Journal of Intelligent & Fuzzy Systems - Volume 43, issue 3

Authors: Wang, Gaihua | Dai, Yingying | Zhang, Tianlun | Lin, Jinheng | Chen, Lei

Article Type: Research Article

Abstract: Remote sensing image change detection is to analyze the change information of two images from the same area at different times. It has wide applications in urban expansion, forest detection, and natural disaster. In this paper, Feature Fusion Network is proposed to solve the problems of slow change detection speed and low accuracy. The MobileNetV3 block is adopted to efficiently extract features and a self-attention module is applied to investigate the relationship between heterogeneous feature maps (image features and concatenated features). The method is tested in data sets SZTAKI and LEVIR-CD. With 98.43 percentage correct classification, it is better than …other comparative networks, and its space complexity is reduced by about 50%. The experimental results show that it has better performance and can improve the accuracy or speed of change detection. Show more

Keywords: Attention mechanisms, change detection, depth separable convolution, siamese network

DOI: 10.3233/JIFS-211432

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 3271-3282, 2022

Authors: Malik, Meenakshi | Nandal, Rainu | Dalal, Surjeet | Maan, Ujjawal | Le, Dac-Nhuong

Article Type: Research Article

Abstract: In recent years, driver behavior analysis plays a vital role to enhance passenger coverage and management resources in the smart transportation system. The real-world environment possesses the driver principles contains a lot of information like driving activities, acceleration, speed, and fuel consumption. In big data analysis, the driver pattern analyses are complex because mining information is not utilized to feature evaluations and classification. In this paper, a new efficient Fuzzy Logical-based driver behavioral pattern analysis has been proposed to offer effective recommendations to the drivers. Primarily, the feature selection can be carried out with the assist of fuzzy logical subset …selection. The selected features are then evaluated using frequent pattern information and these measures will be optimized with a multilayer perception model to create behavioral weight. Afterward, the information weights are trained with a test through an optimized spectral neural network. Finally, the neurons are activated by a recurrent neural network to classify the behavioral approach for the superior recommendation. The proposed method will learn the characteristics of driving behaviors and model temporal features automatically without the need for specialized expertise in feature modelling or machine learning techniques. The simulation results manifest that the proposed framework attains better performance with 98.4% of prediction accuracy and 86.8% of precision rate as compared with existing state-of-the-art methods. Show more

Keywords: Fuzzy logic, feature selection and classification, neural network, behavioral analysis

DOI: 10.3233/JIFS-212007

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 3283-3292, 2022

Authors: Fan, Jianping | Fang, Wenting | Wu, Meiqin

Article Type: Research Article

Abstract: In order to cope with increasingly severe environmental problems, the development of new energy vehicles has been strongly supported. The rapid development of new energy vehicles has led to the development of power batteries. It is vital to choose the appropriate new energy vehicle battery which is the power source of the new energy vehicles. This paper proposes a new model based on D numbers, which combines the Best-worst method (BWM) and Evaluation based on Distance from Average Solution (EDAS) method. First, in order to express the uncertainty of expert decision-making, this paper uses D number to describe the evaluation …information. Then the D-BWM model is applied to determine the weight of the given criteria. Next, the D-EDAS model is constructed for the selection of new energy vehicle battery suppliers. The results show that this newly proposed model is reasonable. Finally, the validity and robustness of the model in this paper are demonstrated through sensitivity analysis. Show more

Keywords: D numbers, BWM, EDAS, new energy vehicles, battery suppliers

DOI: 10.3233/JIFS-220001

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 3293-3309, 2022

Authors: Wang, Pei | Zhao, Zhengwei | Wang, Zhihong | Li, Zhaowen

Article Type: Research Article

Abstract: A fuzzy set-valued information system (FSVIS) is a special information system (IS) where the value of an object under each attribute or each attribute value is a fuzzy set. Homomorphism is a powerful mathematical tool to deal with FSVISs, which can be used to study relationships among them. Based on data compression, we obtain some characterizations about FSVISs and their homomorphisms. First, some homomorphisms between FSVISs are introduced. After that, attribute reduction based on tolerance relation in a FSVIS is studied. Eventually, we get invariant characterizations of FSVISs based on some special homomorphisms under data compression.

Keywords: FSVIS, θ-reduction, θ-core, homomorphism, tolerance relation, data compression, characterization

DOI: 10.3233/JIFS-213186

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 3311-3321, 2022

Authors: Li, Ping | Yu, Jiong | Li, Min | Chen, JiaYin | Yang, DeXian | He, ZhenZhen

Article Type: Research Article

Abstract: In this paper, we propose a unified framework for an abstractive summarization method which uses the prompt language model and a pointer mechanism. The abstractive summarization problem usually includes a text encoder and a text decoder. Current methods usually employ an encoder-decoder architecture to condense and paraphrase a document. To better paraphrase a document, we propose a unified framework for an abstractive summarization model that only uses a topic-sensitive decoder. Our model has a prompt input module, a text decoder and a pointer mechanism. We apply our model to Xsum, Gigaword, and CNN/DailyMail summarization datasets, and experimental results demonstrate that …our model has achieved state-of-the-art results on the Xsum dataset and comparable results on the other two datasets. Show more

Keywords: Abstractive summarization, masked language model, pointer mechanism, text decoder

DOI: 10.3233/JIFS-213500

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 3323-3335, 2022

Authors: Wang, Bing | Huang, Xianglin | Cao, Gang | Yang, Lifang | Wei, Xiaolong | Tao, Zhulin

