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

Authors: Ali, Jawad | Ali, Jawad | Naeem, Muhammad | Mahmood, Waqas

Article Type: Research Article

Abstract: The q-rung picture linguistic set (q-RPLS) is an effective tool for managing complex and unpredictable information by changing the parameter ‘q’ regarding hesitancy degree. In this article, we devise some generalized operational laws of q-RPLS in terms of the Archimedean t-norm and t-conorm. Based on the proposed generalized operations, we define two types of generalized aggregation operators, namely the q-rung picture linguistic averaging operator and the q-rung picture linguistic geometric operator, and study their relevant characteristics in-depth. With a view toward applications, we discuss certain specific cases of the proposed generalized aggregation operators with a range of parameter values. Furthermore, …we explore q-rung picture linguistic distance measure and its required axioms. Then we put forward a technique for q-RPLSs based on the proposed aggregation operators and distance measure to solve multi-attribute decision-making (MADM) challenges with unknown weight information. At last, a practical example is presented to demonstrate the suggested approaches’ viability and to perform the sensitivity and comparison analysis. Show more

Keywords: q-rung-Picture linguistic fuzzy set, generalized operations, generalized aggregation operators, entropy, decision-making

DOI: 10.3233/JIFS-222292

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 3, pp. 4419-4443, 2023

Authors: Umamaheswari, K.M. | Muthu kumaran, A.M.J.

Article Type: Research Article

Abstract: Cloud technology has raised significant prominence providing a unique market economic approach for resolving large-scale challenges in heterogeneous distributed systems. Through the use of the network, it delivers secure, quick, and profitable information storage with computational capability. Cloud applications are available on-demand to meet a variety of user QoS standards. Due to a large number of users and tasks, it is important to achieve efficient scheduling of tasks submitted by users. One of the most important and difficult non-deterministic polynomial-hard challenges in cloud technology is task scheduling. Therefore, in this paper, an efficient task scheduling approach is developed. To achieve …this objective, a hybrid genetic algorithm with particle swarm optimization (HGPSO) algorithm is presented. The scheduling is performed based on the multi-objective function; the function is designed based on three parameters such as makespan, cost, and resource utilization. The proper scheduling system should minimize the makespan and cost while maximizing resource utilization. The proposed algorithm is implemented using WorkflowSim and tested with arbitrary task graphs in a simulated setting. The results obtained reveal that the proposed HGPSO algorithm outperformed all available scheduling algorithms that are compared across a range of experimental setups. Show more

Keywords: Cloud computing, HGPSO, workflow, task scheduling, makespan, resource utilization, multi-objective function, and fitness

DOI: 10.3233/JIFS-222842

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 3, pp. 4445-4458, 2023

Authors: Garg, Harish | Kahraman, Cengiz | Ali, Zeeshan | Mahmood, Tahir

Article Type: Research Article

Abstract: Complex Pythagorean fuzzy set (CPFS) is a massive influential principle for managing ambiguity and inconsistent information in genuine life dilemmas. To determine the relationship among any number of attributes, the Hamy mean (HM) operators based on interaction operational laws are very dominant and massive flexible to manage awkward and problematic information. This study aims to combine the complex Pythagorean fuzzy (CPF) information with interaction HM operators to initiate the CPF interaction HM (CPFIHM) operator, CPF interaction weighted HM (CPFIWHM) operator, CPF interaction dual HM (CPFIDHM) operator, CPF interaction weighted dual HM (CPFIWDHM) operator and their powerful properties. Additionally, a decision-making …strategy for determining the security threats in the computer is elaborated under the interaction of HM operators based on the CPF setting. Numerous examples are illustrated with the help of presented operators to determine the consistency and flexibility of the investigated operators. Finally, with the help of sensitivity analysis, advantages, and geometrical representation, the supremacy, and efficiency of the presented works are also elaborated. Show more

Keywords: Complex pythagorean fuzzy sets, interaction hamy mean operators, interaction dual hamy mean operators, security threats in computers

DOI: 10.3233/JIFS-220947

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 3, pp. 4459-4479, 2023

Authors: Neena Raj, N.R. | Shreelekshmi, R.

