International Journal of Knowledge-based and Intelligent Engineering Systems - Volume Pre-press, issue Pre-press

Authors: D, Mary Jiny | Navamani, G. | Shanmugapriya, R. | Kumar, Raman | Stević, Željko | Kumar, Rajender | Kumar, Sandeep

Article Type: Research Article

Abstract: The eternal 1-secure set, strategically protects graphical structures against attacks by placing sentinels within dominating sets. This study adapts this concept to real-world scenarios, like emergency response systems, by addressing challenges such as roadblocks and traffic congestion. We introduce the secure set and the eternal 1-secure set for fuzzy graphs based on edge membership levels J. Our analysis examines the relationship between the security number of a fuzzy graph G at level J and the domination number of its spanning subgraph at level J, demonstrating the potential of the eternal 1-secure set to enhance security measures in dynamic environments.

Keywords: Fuzzy graph, fuzzy domination number, eternal 1-security number, fuzzy path, fuzzy cycle

DOI: 10.3233/KES-240290

Citation: International Journal of Knowledge-based and Intelligent Engineering Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2024

Authors: Wang, Qian

Article Type: Research Article

Abstract: Undoubtedly, the Internet is an indispensable part of daily life in this era. In this context, the emergence of new media has played a disruptive role in information dissemination, and has also provided new definitions and evaluation standards for the impact of information dissemination. In an environment where excellent research is constantly emerging, it is of research value to redefine the elements of new media information dissemination from a new perspective and provide specific examples to analyze their information dissemination paths. The new-media information communication influence evaluation from super intellectual property (IP) perspective is a multipleattribute group decisionmaking (MAGDM) problem. …Recently, the Exponential TODIM (an acronym in Portuguese of interactive and multicriteria decision making) method has been used to cope with MAGDM issues. The interval-valued Pythagorean fuzzy sets (IVPFSs) are used as a tool for characterizing uncertain information during the new-media information communication influence evaluation from super intellectual property. In this manuscript, the interval-valued Pythagorean fuzzy Exponential TODIM (ExpTODIM) (IVPFExpTODIM) method is built to solve the MAGDM under IVPFSs. In the end, a numerical case study for new-media information communication influence evaluation from super intellectual property is given to validate the proposed method. The main research contribution of this paper is constructed: (1) the Exponential TODIM (ExpTODIM) method is extended to the IVPFSs; (2) the interval-valued Pythagorean fuzzy Exponential TODIM (ExpTODIM) (IVPF-ExpTODIM) method is built to solve the MAGDM under IVPFSs; (3) the information Entropy is used to obtain the weight values based on the score value and accuracy value under IVPFSs; (4) Finally, a numerical case study for new-media information communication influence evaluation from super intellectual property is given to validate the proposed method. Show more

Keywords: Multiple attribute group decision making (MAGDM), interval-valued Pythagorean fuzzy sets (IVPFSs), Exponential TODIM (ExpTODIM) method, information communication influence evaluation

DOI: 10.3233/KES-230121

Citation: International Journal of Knowledge-based and Intelligent Engineering Systems, vol. Pre-press, no. Pre-press, pp. 1-18, 2024

