Journal of Intelligent & Fuzzy Systems - Volume 40, issue 6

Authors: Yuan, Jiahang | Li, Yun | Luo, Xinggang | Li, Lingfei | Zhang, Zhongliang | Li, Cunbin

Article Type: Research Article

Abstract: Regional integrated energy system (RIES) provides a platform for coupling utilization of multi-energy and makes various energy demand from client possible. The suitable RIES composition scheme will upgrade energy structure and improve integrated energy utilization efficiency. Based on a RIES construction project in Jiangsu province, this paper proposes a new multi criteria decision-making (MCDM) method for the selection of RIES schemes. Because that subjective evaluation on RIES schemes benefit under criteria has uncertainty and hesitancy, intuitionistic trapezoidal fuzzy number (ITFN) which has the better capability to model ill-known quantities is presented. In consideration of risk attitude and interdependency of criteria, …a new decision model with risk coefficients, Mahalanobis-Taguchi system and Choquet integral is proposed. Firstly, the decision matrices given by experts are normalized, and then are transformed to minimum expectation matrices according to different risk coefficients. Secondly, the weights of criteria from different experts are calculated by Mahalanobis-Taguchi system. Mobius transformation coefficients based on interaction degree are to calculate 2-order additive fuzzy measures, and then the comprehensive weights of criteria are obtained by fuzzy measures and Choquet integral. Thirdly, based on group decision consensus requirement, the weights of experts are obtained by the maximum entropy and grey correlation. Fourthly, the minimum expectation matrices are aggregated by the intuitionistic trapezoidal fuzzy Bonferroni mean operator. Thus, the ranking result according to the comparison rules using the minimum expectation and the maximum expectation is obtained. Finally, an illustrative example is taken in the present study to make the proposed method comprehensible. Show more

Keywords: Regional integrated energy system, Mahalanobis-Taguchi system, Mobius transformation coefficients, Bonferroni mean

DOI: 10.3233/JIFS-190211

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10333-10350, 2021

Authors: Nawaz, Marriam | Mehmood, Zahid | Bilal, Muhammad | Munshi, Asmaa Mahdi | Rashid, Muhammad | Yousaf, Rehan Mehmood | Rehman, Amjad | Saba, Tanzila

Article Type: Research Article

Abstract: ‘With the help of powerful image editing software, various image modifications are possible which are known as image forgeries. Copy-move is the easiest way of image manipulation, wherein an area of the image is copied and replicated in the same image. The major reason for performing this forgery is to conceal undesirable contents of the image. Thus, means are required to unveil the presence of duplicated areas in an image. In this article, an effective and efficient approach for copy-move forgery detection (CMFD) is proposed, which is based on stationary wavelet transform (SWT), speeded-up robust features (SURF), and a novel …scaled density-based spatial clustering of applications with noise (sDBSCAN) clustering. The SWT allows the SURF descriptor to extract only energy-rich features from the input image. The SURF features can detect the tampered regions even under post-processing attacks like contrast adjustment, scaling, and affine transformation on the images. On the extracted features, a novel scaled density-based spatial clustering of applications with noise (sDBSCAN) clustering algorithm is applied to detect forged regions with high accuracy as it can easily identify the clusters of arbitrary shapes and sizes and can filter the outliers. For performance evaluation, three publicly available datasets namely MICC-F220, MICC-F2000, and image manipulation dataset (IMD) are employed. The qualitative and quantitative analysis demonstrates that the proposed approach outperforms state-of-the-art CMFD approaches in the presence of different post-processing attacks. Show more

Keywords: Sparsely encoded features, sDBSCAN clustering, forensic analysis, forgery detection

DOI: 10.3233/JIFS-191700

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10351-10371, 2021

Authors: Jiao, Yuzhao | Lou, Taishan | Wang, Xiaolei | Zhao, Hongmei

Article Type: Research Article

Abstract: For multi-sensor target tracking system, the accurate state estimation is obtained under the condition that the system model is unbiased and the noise disturbance satisfies the characteristics of independent Gaussian white noise. However, in engineering practice, it is almost impossible to get the accurate system model and also the system noise is non-independent Gaussian white noise. So the traditional state estimation methods are not suitable for uncertainty system with non Gaussian white noise. In this paper, the Kalman Filter-Support Vector Machine (KF-SVM) based data fusion algorithm is proposed for system with model uncertainty and correlated noise. Firstly, the state pre-estimates …are calculated by the proposed improved Kalman Filter for single sensor system. Then, the state estimation is obtained via proposed KF-SVM data fusion algorithm for multi-sensor system. Finally, compared with the traditional algorithms, the simulation results show that the proposed fusion algorithm based on KF-SVM does not need to calculate the sensor cross-covariance matrix and has better estimation accuracy. Show more

Keywords: Support vector machine, kalman filter, data fusion, system uncertainty, cross-correlated noise

