Journal of Intelligent & Fuzzy Systems - Volume 45, issue 2

Authors: Sinika, S. | Ramesh, G.

Article Type: Research Article

Abstract: Due to present condition, the expenses of allocating a job to a specific person or scheduling transport with a precise value may result in ambiguity. To deal with this, neutrosophic sets which is an extended form of fuzzy sets, appear alongside membership, non-membership and indeterminacy. The assignment problem in a trapezoidal neutrosophic environment with cost as the trapezoidal neutrosophic numbers is discussed in this work. The paper’s motive is to convert the trapezoidal neutrosophic numbers into new interval arithmetic form and the efficiency of the same is shown by comparing the existing method with other assignment models using examples.

Keywords: Assignment problem, Hungarian method, Interval Arithmetic, One’s assignment method, Trapezoidal neutrosophic number

DOI: 10.3233/JIFS-222796

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 2, pp. 2179-2191, 2023

Authors: Shah, Sayed Kifayat | Tang, Zhongjun | Yuan, Jingbo | Popp, József | Acevedo-Duque, Ángel

Article Type: Research Article

Abstract: Despite the studies probing the factors associated with the adoption of 5G technology products, the current state of knowledge about this new technology products is still fragmented. Previous research has mainly concentrated on the “cumulative impact” of factors rather than the complexities of behavior. Based on complexity theory, this article aims to explain the behavioral intention of using 5G technology products by evaluating the combination of functional (i.e. price and quality), social (i.e. environmental awareness and knowledge) and consumer personality (i.e. openness and consciousness) factors as causal configuration. A sample of 150 Chinese consumers was examined using the fuzzy set …qualitative comparative analysis (fsQCA) technique. The fsQCA outcomes illustrate that five different and effective configurations of functionality, social, and consumer personality factors exist to attain apex level intention of using 5G technology products. This article extends the existing literature by espousing a new procedural attitude to divulge the intricacy of 5G products adoption. It also provides valuable suggestions for 5G technology service managers and manufacturers to enhance the technology, social, and consumer personality features combination to implement 5G technology products successfully. Show more

Keywords: 5G technology, fsQCA, Complexity, China, Decision-making.

DOI: 10.3233/JIFS-223129

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 2, pp. 2193-2207, 2023

Authors: Ganesan, Balaraman | Raman, Sundareswaran | Marayanagaraj, Shanmugapriya | Broumi, Said

Article Type: Research Article

Abstract:  Let N  = (V , E ) be a simple graph and let X be a subset of V  (N ). If every node not in X lies on a geodesic path between two nodes from X then it is called a geodetic set. The geodetic number g  (N ) is the minimum cardinality of such set X . The subset X is called a dominating set if every node not in X has at least one neighbour in X . The minimum number of nodes of a dominating set is known as domination number γ (N …). If the subset X is a geodetic set as well as a dominating set then it is called a geodetic dominating set. The minimum cardinality of a geodetic dominating set is known as geodetic domination number γg  (N ). The geodetic domination integrity of N is defined to be DI g  (N ) = min {|X | + m  (N  - X ) : X is a geodetic dominating set of N }, where m  (N  - X ) denotes the order of the largest component of N  - X . Uncertain networks can be modelled using fuzzy graphs. In a graph, each vertex and each edge are equally significant. However, in fuzzy graphs, each vertex and each edge is important in terms of fuzziness in their own right. In this study, the concepts of geodetic dominating sets in fuzzy graphs and geodetic domination number are defined and bounds are obtained. Moreover, the vulnerability parameter Geodetic domination integrity is introduced in fuzzy graphs. Further, the geodetic domination integrity for complete fuzzy graphs, complete bipartite fuzzy graphs, Cartesian product of two strong fuzzy graphs and bounds are also discussed. The applications of this parameter are applied to a telecommunication network system model to identify the key persons in the system and applied in a fuzzy social network to find the most influential group within the network. Show more

Keywords: Geodetic set, dominating set, geodetic dominating set, geodetic domination integrity set, fuzzy graphs, Complete fuzzy graphs

DOI: 10.3233/JIFS-223249

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 2, pp. 2209-2222, 2023

Authors: Srilakshmi, A. | Geetha, K.

