Journal of Intelligent & Fuzzy Systems - Volume 46, issue 1

Authors: Kumar, M. | Kavitha, A.

Article Type: Research Article

Abstract: An exponential growth of users demands ubiquitous connectivity, which requires the integration of new technology. Therefore, Device to Device (D2D) communication has been considered a promising technology that utilizes effective and efficient communication. Even though numerous studies have been conducted for establishing secure D2D communication, however, existing techniques face challenges like privacy, security threats, and poor generality. To overcome these issues a novel Deep-MAD model is proposed to preserve data privacy along with its access control in the D2D network and multiple attack detection in a fog environment. A Fully Homomorphic Elliptic Curve Cryptography (FHECC) is introduced to transmit data …securely in a D2D network. The data owner uses FHECC algorithm to encrypt the plain text into cipher text before storing it on the fog. Whenever the user requests data from the fog, the fog service provider confirm the user’s access control. Furthermore, the deep learning-based Bi-LSTM is used to differentiate the device as an authorized or unauthorized user. If the IP address is genuine then the inverse FHECC is used to decrypt the data for authorized users. Otherwise, the particular device is blocked and it is sent for further verification for classifying the types of attacks. The effectiveness of the proposed strategy is examined using several parameters, such as computational complexity, scalability, accuracy, and Execution time. The proposed technique improves the overall computational overhead of 31.77, 9.34, and 4.67 better than AKA protocol, lightweight cipher, and FHEEP respectively. Show more

Keywords: Bi-LSTM, device-to-device communication, cryptography, security, fog environment

DOI: 10.3233/JIFS-235362

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 955-966, 2024

Authors: Rehman, Ubaid ur | Mahmood, Tahir

Article Type: Research Article

Abstract: Wireless sensor networks are flexible monitoring systems that save track of, data, and communicate multipoint digital information interpretations to other devices. Wireless sensor networks meaningly enhance the accuracy, breadth, and extent of local data collection, commonly doing away with the requirement for expensive data wiring and recurring manual checks at risky, remote, or inaccessible locations. As a result, it is utilized to keep an eye on systems and environmental or physical parameters. In this manuscript, we expand the Heronian mean operators in the model of bipolar complex fuzzy linguistic set to concoct bipolar complex fuzzy linguistic arithmetic Heronian mean, bipolar …complex fuzzy linguistic weighted arithmetic Heronian mean, bipolar complex fuzzy linguistic geometric Heronian mean and bipolar complex fuzzy linguistic weighted geometric Heronian mean operators. We also inspect the special cases of the invented bipolar complex fuzzy linguistic arithmetic Heronian mean and bipolar complex fuzzy linguistic geometric Heronian mean operators. Moreover, in this manuscript, we concoct a technique of decision-making in the model of a bipolar complex fuzzy linguistic set with the assistance of the invented operators. As the selection and prioritization of the various types of Wireless sensor networks is the decision-making dilemma, we prioritize various types of Wireless sensor networks by employing the concocted technique of decision-making and by taking artificial data in the model of the bipolar complex fuzzy linguistic set. To reveal the influence and excellence of the concocted work, a comparative study is given in this manuscript. Show more

Keywords: Wireless sensor networks, arithmetic/geometric Heronian mean operators, bipolar complex fuzzy linguistic set.

DOI: 10.3233/JIFS-232167

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 967-990, 2024

Authors: Zhang, Yuhua | Li, Yuerong | Che, Jinxing

Article Type: Research Article

Abstract: Accurate prediction of carbon price is of great value for production, operation, investment decisions and the establishment of carbon pricing mechanism. However, the large amount of data often limits the application of learning model with good predictive performance in carbon price prediction. Therefore, the development of learning algorithms with low computational complexity has become a research hotspot. Among them, subsampling integration technology is an effective method to reduce the computational complexity. However, lack of data representativeness in subsamples and ignorance of differences among submodels inhibit the prediction performance of the subsampled ensemble model. This project proposes an optimal weight random …forest ensemble model with cluster-based subsampling (FCM-OWSRFE) for carbon price forecasting. Firstly, Fuzzy C-means cluster-based subsampling to ensure the data representativeness of subsamples. Secondly, a series of sub-random forest models are built based on subsamples with data representativeness. Finally, an optimal weight ensemble model from these sub-models is derived. To verify the validity of the model, we test FCM-OWSRFE model with the carbon price of Guangzhou Emission Exchange and the carbon price of Hubei Carbon Emission Exchange, respectively. Experimental results show that Fuzzy C-means cluster-based subsampling and the optimal weight scheme can efficiently improve the prediction performance of the subsampled random forest ensemble model. Show more

Keywords: Random forest, Fuzzy C-means clustering, subsampling, optimal weight ensemble