Authors: Wei, Kang | Huang, Yuhan

Article Type: Research Article

Abstract: The highest level of interface design for online games is to achieve invisibility, which means that the interface is very natural and easy to use. Players are proficient in using it and fully immerse themselves in the world of online games. It seems that the interface is transparent and they no longer feel its existence. Excellent online game interface design is the requirement of users that runs through the entire design process. But this is not to say that the usability of online game software can surpass other factors. All great designs seek a balance and harmony between artistic beauty, …reliability, security, usability, cost, and performance. The quality evaluation of online games interface design is a multiple-attribute group decision-making (MAGDM) problem. Recently, the Evaluation Based on Distance from Average Solution (EDAS) technique, cosine similarity measure (CSM), Dice similarity measure (DSM), Jaccard similarity measure (JSM) and entropy technique has been separately employed to cope with MAGDM issues. The probabilistic linguistic term sets (PLTSs) are employed as a tool for conveying uncertain information during the quality evaluation of online games interface design. In this paper, the EDAS technique is expanded to the PLTSs and the probabilistic linguistic EDAS (PL-EDAS) technique based on cosine similarity measure (CSM), Dice similarity measure (DSM) and Jaccard similarity measure (JSM) is constructed to manage MAGDM issue. The information entropy technique is employed to implement the weight values based on CSM technique, DSM technique and JSM technique under PLTSs. Finally, the quality evaluation of online games interface design is employed to demonstrate the PL-EDAS technique and some comparative analysis is employed to demonstrate the PL-EDAS technique. Thus, the main research contribution of this work is constructed: (1) the information entropy technique is constructed to implement the attribute weight values based on CSM technique, DSM technique and JSM technique; (2) the PL-EDAS technique is constructed under PLTSs based on CSM technique, DSM technique and JSM technique; (3) an example for quality evaluation of online games interface design is employed to verify PL-EDAS technique and several decision comparative analysis is employed to verify the PL-EDAS technique. Show more

Keywords: Multiple attribute group decision making (MAGDM), probabilistic linguistic term sets (PLTSs), EDAS technique, information entropy, online games interface design

DOI: 10.3233/KES-230548

Citation: International Journal of Knowledge-based and Intelligent Engineering Systems, vol. Pre-press, no. Pre-press, pp. 1-22, 2024

Authors: Zhang, Hong | Liu, Shaojie | Zhang, Lupeng

Article Type: Research Article

Abstract: The magnitude of the utility of a good depends on the subjective psychological evaluation of the good by the consumer, and the difference in the obtained utility will affect consumer behavior, taking into account that consumers are not completely rational in the actual decision-making process, and that under uncertain conditions, consumers’ perception of loss is much greater than gain. This paper investigates an improved scoring function based on consumer utility and loss aversion, which takes into account the effects of different decision makers’ preferences and loss aversion on the decision outcome. First, the existing score function of intuitionistic fuzzy sets …is analyzed in depth, an improved score function is defined, and its properties and special cases are studied in detail. Then, a Multi-Attribute Decision-Making (MADM) method is proposed based on the improved scoring function combined with the intuitionistic fuzzy hybrid average (IFHA) operator. Finally, a real case of new energy-used car transaction decision-making is given, and the proposed method is validated by Spearman’s correlation coefficient, WS ranking similarity coefficient, and RW coefficient to prove its practicality and effectiveness. Show more

Keywords: Intuitionistic fuzzy set, MADM, consumer utility, loss aversion, used new energy car, improved score function, spearman rank correlation coefficient

DOI: 10.3233/KES-230015

Citation: International Journal of Knowledge-based and Intelligent Engineering Systems, vol. Pre-press, no. Pre-press, pp. 1-18, 2024

Authors: Yuan, Guolun | Yang, Yuhao

Article Type: Research Article

Abstract: In order to solve the problem that existing methods are affected by fundamental frequency and harmonic frequency oscillation of new energy vehicle engine, a new energy vehicle engine fault detection method based on wavelet transform and support vector machine is proposed. Firstly, a detection model of abnormal noise signal of automobile engine fault is established, and the time-frequency parameters of basis function are adjusted adaptively. Then, the mechanical excitation component and the battery excitation component in the engine surface radiation noise are separated, and the new energy vehicle engine fault signal is decomposed by feature decomposition and multi-scale separation. Finally, …wavelet transform combined with support vector machine algorithm was used to extract fault features of new energy vehicles, fuzzy clustering was carried out, and time-frequency analysis of fault signals was carried out in fractional Fourier domain to realize fault detection of new energy vehicle engines. The test results show that the method has high fault identification level and good clustering of fault feature points for new energy vehicle engine fault detection, and can effectively improve the ability of engine fault detection with good application effect. Show more

Keywords: Wavelet transform, support vector machine, new energy vehicle, engine failure, fault detection

DOI: 10.3233/KES-230422

Citation: International Journal of Knowledge-based and Intelligent Engineering Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2024

