Journal of Intelligent & Fuzzy Systems - Volume 44, issue 3

Authors: Aarthi, S. | Shanmugasundari, M.

Article Type: Research Article

Abstract: This paper presents boundless capacity, one server’s fuzzy and intuitionistic fuzzy queuing models. This study’s primary objective is to demonstrate and compare the performance of a single server queuing model with infinite capacity using fuzzy queuing theory and intuitionistic fuzzy queuing theory. This article demonstrates that intuitionistic fuzzy theory performs better when solving queuing problems. Furthermore, by integrating fuzzy queuing models into an intuitionistic fuzzy framework, their relevance in authentic situations is augmented. The fuzzy queuing theory model’s performance measurements are delivered as a range of values, but the intuitionistic fuzzy queuing theory model offers a broad array of values. …In this context, the arrival and the service rates are both triangular (TFN) and intuitionistic triangular fuzzy numbers (TIFN). An assessment is performed to determine the evaluation criteria, employing a design protocol in which the fuzzy values are taken as-is without being turned into crisp values. As a result, in an ambiguous environment, we can use the proposed approach to pick scientific findings. In this study, we are using the TFN in an intuitionistic fuzzy environment, compensating for the degree of stability and denial so that the sum of both virtues is never higher than one. We proffered many non-normal arithmetic techniques for this sort of fuzzified integer. The envisaged compositions are intuitive and concise, as they evolved by utilising canonical algebraic mathematics. In real-world situations, this tactic is simple and straightforward to enact. The nearest interval number is then used to round a TIFN. The key advantage of this strategy is that it allows us to quickly solve a constrained unrestrained optimization model with TIFN coefficients using a multi-section heuristic. The prevailing methodologies and initiatives are destined to be relevant to different types of updated decision-making obstacles in focusing on economic equity, funding, presidency, and environmental sciences, which will be the focus of our future research. And two numerical problems are solved to showcase the sustainability of the suggested technique. In this queuing model, we predict a variety of components, including prospective queue length, expected system length, and sojourn time in both the queue and the system. The statistical analysis reveals that the quantified performance indicators of the intuitionistic fuzzy queuing model agree well with the performance measurements of the fuzzy queuing model. Even though the average correlation between the two concepts is nearly equivalent, TIFN provides a more extensive range of possibilities than TFN. Despite the fact that fuzzy set theory is used to contend with unpredictability in decision-making circumstances, it only relates to the extent of membership and lacks a model for reluctance. The fact that each asset’s affirmation and deprivation levels are comprehended is the special feature of intuitionistic fuzzy sets. As a consequence, it becomes more meticulous, suitable, and generalizable. Show more

Keywords: Intuitionistic fuzzy queue, intuitionistic fuzzy arithmetic, sojourn time, triangular intuitionistic fuzzy numbers

DOI: 10.3233/JIFS-221367

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 3, pp. 4733-4746, 2023

Authors: Lavanya, G. | Velammal, B.L. | Kulothungan, K.

Article Type: Research Article

Abstract: A network of real time devices that can sense and transmit the information from the deployed environment by using multi hop communication is called as Wireless Sensor Network (WSNs). Despite the rapid advancement of WSN, where an increasing number of physical devices so called as sensors nodes are connected with each other, providing the improved security with optimized energy consumption during data transmission, communication and computation remains huge challenge. In wireless sensor networks, numerous sensor nodes are deployed in the physical environment to sense and collect the required information from the given environment. The sensed information is needed to be …transmitted from the nodes to the control station in an energy efficient manner. Data aggregation is one kind of techniques which will optimize the energy usage in wireless sensor networks during the data transmission. In data aggregation, the unnecessary data is removed which will significantly reduce energy of the nodes during data transmission. However, collected data during the data aggregation should be completely protected and there are various threats that can be launched by the intruders to carry out unauthorised data access and can cause threat to the integrity of the network. Therefore, ensuring data security during the data aggregation process is very important and essential for the security of the network. In this paper, a Secure Cluster based Data Aggregation Protocol (SCDAP) have been proposed to provide better security through secure authentication and verification process, and to reduce overall energy consumption of the network by implementing secure clustering process to eliminate the redundant data in the network. Moreover, the proposed system is more efficient in generating public and private keys for effective and secure data transmission and verification process. The proposed system is experimentally tested in NS-3 tool and proves that the proposed system reduces high energy consumption, computational and communicational cost, end-to-end delay and improves the packet delivery ratio. Moreover, the proposed system provides better security in the network when compared to other existing systems during the data aggregation. Show more

Keywords: Wireless networks, data aggregation, energy optimization, efficient authentication, key generation

DOI: 10.3233/JIFS-223256

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 3, pp. 4747-4757, 2023

Authors: Alabdaly, Ammar A. | El-Sayed, Wagdy G. | Hassan, Yasser F.