Article Type: Research Article

Abstract: In this study, a unique generative adversarial network (GAN) architectural variation was suggested, which engages in adversarial game serve by preserving an appropriate distance in the latent dimension of the network. This method overcomes the mode collapse problem with a small dataset. Extensive experiments are conducted using the segmented medical leaf dataset with various classes and the generator network is able to produce all the artificial image classes. This is accomplished by combining a unique training technique with a reasonably simple model design.

Keywords: Mode collapse, image generation, generative adversarial networks, leaf images

DOI: 10.3233/JIFS-230212

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 2, pp. 2223-2233, 2023

Authors: Nandipati, Bhagya Lakshmi | Devarakonda, Nagaraju

Article Type: Research Article

Abstract: Lung cancer is a dangerous tumor that requires accurate diagnosis for effective treatment. Traditional diagnosis involves invasive and time-consuming histologic examination, and radiologists face challenges in localizing lung tumors. Deep neural convolutional networks are frequently used to locate lung cancer, but this is still difficult when not accounting for surrounding lung tissue. Despite progress in research, healthcare still uses deep learning models to improve the precision and sensitivity of large datasets. CNN (Convolutional Neural Network) accuracy standards are adequate, but image properties such as flips, construction, and other uncommon alignments diminish its efficiency. CNN also does not store the geometric …distribution between scanned picture features. CT (Computed Tomography) and PET (Positron Emission Tomography) scans require a method that takes into consideration the spatial information of picture characteristics, as they are vulnerable to alignment problems during the perusing process. To address these issues, the authors propose MCNet (MobileNetV2 with Capsule Network), a hybrid network that adopts feature extraction and categorization from MobileNetV2, and capsule network is used to overcome the limitations of convolutional neural networks (CNNs) when it comes to processing images with abnormal orientations, such as tilting or rotation. Although CNNs are effective in processing images presented in a standard orientation, they have difficulty handling variations in image orientation. In this work, MobileNetV2 serves as a backbone network for Capsule Networks in lung cancer diagnosis. The lung image collection dataset verifies the effectiveness of MCNet, and experimental results show that MCNet technology performs better than previous state-of-the-art techniques. The proposed hybrid MCNet architecture achieves the clinical goal of lung cancer diagnosis with a lower computational cost, reducing processing time complexity and false positive rates compared to current techniques. Show more

Keywords: MCNet, CNN, CT, PET, LUAD, LUSC, feature extraction

DOI: 10.3233/JIFS-231145

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 2, pp. 2235-2252, 2023

Authors: Sivasankar, S. | Bera, Sanchari | Maaz, Syed Ibrahim | Pal, Madhumangal

Article Type: Research Article

Abstract: A new concept of vertices in a fuzzy graph known as defective vertices is introduced here. A vertex in a fuzzy network is called defective if no edges incident with it are strong. Defective vertex cannot be ignored when determining dominance in a fuzzy network because they are a part of the network. Finding defective vertices in a network is not much difficult when the adjacency matrix is given. In this paper, the novel concept of defective vertices of a fuzzy graph is introduced. Based on this idea a stable domination set and a stable domination number are defined. This …also optimised the network by establishing minimal connectivity. We have proposed three algorithms for finding the defective vertices, establishing stable connectivity, and determining the stable domination number for a given graph. An application of stable domination in the diagnosis of chickenpox disease is demonstrated to show the effectiveness of the proposed algorithms. Show more

Keywords: Fuzzy graph, stable fuzzy graph, defective vertex, stable domination set, stable domination number