Article Type: Research Article

Abstract: This paper presents a secure image authentication scheme for tamper localization and recovery at pixel level. The proposed scheme encrypts the watermark comprising tamper localization code and self-recovery code using chaotic sequence to ensure security. This scheme uses pixel to block conversion technique for ensuring lossless recovery of the original image from an untampered watermarked image. For enhancing the localization accuracy, a multilevel tamper localization strategy is used. The experimental results show that the proposed scheme generates watermarked images with minimal information loss and can withstand copy-move, image splicing, content removal, vector quantization, collage and content only attacks. This scheme …has better security, better tamper localization accuracy and better recovered image quality under extensive tampering and takes less computation time in comparison to the state-of-the-art schemes. Show more

Keywords: Chaotic sequence, fragile watermarking, image authentication, image recovery, tamper localization

DOI: 10.3233/JIFS-221245

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 3, pp. 4481-4493, 2023

Authors: Shi, Jianzhong

Article Type: Research Article

Abstract: Fuzzy clustering has been widely applied in T-S fuzzy model identification for nonlinear systems, however, tradition type-1 fuzzy clustering algorithms can’t deal with uncertainties in real world, an improved interval type-2 fuzzy c-regression model (IT2-FCRM) clustering is proposed for T-S fuzzy model identification in this paper. The improved IT2-FCRM adapts a new objective function, which makes the boundary of clustering more clearly and reduces the influence of outliers or noisy data on clustering results. The premise parameters of T-S fuzzy model are upper and lower hyperplanes obtained by improved IT2-FCRM, and the upper and lower hyperplanes are used to build …hyper-plane-shaped type-2 Gaussian membership function. Compared with the hyper-sphere-shaped membership function of tradition IT2-FCRM, the hyper-plane-shaped membership function is more coincided with point to plane sample distance described by FCRM clustering. The simulation results of several benchmark problems and a real bed temperature in circulating fluidized bed plant show that the identification algorithm has higher accuracy. Show more

Keywords: Fuzzy identification, interval type-2 fuzzy c-regression model, fuzzy clustering, T-S fuzzy model, orthogonal least squares

DOI: 10.3233/JIFS-221434

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 3, pp. 4495-4507, 2023

Authors: Bakhshi, M. | Ahn, S. S. | Jun, Y. B. | Xin, X. L. | Borzooei, R. A.

Article Type: Research Article

Abstract: We study the lattice structure of fuzzy A-ideals in an mv-module M (fai (M), symbolically) and show that it is a complete Heyting lattice and so the set of its pseudocomplements forms a Boolean algebra. In the sequel, the properties of fuzzy congruences in an mv-module are investigated and using them some structural theorems are stated and proved. Finally, it is proved that fai (M) can be embedded into the lattice of fuzzy congruences.

Keywords: mv-module, fuzzy A-ideal, fuzzy congruence, distributive lattice

DOI: 10.3233/JIFS-221552

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 3, pp. 4509-4519, 2023

Authors: Li, Yufei | Hu, Nanyan | Ye, Yicheng | Wu, Menglong

Article Type: Research Article

Abstract: In order to solve the problem of underground goafs, particularly in light of the importance ranking of evaluation indices being more subjective and catastrophe progression values being large and too concentrated in the catastrophe progression method, the importance of multiple indices is ranked by the maximizing deviation method. An S-shaped curve is used to establish a regression function to improve the value of catastrophe progression method. First, three first-level evaluation indices and eight second-level evaluation indices are selected to establish an index system for risk evaluation of the underground goaf. Next, based on the principle of catastrophe progression method, an …improved catastrophe model for its risk evaluation is established. Finally, sample training and verification are performed based on the improved evaluation model. The evaluation results show that the improved catastrophe progression method objectively ranks the importance of the evaluation indices of each layer, which improves the credibility of the evaluation results. The evaluation results are consistent with the actual geological data and detection results, which verifies the validity and accuracy of the evaluation model. However, only 87.5% of the risk levels obtained by the fuzzy comprehensive evaluation method are completely consistent with the improved catastrophe progression method, and the ranking error of risk value within one rank also accounted for 87.5%. Therefore, the results calculated by the improved catastrophe progression method are more accurate. The numerical gap of the improved catastrophe progression values becomes larger, from [0.796, 0.969] to [0.275, 0.691], which is 2.405 times of the interval difference of the catastrophe progression values before the improvement, which makes the numerical distribution of the catastrophe progression values more scientific and reasonable, with a higher resolution level. Therefore, it is reasonable and feasible to use the improved catastrophe progression method for the risk evaluation of the underground goaf, which can provide a certain theoretical basis and engineering guidance for underground goaf disaster control and management. Show more

Keywords: Catastrophe progression method, maximizing deviation method, regression model, underground goaf, risk evaluation, catastrophe model

