Journal of Intelligent & Fuzzy Systems - Volume 43, issue 6

Authors: Wang, Jing | Wang, Ting

Article Type: Research Article

Abstract: Microgrids (MGs) are defined as a set of loads, generation sources and energy storage devices that act as a controllable load or generator, and can supply power and heat to local areas. Management of generated power in MGs is among the main topics that should be addressed for MG design and operation. The existence of distributed generation (DG) resources has caused MG management to face new issues. Depending on the level of exchange between the MG and main grid, MG operation can be classified into two modes: off-grid (islanded) and grid-connected. Optimal energy management in the systems with multiple MGs …has created new challenges in power systems. Therefore, it is important to develop energy management systems (EMSs) focusing on the optimal performance of MG resources and controlling power exchange between the grid and MGs. The present study aims to present a structure with two control layers, called primary and secondary control, for energy management in the systems with multiple MGs and different ownership. Moreover, a flexible distributed EMS is proposed to coordinate the operation of interconnected MGs. Each MG is regarded as an independent unit with local objectives to optimize its operating costs and exchanged power. It is assumed that interconnected MGs are connected to each other by a common bus, through which they can exchange power. MG planning is simulated considering load flow equations and voltage constraints in a system consisting of multiple MGs over a 24-h period. The simulation results indicate using the proposed EMS can improve MG efficiency and reliability. The simulation is performed in MATLAB software by grasshopper optimization algorithm (GOA). Uncertainties and scenario generation and reduction are considered in modeling. Show more

Keywords: Distributed energy management system, Microgrid (MG), distributed generation resource, power exchange

DOI: 10.3233/JIFS-220568

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 7949-7961, 2022

Authors: Wang, Huifang | Zhang, Shili

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Abstract: This article has been retracted.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-220736

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 7963-7974, 2022

Authors: Yuvaraja, M.

Article Type: Research Article

Abstract: The use of wireless sensor networks (WSNs) for data collection is widespread. The resource constraint is an important factor in WSN communications design. The issue arises naturally in WSNs as a result of uneven energy consumption caused by multi-hop routing and dynamic network models, which substantially affects network lifetime. The nodes are dispersed over distant sensing areas and are powered by finite or limited energy batteries that are difficult to replace. The energy of nodes is reduced as a result of changes in network topology or the network’s lifespan and the main intention of this research is to figure out …how to make sensor networks last longer. The suggested study work focuses on a specific routing strategy for WSNs that employs the AO-star algorithm with a Fuzzy approach and link stability for extending the network lifetime. The technique chooses the optimum routing path by the sensing point to the receiving node based on how much energy is consumed, the smallest number of nodes with the shortest latency, and lower transmission loads with higher throughput. To compare the proposed strategy’s efficiency in energy consumption balancing and network lifespan enhancement, the proposed technique may achieve a 30% longer average network lifetime than the A-star algorithm. Show more

Keywords: Energy, fuzzy, loads, simulation data and WSN

DOI: 10.3233/JIFS-212977

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 7975-7982, 2022

Authors: Wang, Liqin | Chu, Hang | Dong, Yongfeng | Liu, Enhai | Li, Linhao

Article Type: Research Article

Abstract:  Many real-world knowledge graphs are complex and keep evolving over time. Inferring missing facts in temporal knowledge graphs is a fundamental and challenging task. Previous studies focus on link prediction in static knowledge graphs which hardly extracts the temporal features effectively. In this paper, we propose a novel deep learning model, namely KBGAT-BiLSTM, which is capable of solving long-term predict problems and is suitable for temporal knowledge graph with complex structures. First, we adapt the Graph Attention Network (GAT) to learn the structural features of knowledge graph. Then we utilize the Bidirectional Long Short-Term Memory Networks (BiLSTM) to learn the …temporal features and obtain the low-dimensional embeddings of entities and relations. Finally, we employ a scoring function for link prediction in temporal knowledge graphs. Through extensive experiments on YAGO, WIKI, and ICEWS18 datasets, we demonstrate the effectiveness of our model, compare the performance of our model with several different state-of-the-art methods and further analyze the properties of the proposed method. Show more

Keywords: Knowledge graph, link prediction, graph attention network, temporal

DOI: 10.3233/JIFS-210943

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 7983-7994, 2022

Authors: Janardhan, G. | Surendra Babu, N. N. V. | Srinivas, G. N.

Article Type: Research Article

Abstract: A hybrid method for transformer-less grid-tie hybrid Renewable Energy Source (HRES), such as photovoltaic (PV) and wind energy system (WES) with minimization of common mode leakage current is proposed in this manuscript. The proposed system is the combined execution of Vascular Invasive Tumor Growth (VSTG) Optimization Algorithm and extreme gradient boosting (XGBOOST) named VSTG-XGBOOST control topology. The main intention of transformerless grid-connected HRES system is “to lessen the leakage current, maximum power point (MPP) extraction and maximal power point tracking (MPPT), the active and reactive power controller, and having the unity power factor. To attain the above-mentioned aims, the following …actions have been performed in this proposed work. Two turn-off snapper circuits are inserted parallel to the switches to share the input DC voltage among snubber capacitors. By then, VSTG is used to estimate the optimal gain parameters under various source currents as normal value is used to generate the optimal control signal database offline. Based on the attained dataset, the XGBOOST forecasts the optimal control signals of the grid-connected HRES inverter in the online way. This control technique allows two sources to supply the load separately depending on the availability of the energy sources and keeps common DC voltage constant. Show more

Keywords: Transformer-less grid-tie inverter, common mode leakage current, photovoltaic, Hybrid Renewable Energy Source, snubber capacitors

DOI: 10.3233/JIFS-213362

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 7995-8019, 2022

Authors: Rashid, M.H.M. | Altaweel, Nifeen Hussain

Article Type: Research Article

Abstract:  In this paper, we introduce a new fuzzy contraction mapping and prove that such mappings have fixed point in τ -complete fuzzy metric spaces. As an application, we shall utilize the results obtained to show the existence and uniqueness of random solution for the following random linear random operator equation. Moreover, we shall show the existence and uniqueness of the solutions for nonlinear Volterra integral equations on a kind of particular fuzzy metric space.