Article Type: Research Article

Abstract: Many micro-video related applications, such as personalized location recommendation and micro-video verification, can be benefited greatly from the venue information. Most existing works focus on integrating the information from multi-modal for exact venue category recognition. It is important to make full use of the information from different modalities. However, the performance may be limited by the lacked acoustic modality or textual descriptions in uploaded micro-videos. Therefore, in this paper visual modality is explored as the only modality according to its rich and indispensable semantic information. To this end, a hybrid-attention and frame difference enhanced network (HAFDN) is proposed to generate …the comprehensive venue representation. Such network mainly contains two parallel branches: content and motion branches. Specifically, in the content branch, a domain-adaptive CNN model combined with temporal shift module (TSM) is employed to extract discriminative visual features. Then, a novel hybrid attention module (HAM) is introduced to enhance extracted features via three attention mechanisms. In HAM, channel attention, local and global spatial attention mechanisms are used to capture salient visual information from different views. In addition, convolutional Long Short-Term Memory (convLSTM) is enforced after HAM to better encode the long spatial-temporal dependency. A difference-enhanced module parallel with HAM is devised to learn the content variations among adjacent frames, which is usually ignored in prior works. Moreover, in the motion branch, 3D-CNNs and LSTM are used to capture movement variation as a supplement of content branch in a different form. Finally, the features from two branches are fused to generate robust video-level representations for predicting venue categories. Extensive experimental results on public datasets verify the effectiveness of the proposed micro-video venue recognition scheme. The source code is available at https://github.com/hs8945/HAFDN. Show more

Keywords: Micro-video venue recognition, robust visual features, hybrid attention module, difference enhanced module

DOI: 10.3233/JIFS-213191

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 3337-3353, 2022

Authors: Santhana Marichamy, V. | Natarajan, V.

Article Type: Research Article

Abstract: In this manuscript proposes an efficient big data security analysis on HDFS based on the combination of Improved Deep Fuzzy K-means Clustering (IDFKM) Algorithm and Modified 3D rotation data perturbation algorithm using health care database. To compile a similar group of data, an Improved Deep Fuzzy K-means Clustering (IDFKM) Algorithm is used as partitioning the medical data. After clustering, Modified 3D rotation data perturbation technique is used to satisfy the privacy requirement of the client. Modified 3D rotation Data Perturbation technique perturbs each and every sensitive data of the cluster and all the key parameters values used for clustering have …warehoused in the database file sector. The proposed approach is executed by Java program, its efficiency is assessed by Health care database. The metrics under the study of memory usage attains higher accuracy 34.765%, 23.44%, 52.74%, 18.74%, lower execution time 35.23%, 23.76%, 27.86%, 27.76%, higher Efficiency 26.85%, 38.97%, 28.97%, 35.65%. then the proposed method is compared with the existing methods such asSecurity Analysis of SDN Applications for Big Data with spoofing identity, Tampering with data, Repudiation threats, Information disclosure, Denial of service and Elevation of privileges (STRIDE), Big Data Analysis-based Secure Cluster Management for using Ant Colony Optimization (ACA) Optimized Control Plane in Software-Defined Networks, System Architecture for Secure Authentication and Data Sharing in Cloud Enabled Big Data Environment using LemperlZivMarkow Algorithm (LZMA) and Density-based Clustering of Applications with Noise (DBSCAN), Big Data Based Security Analytics using data based security analytics (BDSA) approach for Protecting Virtualized Infrastructures in Cloud Computing respectively. Show more

Keywords: Hadoop distributed file system (HDFS), cloud storage, hadoop, data security, Improved Deep Fuzzy K-means Clustering (IDFKM) Algorithm, modified 3D rotation data perturbation algorithm

DOI: 10.3233/JIFS-213024

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 3355-3372, 2022

Authors: Rajanandhini, V.M. | Elangovan, G.

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-213198

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 3373-3391, 2022

Authors: Gao, Ying | Li, Shan | Ba, Tao | Ren, Tong

Article Type: Research Article

Abstract: The stability of unmanned vehicle is related to the safety of the vehicle itself. In the process of unmanned vehicle control, there will be collision phenomenon in the process of meeting the vehicle. To solve the above problem, the design of unmanned interaction system based on visual cognition is proposed. The hardware structure of the system is designed based on 80C51 single chip microcomputer, including ARM processor, GPS receiving module, driving record signal collecting module, etc. The PID controller design based on neural network is optimized, and the design of unmanned interactive system based on visual cognition is completed. Experimental …results show that the designed system can identify the surrounding environment in real time, make corresponding decisions, let the vehicle avoid the wrong vehicle operation, and save Oil consumption. Show more

Keywords: Visual cognition, unmanned driving, interactive system, communication serial port, display module

DOI: 10.3233/JIFS-211657

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 3393-3401, 2022

Authors: Li, Qiqi | Qin, Zhongfeng | Liu, Zhe

Article Type: Research Article

Abstract: Traditional support vector regression dedicates to obtaining a regression function through a tube, which contains as many as precise observations. However, the data sometimes cannot be imprecisely observed, which implies that traditional support vector regression is not applicable. Motivated by this, in this paper, we employ uncertain variables to describe imprecise observations and build an optimization model, i.e., the uncertain support vector regression model. We further derive the crisp equivalent form of the model when inverse uncertainty distributions are known. Finally, we illustrate the application of the model by numerical examples.

Keywords: Imprecise observations, uncertain variables, support vector regression, uncertainty theory

DOI: 10.3233/JIFS-212156

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 3403-3409, 2022