Article Type: Research Article

Abstract: The task of cell segmentation in microscope images is difficult and popular. In recent years, deep learning-based techniques have made incredible progress in medical and microscopy image segmentation applications. In this paper, we propose a novel deep learning approach called Residual-Atrous MultiResUnet with Channel Attention Mechanism (RAMRU-CAM) for cell segmentation, which combines MultiResUnet architecture with Channel Attention Mechanism (CAM) and Residual-Atrous connections. The Residual-Atrous path mitigates the semantic gap between the encoder and decoder stages and manages the spatial dimension of feature maps. Furthermore, the Channel Attention Mechanism (CAM) blocks are used in the decoder stages to better maintain the …spatial details before concatenating the feature maps from the encoder phases to the decoder phases. We evaluated our proposed model on the PhC-C2DH-U373 and Fluo-N2DH-GOWT1 datasets. The experimental results show that our proposed model outperforms recent variants of the U-Net model and the state-of-the-art approaches. We have demonstrated how our model can segment cells precisely while using fewer parameters and low computational complexity. Show more

Keywords: Cell segmentation, convolutional neural network, deep neural networks, medical image segmentation, u-net

DOI: 10.3233/JIFS-222631

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 3, pp. 4759-4777, 2023

Authors: Sun, Jiaqi | Wang, Pingxin | Yu, Hualong | Yang, Xibei

Article Type: Research Article

Abstract: Essentially, the problem solving of attribute reduction can be regarded as a process of reduct searching which will be terminated if a pre-defined restriction is achieved. Presently, among a variety of searching strategies, meta-heuristic searching has been widely accepted. Nevertheless, it should be emphasized that the iterative procedures in most meta-heuristic algorithms rely heavily on the random generation of initial population, such a type of generation is naturally associated with the limitations of inferior stability and performance. Therefore, a constraint score guidance is proposed before carrying out meta-heuristic searching and then a novel framework to seek out reduct is developed. …Firstly, for each attribute and each label in data, the index called local constraint score is calculated. Secondly, the qualified attributes are identified by those constraint scores, which consist of the foundation of initial population. Finally, the meta-heuristic searching can be further employed to achieve the required restriction in attribute reduction. Note that most existing meta-heuristic searchings and popular measures (evaluate the significance of attributes) can be embedded into our framework. Comprehensive experiments over 20 public datasets clearly validated the effectiveness of our framework: it is beneficial to reduct with superior stabilities, and the derived reduct may further contribute to the improvement of classification performance. Show more

Keywords: Attribute reduction, constraint score, meta-heuristic searching, rough set

DOI: 10.3233/JIFS-222832

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 3, pp. 4779-4800, 2023

Authors: Zhao, Xiaofang | Li, Faming | Chen, Biao | Li, Xiaofei | Lu, Shasha

Article Type: Research Article

Abstract: Examining the properties of High-Performance Concrete (HPC) has been a big challenge due to the highly heterogeneous relationships and coherence among several constituents. The employment of silica fume and fly ash as eco-friendly components in mixtures benefits the concrete to improve its physical features. Although machine learning approaches are utilized broadly in many studies solitarily to estimate the mechanical features of concrete, causing to reduce accuracy and lift the cost and complexities of computational networks. Consequently, current research aims to develop a Radial Basis Function Neural Network (RBFNN) integrating with optimization algorithms in order to precisely model the mechanical characteristics …of HPC mixtures including compressive strength (CS) and slump (SL). Feeding the dataset of HPC samples to hybrid models will result to reproduce the given CS and SL factors simultaneously. The results of the models showed that the maximum rate of correlation between estimated values and measured ones was obtained at 98.3% while the minimum rate of RMSE was calculated at 3.684 mm (and MPa) in the testing phase. Employing such soft-oriented approaches has been benefiting us to reduce costs and increase the result accuracy. Show more

Keywords: High-performance concrete, radial basis function, neural network, compressive strength, slump, whale optimization algorithm

DOI: 10.3233/JIFS-222805

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 3, pp. 4801-4815, 2023

Authors: Li, Junxia

Article Type: Research Article

Abstract: In order to improve the estimation accuracy of structural change points of multi-dimensional stochastic model, the accurate estimation algorithm of structural change points of multi-dimensional stochastic model is studied. A multi-dimensional stochastic Graphical Modeling model based on multivariate normal hypothesis is constructed, and the relationship between the Graphical Gaussian model and the linear regression model is determined. The parameters of the multi-dimensional stochastic model are estimated by using the parameter estimation algorithm of the multi-dimensional stochastic model containing intermediate variables. According to the parameter estimation results of the multi-dimensional stochastic model, the structural change point estimation results of the multi-dimensional …stochastic model are obtained by using the accurate estimation algorithm of the structural change point based on the MLE identification local drift time. The experimental results show that the proposed algorithm has higher estimation accuracy of structural change points than the control algorithms, which shows that it can effectively estimate the structural change points of multi-dimensional random models and has higher practicability. Show more