DOI: 10.3233/JIFS-192116

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10373-10383, 2021

Authors: Raj, Vinoth | Janakiraman, Siva | Amirtharajan, Rengarajan

Article Type: Research Article

Abstract: Digitized forms of images do widely used for medical diagnostics. To maintain the privacy of an individual in e-health care applications, securing the medical image becomes essential. Hence exclusive encryption algorithms have been developed to protect the confidentiality of medical images. As an alternative to software implementations, the realization of image encryption architectures on hardware platforms such as FPGA offers significant benefit with its reconfigurable feature. This paper presents a lightweight image encryption scheme for medical image security feasible to realize as concurrent architectural blocks on reconfigurable hardware like FPGA to achieve higher throughput. In the proposed encryption scheme, Lorentz …attractor’s chaotic keys perform the diffusion process. Simultaneously, the pseudo-random memory addresses obtained from a Linear Feedback Shift Register (LFSR) circuit accomplishes the confusion process. The proposed algorithm implemented on Intel Cyclone IV FPGA (EP4CE115F29C7) analyzed the optimal number of concurrent blocks to achieve a tradeoff among throughput and resource utilization. Security analyses such as information entropy, histogram, correlation, and PSNR confirms the algorithm’s encryption quality. The strength of diffusion keys was ensured by randomness verification through the standard test suite from the National Institute of Standards and Technology (NIST). The proposed scheme has a larger keyspace of 2384 that guarantees good confusion through near-zero correlation, and successful diffusion with a PSNR of <5 dB towards the statistical attacks. Based on the hardware analysis, the optimal number of concurrent architectural blocks (2 N ) on the chosen FPGA to achieve higher throughput (639.37 Mbps), low power dissipation (138.85 mW), minimal resource utilization (1268 Logic Elements) and better encryption quality for the proposed algorithm is recommended as 4 (with N = 2). Show more

Keywords: Concurrency, lightweight, lorentz attractor, FPGA and encryption

DOI: 10.3233/JIFS-200203

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10385-10400, 2021

Authors: Sun, Zhao | Peng, Qinke | Mou, Xu | Wang, Ying | Han, Tian

Article Type: Research Article

Abstract: In the era of data technology, data growth is occurring at an unprecedented scale. Business data and information are among the most valuable assets. Massive data analysis now drives nearly every aspect of society and can facilitate informed decision-making by businesses. Fully automated data flow detection of anomalies plays a crucial role in maintaining data service stability and preventing malicious attacks. This paper presents an extensible and generic real-time monitoring system framework (EGRTMS) for large-scale time-series data. EGRTMS employs a prediction module and an anomaly detection module within an anomaly filtering layer for the accurate identification of anomalies. Moreover, the …alarm module and anomaly handling module within an anomaly trace processing layer enables the system to respond swiftly to the detected threats. Our solution does not rely on the labelling of anomalies; instead, a predictor module with a deep learning attention-based mechanism learns the normal behaviour of the data, and an anomaly handling module determines the dynamic alarm-threshold by utilizing a sliding window. The results of this study demonstrate that our framework significantly outperforms other anomaly detection systems on most real and synthetic datasets. Show more

Keywords: Real-time monitoring, scalable framework, deep learning, attention-based mechanism, dynamic threshold

DOI: 10.3233/JIFS-200366

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10401-10415, 2021

Authors: Abbasi-Tavallali, Pezhman | Feylizadeh, Mohammad Reza | Amindoust, Atefeh

Article Type: Research Article

Abstract: Cross-dock is defined as the practice of unloading goods from incoming vehicles and loading them directly into outbound vehicles. Cross-docking can simplify supply chains and help them to deliver goods to the market more swiftly and efficiently by removing or minimizing warehousing costs, space requirements, and use of inventory. Regarding the lifetime of perishable goods, their routing and scheduling in the cross-dock and transportation are of great importance. This study aims to analyze the scheduling and routing of cross-dock and transportation by System Dynamics (SD) modeling to design a reverse logistics network for the perishable goods. For this purpose, the …relations between the selected variables are first specified, followed by assessing and examining the proposed model. Finally, four scenarios are developed to determine the optimal values of decision variables. The results indicate the most influencing factors on reaching the optimal status is the minimum distance between the cross-dock and destination, rather than increasing the number of manufactories. Show more

Keywords: Scheduling, routing, transportation, cross-dock, reverse logistics network, perishable goods

DOI: 10.3233/JIFS-200610

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10417-10433, 2021

Authors: Qurashi, Saqib Mazher | Kanwal, Rani Sumaira | Shabir, Muhammad | Ali, Kashan