Keywords: Random fixed point, random operator, random operator equation, contractive mapping, fixed point, t-norm, fuzzy metric space, non-archimedean fuzzy metric space

DOI: 10.3233/JIFS-220258

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8021-8040, 2022

Authors: Thai, Pon L.T. | Merry Geisa, J.

Article Type: Research Article

Abstract: Cervical cancer is the most frequent and fatal malignancy among women worldwide. If this tumor is detected and treated early enough, the complications it causes can be minimized. Deep learning demonstrated significant promise when imposed on biomedical difficulties such as medical image processing and disease prognostication. Therefore, in this paper, an automatic cervical cell classification approach named IR-PapNet is developed based on Inception-ResNet which is an optimized version of Inception. The learning model’s conventional ReLu activation is replaced with the parametric-rectified linear unit (PReLu) to overcome the nullification of negative values and dying ReLu. Finally, the model loss function is …minimized with the SGD optimization model by modifying the attributes of the neural network. Furthermore, we present a simple but efficient noise removal technique called 2D-Discrete Wavelet Transform (2D-DWT) algorithm for enhancing image quality. Experimental results show that this model can achieve a top-1 average identification accuracy of 99.8% on the pap smear cervical Herlev datasets, which verifies its satisfactory performance. The restructured Inception-ResNet network model can obtain significant improvements over most of the state-of-the-art models in 2-class classification, and it achieves a high learning rate without experiencing dead nodes. Show more

Keywords: Cervical cancer, medical image processing, deep learning, 2D-DWT, ResNet model

DOI: 10.3233/JIFS-220511

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8041-8056, 2022

Authors: Chen, Zhihua | Kosari, Saeed | Kaarmukilan, S.P. | Yuvapriya, C. | Atanassov, Krassimir T. | Rangasamy, Parvathi | Rashmanlou, Hossein

Article Type: Research Article

Abstract:  Video Processing has found enormous applications in recent times from security systems to interplanetary missions. In real-life situations, most of the videos are fuzzy/vague/uncertain. Intuitionistic fuzzy set (IFS) is one of the effective tools for handling uncertainty. Among many extensions of IFSs, temporal intuitionistic fuzzy sets (TIFSs) are very interesting as they are time-dependent. Hence, TIFSs are suitable to define a video, which is dynamic and hence depends on time-moment. In this way, this work introduces a novel VIdeo PROCessing (VIPROC) algorithm, using temporal intuitionistic fuzzy sets to enhance videos, which is first of its kind in existence. The comparison …is made with fuzzy contrast intensification operation. VIPROC algorithm is designed using contrast intensification operation for video enhancement. The results are encouraging in comparison with the original test videos. The results are discussed taking into account the several frames of the test video. Further, the proposed algorithm can be applied/extended to engineering applications like motion tracking, traffic detection systems, real time videos captured through mobile (hand-held) devices, and so on. As no such algorithms are existing which use TIFSs to process a video, the authors got motivated to design and develop VIPROC algorithm. Show more

Keywords: Temporal intuitionistic fuzzy sets, contrast intensification, VIdeoPROCessing (VIPROC) algorithm

DOI: 10.3233/JIFS-220928

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8057-8072, 2022

Authors: Annamalai, Tamizhselvi | Liju Anton, J. | Yoganathan, P.

Article Type: Research Article

Abstract: Intelligent transport system is a greatly emerging technology in recent years. The stability and reliability of these systems is very important. In vehicular ad-hoc networks (VANET), the data transmission process can be improved by employing clustering process. The nodes can be clustered in order to utilize the maximum bandwidth of the network and improving network stability. In VANETs it is to introduce road safety and driver safety. In addition, security is a major concern and the malicious nodes need to be accurately detected. Several kinds of attacks can present in the VANETs. Hence an efficient authentication method and trust aware …method is essentially required. In this work, stability assured CNN based trust aware clustering and authenticated transmission is introduced. For data authentication quantum cryptography technique is employed. In clustering process, trust degree of nodes is computed, vehicle speed is observed, direction of vehicle and distance among nodes are taken. In addition, for ensuring more safety, the critical data transmission is given higher priority. Therefore in clustering, data criticality parameter is also considered. For cluster formation, convolution neural network is employed. After the clustering process, the quantum cryptography based authentication is implemented for vehicle units and road side units. Data among these units are transmitted with quantum channel encryption key. Then simulation results are observed for validating the proposed protocol. Show more

Keywords: Vehicular ad-hoc networks, wireless communication, routing protocols, cryptography, convolution neural network

DOI: 10.3233/JIFS-220460

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8073-8087, 2022

Authors: Liu, Lu | Sun, Qiming | Jiang, Tianhua | Deng, Guanlong | Gong, Qingtao | Li, Yaping

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-220494

Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 8089-8107, 2022