Keywords: Multidimensional, stochastic model, structure, change point, accurate, estimation algorithm

DOI: 10.3233/JIFS-222821

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 3, pp. 4817-4829, 2023

Authors: Nayana, P.G. | Iyer, Radha Rajamani

Article Type: Research Article

Abstract: Generalized Mycielskians are triangle-free networks with a large chromatic number, having a number of desirable characteristics like fast multi-path communication, high fault tolerance, reliable resource sharing, etc. Graph invariants like domination number and secure domination number can be used to protect the network by monitoring each node or moving to a failing node. A dominating set of a graph G is a subset of its vertex set, which can monitor every other vertex of the graph, and γ (G ), the domination number of G , is the least cardinality among all dominating sets of G . A secure dominating …set S of G is a dominating set with an additional property that, for each vertex u not in S there is a vertex v in S adjacent to u such that, the swapped set (S  - {v }) ∪ {u } is dominating. γs  (G ) is the secure domination number of G , which is the minimum cardinality among all secure dominating sets of G . In this paper, we analyzed γ and γs of the generalized Mycielskian (μm ) for path graphs P n and cycle graphs C n , varying both n and m , and used these results to obtain bounds for general graphs G . Show more

Keywords: Generalized Mycielskian, domination number, secure domination number

DOI: 10.3233/JIFS-223326

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 3, pp. 4831-4841, 2023

Authors: Lizhu, Yue | Liwei, Yao

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-213294

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 3, pp. 4843-4852, 2023

Authors: Swapna, S. | Premila, T.R. | Janaki, N. | Kirubakaran, D.

Article Type: Research Article

Abstract: This paper proposes a hybrid optimization system depending on optimal location for electric vehicles parking lot (PL) and capacitors on distribution system to maintain voltage profile with electricity loss. The proposed system is the consolidation of Seagull optimization algorithm (SGO) and salp swarm algorithm (SSA). The migration and attacking behaviors of seagull is empowered through SSA method. By this manner, the proposed hybrid optimization scheme is known as SGOS2 A method. Here, parking zone allocation with capacitor is considered to congestion management in conjunction through the compensation of reactive energy. So, one can optimally decide the size of automobile parking …space, SGOS2 A method is followed. Moreover, parking lot with capacitor allocation is considered to congestion control at the side of reactive power compensation. By this proper manipulate, the capacitors exact location, automobile parking space of electric vehicles on the grid, lessening of active with reactive power loss, voltage profile conversion is selected optimally. Besides, the proposed SGOS2 A scheme is activated on MATLAB/Simulink site, then the efficiency is examined with different techniques. The mean, median and standard deviation of the proposed approach achieves 1.0593, 1.0915 and 0.1050. Show more

Keywords: Electric vehicle, voltage and power loss, parking lot, seagull optimization algorithm, salp swarm algorithm

DOI: 10.3233/JIFS-220651

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 3, pp. 4853-4868, 2023

Authors: Khatun, Mahafuja | Islam, Ridwan Arefin | Islam, Salekul

Article Type: Research Article

Abstract: In recent years, blockchain technology has been successfully used in many distributed environments where different stakeholders, who do not have any trust between them, interact with each other through a secured and transparent platform. The use of blockchain in healthcare insurance industry has not been studied methodically. In this study, we develop a blockchain based Secured and Automated Health Insurance Claim (B-SAHIC) processing system. First, we design an Entity-Relationship (ER) diagram identifying all actors with their respective data and relations between them. We also develop the business model and algorithms for all necessary steps. We implement the system in Hyperledger …Fabric and deploy a smart contract to implement these algorithms. We introduce CouchDB to store the OffChain data where we store World-State Database. B-SAHIC provides a web-based portal for all actors who interact with the blockchain. Privacy of clients’ claim-related data is ensured by encrypting treatment-related data with a new key that is derived uniquely for each new submission done of clients’ personal documents. We have also deployed Hyperledger Explorer, a user-friendly web application tool for monitoring the health state of each node participating on the blockchain network. We have studied the performance of B-SAHIC for two to six peer nodes. Moreover, our performance study shows that B-SAHIC is fast and scalable. In our study, the average query latency is decreased from 0.07 second (for two peer nodes) to 0.02 second (for six peer nodes) in case of 1300 queries per second while the average transaction latency remains unchanged (around 3.5 seconds) for 300 transactions per second. Moreover, B-SAHIC consumes minimum resources, around 350MB only for two peer nodes. We believe that the development process of this blockchain based platform can be applicable for the automation of other insurance industry too. Show more

Keywords: Health insurance, insurance claim processing, blockchain, hyperledger fabric, smart contract

DOI: 10.3233/JIFS-220690

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 3, pp. 4869-4890, 2023