Authors: V, Edward Naveen | A, Jenefa | T.M, Thiyagu | A, Lincy | Taurshia, Antony

Article Type: Research Article

Abstract: In the realm of deep learning, Generative Adversarial Networks (GANs) have emerged as a topic of significant interest for their potential to enhance model performance and enable effective data augmentation. This paper addresses the existing challenges in synthesizing high-quality data and harnessing the capabilities of GANs for improved deep learning outcomes. Unlike traditional approaches that heavily rely on manually engineered data augmentation techniques, our work introduces a novel framework that leverages DeepGANs to autonomously generate diverse and high-fidelity data. Our experiments encompass a diverse spectrum of datasets, including images, text, and time series data. In the context of image classification …tasks, we conduct experiments on the widely recognized CIFAR-10 dataset, which consists of 50,000 image samples. Our results demonstrate the remarkable efficacy of DeepGANs in enhancing model performance across various data domains. Notably, in image classification using the CIFAR-10 dataset, our innovative approach achieves an impressive accuracy of 97.2%. This represents a substantial advancement beyond conventional CNN models, underscoring the profound impact of DeepGANs in the realm of deep learning. In summary, this research sheds light on DeepGANs as a fundamental component in the pursuit of enhanced deep learning performance. Our framework not only overcomes existing limitations but also heralds a new era of data augmentation, with generative adversarial networks leading the way. The attainment of an accuracy rate of 97.2% on CIFAR-10 serves as a compelling testament to the transformative potential of DeepGANs, solidifying their pivotal role in the future of deep learning. This promises the development of more robust, adaptive, and accurate models across a myriad of applications, marking a significant contribution to the field. Show more

Keywords: Data augmentation, DeepGAN, generative adversarial networks (GANs), deep learning, style transfer

DOI: 10.3233/KES-230326

Citation: International Journal of Knowledge-based and Intelligent Engineering Systems, vol. Pre-press, no. Pre-press, pp. 1-17, 2024

Authors: Ashir, Abubakar Muhammad

Article Type: Research Article

Abstract: In the manuscript, an automatic approach for analysis and detection of various stages of retinopathy defects in human eyes has been proposed. The approach consists of a robust preprocessing technique of the retina fundus image to mitigate the effects of noise and poor lightening in the image. To realize a compressive analysis of the defects, methods for extracting blood vessels and optic disc in the fundus image has also been developed. Adaptive Histogram Equalization (AHE), median filtering and Connected Component Analysis techniques were used in separating blood vessels and optic disc from each fundus image. The pre-processing utilizes canny edge …detection and Morphological Closing on the fundus image. An interval type-2 fuzzy (IT2F) clustering is applied to segments an input image into four clusters. These four clusters from the fuzzy segmentation are further analyzed to extract various stages of retinopathy abnormalities (e.g., Hemorrhage, hard exudates etc.). The extracted blood vessels and optic disc are removed from the analysis to enhance the defects detection process. Experiments were conducted on DIARETDB1 database. The experimental results obtained are validated using the ground-truth images contained in DIARETDB1 database. Impressive results are recorded throughout the experiment. Hard-Exudates and Hemorrhage were detected from the fundus images and results from similarity indexes such as, accuracy (94.11%) sensitivity (93.03%) and specificity (98.45%) were recorded. Show more

Keywords: Retinopathy, fuzzy c-means, connected component analysis, canny edge detection, morphological operation, high pass filter (HPF)

DOI: 10.3233/KES-230443

Citation: International Journal of Knowledge-based and Intelligent Engineering Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2024

