built based on the Hamming distance and Euclid distance to cope with MADM under interval-valued intuitionistic fuzzy sets (IVIFSs). The new MADM method is proposed for IEE environment evaluation in universities under the background of “ Double Innovation”. Finally, the IVIF-CoCoSo approach is compared with existing methods to verify the effectiveness of IVIF-CoCoSo algorithm. The main contributions of this constructed paper are: (1) the IVIF-CoCoSo method is built based on the Hamming distance and Euclid distance. (2) the information entropy model is employed to calculate the objective weight of the evaluation attribute. (3) The new MADM method is proposed for IEE environment evaluation in universities under the background of “ Double Innovation” based on IVIF-CoCoSo. (4) The IVIF-CoCoSo model is compared with existing methods to verify the effectiveness of the IVIF-CoCoSo algorithm. Show more

Keywords: Multi-attribute decision making (MADM), interval-valued intuitionistic fuzzy sets (IVIFSs), IVIF-CoCoSo method, information entropy method; IEE environment

DOI: 10.3233/JIFS-232151

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2023

Authors: Abiyev, Rahib H. | Aliev, Rafik | Kaynak, Okyay

Article Type: Research Article

Abstract: In this paper, a novel Z-number based Fuzzy Neural Network (Z-FNN) based on the integration of Z-valued fuzzy logic and neural networks is proposed. Z-valued fuzzy rule base is presented and its inference process is described using interpolative approximate reasoning. Accordingly, the structure of the Z-FNN is proposed using a distance measure and interpolative approximate reasoning scheme. Based on presented architecture the learning algorithm of Z-FNN is designed. The updating of the unknown parameters of the network is carried out using Genetic Algorithms (GA). The proposed Z-FNN system is utilized for dynamic plant identification. The effectiveness of Z-FNN has been …tested by comparing its performance with the performances of other fuzzy systems available in the literature. The proposed approach has been proven to be a suitable alternative for the identification of nonlinear systems characterized by uncertain and imprecise information. Show more

Keywords: Fuzzy neural networks, Z-number, fuzzy rule, learning

DOI: 10.3233/JIFS-232741

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2023

Authors: Gnanasundari, P. | Sheela Sobana Rani, K.

Article Type: Research Article

Abstract: Wireless sensor networks (WSNs) are a new technology that helps with a variety of practical uses, involving healthcare and monitoring the environment. In recent years, security has been considered as important topic in WSN since it is vulnerable to several security threats. Recent works uses cryptographic techniques to ensure security in WSN. In existing works, the security methodologies require high resources but still assure low level security. To resolve this issue, this paper proposes a node validation method which is lightweight as well as assures high level security. The main idea behind this work is to integrate Blockchain technology with …WSN environment. We presented a novel Blockchain-assisted Node Validation (BlockNode) methodology for ensuring high level security. To maintain energy efficiency, the network is segregated into multiple clusters by Valid Cluster Formation (VCF) approach. In each cluster, optimum CH is selected by using type-II fuzzy algorithm. The VCF approach only allows the valid nodes which are authorized by Blockchain validation. Then, the data transmission is secured by Jacobian Curve Encryption (JCE) algorithm. For optimal route selection, Energy-aware Reinforcement Learning (ERL) algorithm is proposed. Overall, the proposed work high level security with minimum resource consumption. The experimental results obtained from NS-3.25 simulation tool confirms that the proposed work achieves better performance in security level, encryption & decryption time, delay, energy consumption, delivery ratio and throughput. Show more

Keywords: Node Validation, energy efficiency, cybersecurity, blockchain, WSN

DOI: 10.3233/JIFS-230020

Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2023