DOI: 10.3233/JIFS-222094

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 3, pp. 4521-4536, 2023

Authors: Bai, Wenhui | Zhang, Chao | Zhai, Yanhui | Sangaiah, Arun Kumar

Article Type: Research Article

Abstract: Water quality inspection (WQI) is one of the primary ways to ensure the safe utilization of water resources, and complicated data modeling, fusion and analysis play a significant role in seeking the resource with the best water quality. Nevertheless, the challenges of missing data, relatively large differences in decision results and bounded rationality owned by decision-makers (DMs) in terms of WQI still exist nowadays. Thus, from the aspect of stable and behavioral decision-making in multi-granularity incomplete intuitionistic fuzzy information systems (MG-IIFISs), the paper investigates a comprehensive multi-attribute group decision-making (MAGDM) approach for the application of WQI. First, the concept of …MG-IIFISs is built by modeling MAGDM problems with intuitionistic fuzzy numbers (IFNs), then a new transformation scheme is constructed for transforming MG-IIFISs into multi-granularity intuitionistic fuzzy information systems (MG-IFISs) based on the similarity principle. Second, three types of multigranulation intuitionistic fuzzy probabilistic rough sets (MG IF PRSs) are developed by referring to the MULTIMOORA (Multi-Objective Optimization by Ratio Analysis plus the full MULTIplicative form) method. Afterwards, attribute weights are objectively calculated based on the best-worst method (BWM), and a new stable and behavioral MAGDM approach is constructed by means of the TODIM (an acronym in Portuguese for interactive multi-criteria decision-making) method. At last, a case study in the setting of WQI is conducted with the support of a UCI data set, and sensitivity analysis, comparative analysis and experimental analysis are investigated to display the validity of the proposed approach. In general, the proposed approach improves the stability of decision results via MULTIMOORA and BWM, and also fully considers the bounded rationality of DMs’ psychological behaviors from the aspect of the TODIM method, which has certain advantages in the community of MAGDM studies. Show more

Keywords: Granular computing, rough set, MULTIMOORA, incomplete intuitionistic fuzzy information system, water quality inspection

DOI: 10.3233/JIFS-222385

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 3, pp. 4537-4556, 2023

Authors: Kaur, Kamalpreet | Gupta, Asha

Article Type: Research Article

Abstract: The present paper proposes a novel version of inducing nano topology by using new kinds of approximation operators via two ideals with respect to a general binary relation. This approach improves the accuracy of the approximation quite significantly. These newly defined approximations constitute the generalized version of rough sets defined by Pawlak in 1982. A comparison is drawn between the suggested technique and the already existing ones to demonstrate the significance of the proposed ideology. In addition, the standard notion of nano topology, based on an equivalence relation is generalized to the binary relation, which can have a broader scope …when applied to intelligent systems. Also, the significance of this approach is demonstrated by an example where an algorithm is given to find the key factors responsible for the profit of a company along with the comparison to the previous notions. Likewise, the proposed algorithm can be used in all fields of science to simplify complex information systems in extracting useful data by finding the core. Show more

Keywords: Nano topology, rough sets, ideals, bi-ideal approximation, core

DOI: 10.3233/JIFS-222958

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 3, pp. 4557-4567, 2023

Authors: Arulaalan, M. | Aparna, K. | Nair, Vicky | Banala, Rajesh

Article Type: Research Article

Abstract: It is difficult for underwater archaeologists to recover the fine details of a captured image on the seabed when the image quality worsens due to the presence of more noisy artefacts, a mismatched device colour map, and a blurry image. To resolve this problem, we present a machine learning-based image restoration model (ML-IRM) for improving the visual quality of underwater images that have been deteriorated. Using this model, a home-made bowl set-up is created in which a different liquid concentration is used to replicate seabed water variation, and an object is dipped, or a video is played behind the bowl …to recognise the object texture captured image in high-resolution for training the image restoration model is proposed. Gaussian and bidirectional pre-processing filters are used to both the high and low frequency components of the training image, respectively. To improve the clarity of the high-frequency channel background, soft-thresholding decreases the presence of distracting artefacts. On the other hand, the ML-IRM model can effectively keep the object textures on a low frequency channel. Experiment findings show that the proposed ML-IRM model improves the quality of seabed images, eliminates colour mismatches, and allows for more detailed information extraction. Blue shadow, green shadow, hazy, and low light test samples are randomly selected from all five datasets including U45 [1 ], EUVP [2 ], DUIE [3 ], UIEB [4 ], UM-ImageNet [5 ], and the proposed model. Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index (SSIM) are computed for each condition separately. We list the values of PSNR (at 16.99 dB, 15.96 dB, 18.09 dB, 15.67 dB, 9.39 dB, 17.98 dB, 19.32 dB, 14.27 dB, 12.07 dB, and 25.47 dB) and SSIM (at 0.52, 0.57, 0.33, 0.47, 0.44, and 0.23, respectively. Similarly, it demonstrates that the proposed ML-IRM achieves a satisfactory result in terms of colour correction and contrast adjustment when applied to the problem of improving underwater images captured in low light. To do so, high-resolution images were captured in two low-light conditions (after 6 p.m. and again at 6 a.m.) for the training image datasets, and the results of their observations were compared to those of other existing state-of-the-art-methods. Show more

Keywords: ML-IRM, image denoising, different low-lighting conditions, Gaussian and bidirectional filters, high and low frequency channel

DOI: 10.3233/JIFS-223310

Citation: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 3, pp. 4569-4591, 2023