Authors: Abluton, Alessandro | Ciarlo, Daniele | Portinale, Luigi

Article Type: Research Article

Abstract: In this paper, we introduce a retrieval framework designed for e-commerce applications, which employs a multi-modal approach to represent items of interest. This approach incorporates both textual descriptions and images of products, alongside a locality-sensitive hashing (LSH) indexing scheme for rapid retrieval of potentially relevant products. Our focus is on a data-independent methodology, where the indexing mechanism remains unaffected by the specific dataset, while the multi-modal representation is learned beforehand. Specifically, we utilize a multi-modal architecture, CLIP, to learn a latent representation of items by combining text and images in a contrastive manner. The resulting item embeddings encapsulate both the …visual and textual information of the products, which are then subjected to various types of LSH for balancing between result quality and retrieval speed. We present the findings of our experiments conducted on two real-world datasets sourced from e-commerce platforms, comprising both product images and textual descriptions. Promising results have been achieved, demonstrating favorable retrieval time and average precision. These results were obtained through testing the approach with a specifically selected set of queries and with synthetic queries generated using a Large Language Model. Show more

Keywords: Multi-modal embeddings, e-commerce applications, locality sensitive hashing

DOI: 10.3233/KES-240006

Citation: International Journal of Knowledge-based and Intelligent Engineering Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2024

Authors: Mahmood, Tahir | ur Rehman, Ubaid

Article Type: Research Article

Abstract: Resource allocation strategy selection in 5G networks is a MADM (Multi-Attribute Decision-Making) problem, which all the methods defined so far or those used to solve it have neglected the negative aspects of attributes. This can result in the occurrence of information loss and it would be difficult to come to the right decision. Thus, in this paper, we present a MADM technique that can be used to take the negative aspects of attributes into account. This goal will be achieved by the method based on bipolar fuzzy sets (BFS) and tangent trigonometric aggregation operators (AOs). For this, in this article, …firstly, we devise the concept of tangent trigonometric bipolar fuzzy number (TT-BFN) and linked algebraic operators. Then, we deduce tangent trigonometric bipolar fuzzy weighted averaging (TT-BFWA), tangent trigonometric bipolar fuzzy ordered weighted averaging (TT-BFOWA), tangent trigonometric bipolar fuzzy weighted geometric (TT-BFWG), and tangent trigonometric bipolar fuzzy ordered weighted geometric (TT-BFOWG) operators. We also devised the related results of these operators that is idempotency, monotonicity, and boundedness. Further in this manuscript, we investigate a case study “Selection of resource allocation strategy for 5G network” by considering artificial data and employing the invented MADM approach in the environment of BFS and get that “Max-Min Fairness Allocation” is the finest resource allocation strategy in 5G network. Finally, we compare our deduced theory with a few current ones to reveal supremacy and dominance. Show more

Keywords: Resource allocation strategy, 5G network, tangent trigonometric aggregation operators, bipolar fuzzy set

DOI: 10.3233/KES-240086

Citation: International Journal of Knowledge-based and Intelligent Engineering Systems, vol. Pre-press, no. Pre-press, pp. 1-19, 2023

Authors: Zhang, Yanboyu

Article Type: Research Article

Abstract: In this study, the objective is to model a neuronal population using cellular automata (CA) rules that are both simple and realistic. Unlike in previous research, the primary aim is to capture a range of neuronal behaviours with minimal complexity and computational overhead. To achieve this, a two-dimensional lattice of cellular automata was implemented in the C+ ⁣ + programming language, with the lattice and cell structure, cell states, neighbourhood interactions, and governing rules being defined. Various behaviours within the neuronal population were simulated by taking into account the resting state and action potential of each …neuron. Four distinct behaviours in the model were unveiled by our observations: fixed point, rhythmic, chaotic, and dual behaviour. Importantly, the outcomes of the neuronal CA were significantly influenced by the neighbourhood configuration of a neuron. In particular, a dual behaviour also referred to as an intrinsic bifurcation, was induced when the number of neighbouring cells for a neuron was reduced. In a broader sense, the maximum and minimum neighbour counts for a cell were found to serve as low-pass and high-pass filters, respectively, for the output signal of the CA model. Show more

Keywords: Modeling, cellular automata, neuron population, nonlinear dynamics

DOI: 10.3233/KES-230154

Citation: International Journal of Knowledge-based and Intelligent Engineering Systems, vol. Pre-press, no. Pre-press, pp. 1-11, 2024