Article Type: Research Article

Abstract: In this work, we have proposed a new relationship among rough set, soft set and quantales with the help of soft compatible relation. This typical relationship is used to approximate the fuzzy substructures in quantales in association with soft compatible relations by using aftersets and foresets. This type of approximation is extended notation of rough quantales, rough fuzzy subquantales and soft subquantales. We have corroborated this work by considering some test examples containing soft compatible relations over quantales. Moreover, by using soft compatible relations, we will describe the relationship between upper (lower) generalized rough fuzzy soft substructures of quantale and …the upper (lower) approximations of their homomorphic images with the help of weak quantale homomorphism. The comparison of this type approximations and their results affirms the superiority of our new approximation method over current methods on the topic. Show more

Keywords: Quantale, ideals, soft relations, aftersets, forsets, roughness of fuzzy substructures in Quantales

DOI: 10.3233/JIFS-200629

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10435-10452, 2021

Authors: Jin, Zhen-Yu | Yan, Cong-Hua

Article Type: Research Article

Abstract: The main purpose of this paper is to study Hutton type fuzzifying uniformities on linear spaces. Firstly, we show that if a base of a fuzzifying uniformity defined over a linear space is translation-invariant, balanced and absorbed, then it generates a linear fuzzifying topology. From this linear fuzzifying topology, we can construct a new linear fuzzifying uniformity (i.e., a fuzzifying uniformity compatible with the linear structure) which is equivalent to the original fuzzifying uniformity. Secondly, the Hausdorff separation and complete boundedness in linear fuzzifying uniformities are investigated. In addition, as an example, the linear fuzzifying uniformity induced by a fuzzy …norm is also discussed. Show more

Keywords: Linear fuzzifying uniformity, linear fuzzifying topology, complete boundedness, Hausdorff separation axiom, fuzzy norm

DOI: 10.3233/JIFS-200702

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10453-10464, 2021

Authors: Wang, Shuai | Ning, Yufu | Shi, Hongmei | Chen, Xiumei

Article Type: Research Article

Abstract: The least squares estimation can fully consider the given data and minimize the sum of squares of the residuals, and it can solve the linear regression equation of the imprecisely observed data effectively. Based on the least squares estimation and uncertainty theory, we first proposed the slope mean model, which is to calculate the slopes of expected value and each given data, and the average value of these slopes as the slope of the linear regression equation, substituted into the expected value coordinates, and we can get the linear regression equation. Then, we proposed the deviation slope mean model, which …is a very good model and the focus of this paper. The idea of the deviation slope mean model is to calculate the slopes of each given data deviating from the regression equation, and take the average value of these slopes as the slope of the regression equation. Substituted into the expected value coordinate, we can get the linear regression equation. The deviation slope mean model can also be extended to multiple linear regression equation, we transform the established equations into matrix equation and use inverse matrix to solve unknown parameters. Finally, we put forward the hybrid model, which is a simplified model based on the combination of the least squares estimation and deviation slope mean model. To illustrate the efficiency of the proposed models, we provide numerical examples and solve the linear regression equations of the imprecisely observed data and the precisely observed data respectively. Through analysis and comparison, the deviation slope mean model has the best fitting effect. Part of the discussion, we are explained and summarized. Show more

Keywords: Slope mean, deviation slope mean, regression equation, the least squares estimation, uncertainty theory

DOI: 10.3233/JIFS-201112

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10465-10474, 2021

Authors: Wang, Shuang | Ding, Lei | Sui, He | Gu, Zhaojun

Article Type: Research Article

Abstract: Cybersecurity risk assessment is an important means of effective response to network attacks on industrial control systems. However, cybersecurity risk assessment process is susceptible to subjective and objective effects. To solve this problem, this paper introduced cybersecurity risk assessment method based on fuzzy theory of Attack-Defense Tree model and probability cybersecurity risk assessment technology, and applied it to airport automatic fuel supply control system. Firstly, an Attack-Defense Tree model was established based on the potential cybersecurity threat of the system and deployed security equipment. Secondly, the interval probability of the attack path was calculated using the triangular fuzzy quantification of …the interval probabilities of the attack leaf nodes and defensive leaf nodes. Next, the interval probability of the final path was defuzzified. Finally, the occurrence probability of each final attack path was obtained and a reference for the deployment of security equipment was provided. The main contributions of this paper are as follows: (1) considering the distribution of equipment in industrial control system, a new cybersecurity risk evaluation model of industrial control system is proposed. (2) The experimental results of this article are compared with other assessment technologies, and the trend is similar to that of other evaluation methods, which proves that the method was introduced in this paper is scientific. However, this method reduces the subjective impact of experts on cybersecurity risk assessment, and the assessment results are more objective and reasonable. (3) Applying this model to the airport oil supply automatic control system can comprehensively evaluate risk, solve the practical problems faced by the airport, and also provide an important basis for the cybersecurity protection scheme of the energy industry. Show more

Keywords: Cybersecurity risk assessment, fuzzy set theory, attack-defense tree

DOI: 10.3233/JIFS-201126

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10475-10488, 2021