DOI: 10.3233/JIFS-223545

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 2, pp. 2253-2265, 2023

Authors: Qiao, Lin | Fan, Lijun | He, Yao | Zhou, Yan

Article Type: Research Article

Abstract: Aiming at the problem that manufacturing enterprises that rely more on asset projects currently lack effective means of divestiture of non performing assets, starting from incomplete information theory, this paper derives an optimal decision-making model for the divestiture path of non performing assets caused by the quality and safety crisis of manufacturing enterprises in an incomplete information environment, and uses the comprehensive method of SUMDII to establish a comprehensive integrated optimization model that reflects subjective evaluation and objective information. In addition, this study provides specific decision-making methods and implementation steps for optimizing the stripping path of non-performing assets. The empirical …analysis results verify and demonstrate the feasibility, operability, accuracy, and applicability of the established model. The results show that the model designed in the study exhibits strong stability in sensitivity testing. When the parameter vectors are taken as (1,0,0,0), (1,1,0,0), (1,1,0,0), and (1,1,1,1), respectively, the ranking results corresponding to the first three parameter vectors are stable, all of which are A2 > A4 > A1 > A3. At the same time, the applied decision-making result of the model is A4 > A1 > A2 > A3, which is consistent with the best scheme evaluated by experts and superior to most comparative models. At the same time, in the analysis of decision-making characteristics, the research and design model has the most comprehensive review of decision-making elements, which is superior to other comparative models. It can be seen that the model designed by the research can lead to higher quality NPL divestiture schemes, which can help manufacturing enterprises improve asset quality and weaken the negative impact of the quality and safety crisis in manufacturing enterprises. Show more

Keywords: Non-performing asset, stripping path optimization, stochastic and uncertain multi-attribute decision-making with incomplete information, fuzzy rough sets, projection pursuit, optimization decision-making

DOI: 10.3233/JIFS-224162

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 2, pp. 2267-2278, 2023

Authors: Lu, Xiaohong | Ma, Chong | Yang, Banghua | Sun, Shixuan | Xu, Kai

Article Type: Research Article

Abstract: Friction stir welding (FSW) is a complex thermo-mechanical coupling process. Tensile strength is an important evaluation index of the mechanical properties of welded joints. How to realize the real-time prediction of tensile strength of the friction stir welded joints to reflect the dynamic change of welding state is a problem in the field. To solve this problem, this paper presents a multi-scale one-dimensional convolutional neural network (Multi-scale 1D CNN) prediction model using time series data of temperature and axial force as inputs to realize the online prediction of tensile strength of welded joints. Firstly, FSW experiments are carried out to …obtain time series data of temperature and axial force. Tensile strength values of the welded joints is obtained by tensile tests. The time series data and tensile strength values are fused as a dataset. Then Multi-scale 1D CNN, traditional 1D CNN and Multi-channel 1D CNN prediction models are established and trained with the dataset, respectively. Finally, by comparing the prediction performance of the three models, Multi-scale 1D CNN is proved to be more suitable for analyzing time series data to feedback the dynamic change of tensile strength of the joints during welding. Show more

Keywords: FSW, axial force, tensile strength, 1D CNN, temperature, online prediction

DOI: 10.3233/JIFS-230144

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 2, pp. 2279-2288, 2023

Authors: Nirupama, V. | Nair, Prabha Shreeraj | Kishore Kumar, ATA | Murthy, Mantripragada Yaswanth Bhanu | Malhotra, Priyanka | Taqui, Syed Noeman | Almoallim, Hesham S. | Alharbi, Sulaiman Ali | Raghavan, S.S.

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-231903

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 2, pp. 2289-2304, 2023

Authors: Balcı, Sonay Görgülü | Ersöz, Süleyman | Lüy, Murat | Türker, Ahmet Kürşad | Barışçı, Necaattin

Article Type: Research Article

Abstract: It is known that in crowded environments such as educational institutions and workplaces, keeping indoor air quality and climate within certain limits contributes to success and production. For this purpose, a system has been developed to ensure air quality well-being in working environments. In our study, the Arduino processor managed by the fuzzy logic control system (FLC) starts to work with the trigger of the motion sensor HC-SR501. The inputs of the FLC system are defined as LM-35 sensor for temperature, DHT-11 for humidity, MQ-135 for air quality, MQ-9 sensor for CO and explosive gas. The designed system evaluates the …instantaneous data obtained from the fuzzy logic system rule base and decides which of the output air filter, heater and alarm systems will operate at what speed. In order to increase system efficiency, fuzzy logic input membership values are optimized by genetic algorithm. Show more

Keywords: Arduino, fuzzy logic, air quality, genetic optimization

DOI: 10.3233/JIFS-223955

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 2, pp. 2305-2317, 2023