DOI: 10.3233/JIFS-233422

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 991-1003, 2024

Authors: Chenmin, Ni | Marsani, Muhammad Fadhil | Shan, Fam Pei

Article Type: Research Article

Abstract: Traffic sign recognition is of great significance to promote traffic sustainability and maintain traffic safety. GPS monitoring systems and advanced autonomous vehicles are often heavily reliant on camera imagery. Algorithms based on dark channel prior are susceptible to color distortion when processing traffic images containing bright sky or high-brightness areas, which can negatively impact the identification of traffic signals and signage located in elevated positions. To address this issue, this paper proposes a dehazing algorithm (SRSTO) that combines sky region segmentation and transmittance optimization. Firstly, the gradient, brightness and saturation information are calculated, followed by the construction of a threshold …function used in area segmentation. This approach is utilized to partition the image into areas not containing sky highlights and the area that contains them. Subsequently, the dark channel images of the sky and the non-sky regions are acquired, morphological operations are further performed in layers and blocks, and then the atmospheric scattered light value is calculated. Secondly, the functional relationship between the transmittance of the sky region and the brightness of the image is constructed, the transmittance of the sky and the non-sky region are optimized, and the transmittance map is further improved by using guided filtering. A simulated annealing algorithm is employed to intelligently optimize parameters such as sky segmentation threshold and sky brightness area transmittance, followed by improving the adaptability of the algorithm. Finally, combined with Gaussian filtering and Sobel edge enhancement, the image brightness is further adjusted. Using Information Entropy and NIQE as objective evaluation indexes, combined with subjective evaluation, it is concluded that the proposed method has good convergence and self-adaptive ability, and the objective indexes and subjective effects are better, especially for the hazed images containing air traffic signs. Show more

Keywords: Haze removal, traffic image, sky region segmentation, transmission optimization, simulated annealing algorithm

DOI: 10.3233/JIFS-233433

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 1005-1017, 2024

Authors: Yan, Li

Article Type: Research Article

Abstract: To improve the effect of immersive animation design, this paper combines digital media technology (DT) to establish an immersive animation design system and analyzes the media digital signal data processing algorithm. According to the advantages and disadvantages of the FHT algorithm and probabilistic algorithm, this paper proposes the FHT-SLM algorithm and the FHT-IPTS algorithm. Moreover, this paper analyzes the basic principle of TPWC transform and M-TPWC and the CO-OFDM system of cascaded FHT algorithm and M-TPWC algorithm. Finally, this paper simulates the CO-OFDM simulation system built by Matlab2018.a and Optisystem. Through the experimental analysis results, the reliability of the algorithm …and the system in this paper is verified, and the design effect of immersive animation is effectively improved. Show more

Keywords: DT, immersion, animation design, influence

DOI: 10.3233/JIFS-235793

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 1019-1028, 2024

Authors: Khan, Sami Ullah | Al Ghour, Samer | Hussain, Shoukat | Saeed, Maha Mohammed | Hussain, Fiaz | Mehmood, Arif | Park, Choonkil

Article Type: Research Article

Abstract: The concept of the fuzzy graph (FG) and the simplification of its type have been designed with many real-world concerns, decision-making, network problems, and other types of impression in mind. This article is essentially a generalization of fuzzy graph theory with their association in settings where four organizations of membership grade are characterized by imprecision. The contemporary idea of domination in picture fuzzy graph (PFG) is given the generalization of fuzzy graph domination and intuitionistic fuzzy graph (IFG) domination is unit on the innovative idea of picture fuzzy graph. This article is the main focus on the graph of the …picture fuzzy set. Additionally, this research paper concludes with the concept of domination theory (DT) and double domination theory (DDT) in the concept of environment. Obviously, the framework of picture fuzzy graph is purposed and their connected theory is obtained together with presented examples. Supplementary the domination theory (DT) in the picture fuzzy graph. A few order, strength, cardinality, and domination of completeness, neighbors in a picture fuzzy graph, and the DDS and given some examples are likewise studied in the concept of picture fuzzy graph in the environment. The application of the politician campaign is novel exploiting the projected study and curious how to double dominate would relationship with the politician campaign. Finally, a comparison between the current effort and the prior effort is made, and the advantages of the work done in the context of a picture fuzzy graph are discussed. Show more

Keywords: Intuitionistic fuzzy set, intuitionistic fuzzy graph, picture fuzzy graph, domination, double domination

DOI: 10.3233/JIFS-230918

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 1029-1041, 2024

Authors: Sharma, Rakesh | Sahay, Kuldeep | Singh, Satyendra

Article Type: Research Article

Abstract: The Challenge to stabilize the grid frequency increases with the increment of renewable energy resources. System inertia/frequency control is a significant concern for maintaining system stability with a fast response time during the load transition. This manuscript proposes surface-mounted permanent magnet synchronous generator (SPMSG) based wind energy conversion system (WECS) with a frequency support DC-link controlling loop and a converter protective DC-link voltage-controller frequency support system. To achieve power exchange, the frequency control system (FCS) for the SPMSG-based wind turbine supports the grid-side virtual inertia. The DC-link voltage is disturbed during the load transition to maintain the frequency, while the …electrolytic capacitor requires extra care regarding the DC bus voltage. This manuscript incorporates the FCS system with a supercapacitor and dynamic voltage limiter to avoid additional care of the DC bus voltage. A detailed analysis of system frequency with the additional load increment, normal connected load decrement, and various fault scenarios has been done. The proposed system is compared with the existing virtual inertia support (VIS). The simulation results show that the proposed frequency control system-based VIS efficiently limits the frequency deviations & DC-link voltage. The results are verified in the OPAL-RT 4510 real-time simulator environment to ensure the efficacy of the proposed system. Show more

Keywords: Frequency control system, wind energy conversion system, surface-mounted permanent magnet synchronous generator (SPMSG), variable speed wind turbine system, virtual inertia support.

DOI: 10.3233/JIFS-233729

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 1043-1057, 2024

Authors: Pu, Tongzheng | Huang, Chongxing | Yang, Yifei | Yang, Jingjing | Huang, Ming

Article Type: Research Article

Abstract: Hybrid tabular-textual question answering (QA) is a crucial task in natural language processing that involves reasoning and locating answers from various information sources, primarily through numerical reasoning and span extraction. Cur-rent techniques in numerical reasoning often rely on autoregressive models to decode program sequences. However, these methods suffer from exposure bias and error propagation, which can significantly decrease the accuracy of program generation as the decoding process unfolds. To address these challenges, this paper proposes a novel multitasking hybrid tabular-textual question answering (MHTTQA) framework. Instead of generating operators and operands step by step, this framework can independently generate entire program …tuples in parallel. This innovative approach solves the problem of error propagation and greatly improves the speed of program generation. The effectiveness of the method is demonstrated through experiments using the ConvFinQA and MultiHiertt datasets. Our proposed model outperforms the strong FinQANet baselines by 7% and 7.2% Exe/Prog Acc and the MT2Net baselines by 20.9% and 9.4% EM/F1. In addition, the program generation rate of our method far exceeds that of the baseline method. Additionally, our non-autoregressive program generation method exhibits greater resilience to an increasing number of numerical reasoning steps, further highlighting the advantages of our proposed framework in the field of hybrid tabular-textual QA. Show more

Keywords: Tabular-textual question answering, numerical reasoning, program generation

DOI: 10.3233/JIFS-234719

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 1059-1068, 2024

Authors: Rajasekaran, P. | Duraipandian, M.

Article Type: Research Article

Abstract: Internet of Things (IoT), a distributed healthcare system has integrated different medical resources with sensors and actuators. In this research paper proposes a secure healthcare monitoring system for IoT based distributed healthcare systems in the cloud using blockchain and deep learning (DL) mechanisms. The proposed system involved three phases: secure data transmission, data storage, and disease classification system. Initially, the patients are authenticated via blockchain mechanism and their data is encrypted via Effective Key-based Rivest Shamir Adelman (EKRSA), in which the keys are generated using Circle chaotic map and Linear inertia weight-based Honey Badger Optimization (CLHBO) algorithm. Next, in the …data storage phase, these encrypted IoT data are securely stored in the cloud using blockchain technology in a distributed manner. Finally, in the disease classification, the data are gathered from the publicly available dataset, and these collected datasets are preprocessed to handle missing values and data normalization. After that, the proposed system applies a radial basis kernel-based linear discriminant analysis (RBKLDA) model to reduce the dimensionality of the dataset. At last, the disease classification is done by optimal parameter-centered bidirectional long short-term memory (OPCBLSTM). The proposed EKRSA system archives maximum throughput of 99.05% and reliability of 99.66, which is superior to the existing approaches. The OPCBLSTM is investigated for its disease classification process, the proposed one achieves 99.64% accuracy with less processing time of 6 ms, which is superior to the existing classifiers. The experimental analysis proves that the system attained better security and classification metrics results than the existing methods. Show more

Keywords: Internet of Things (IoT), healthcare monitoring, secure data transmission, blockchain, disease prediction, machine learning (ML), deep learning (DL)

DOI: 10.3233/JIFS-234884

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 1069-1084, 2024

Authors: Xu, Xueyan | Wang, Jiayin

Article Type: Research Article

Abstract: In this study, we propose a new classification method by adopting some ideas originating from the fuzzy comprehensive evaluation (FCE). To make the FCE be a classifier, the class labels in classification problems are regarded as the evaluation remarks in the FCE, and the attributes in these two domains are regarded to be consistent. Then, to implement the FCE model B  = W ∘ R and obtain an accurate classification result, on the one hand, a learning algorithm, which is based on the joint distribution of attribute values and is dynamic, is proposed to construct the fuzzy relational matrix R …; on the other hand, equal weight is considered to constitute the weight vector W. Meanwhile, for a continuous dataset, the discretization method and the determination of the discretization class number corresponding to the proposed classifier are discussed. The proposed classifier not only innovatively extends the FCE to data mining but also has its own classification advantages, that is, it is easy to operate and has good interpretability. Finally, we perform some numerical experiments using publicly available datasets, and the experimental results demonstrate that the proposed classifier outperforms some existing classifiers. Show more

Keywords: Fuzzy set, fuzzy comprehensive evaluation, classification, data mining

DOI: 10.3233/JIFS-232622

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 1085-1100, 2024