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

Authors: Guo, Wei | Zhang, Chuchen

Article Type: Research Article

Abstract: The expansive growth of information on the Internet has led to new developments in computer vision technology and image processing techniques. Since stone inscriptions are subject to erosion and polishing by the external environment for years, it is difficult to extract image and text information. In this study, the fuzzy control theory is combined with edge detection technology for image edge detection. Firstly, a suitable fuzzy rule and affiliation function are set, then a fuzzy control system is used to extract and detect the image edge information, and then a fuzzy logic rule-based edge detection algorithm is proposed to detect …the inscription images. To test the performance of the algorithm, the detection effect of the image is first analyzed from a subjective perspective. The experimental results show that the proposed algorithm has better edge detection for both inscription and lena images, with better noise suppression without excessive distortion, and clearer inscription images. The proposed algorithm has the lowest MSE value of 41.26 when the detection object is the lena image b, and the highest PSNR value of 33.84 when the detection object is the lena image a. The proposed algorithm has the lowest MSE value of 41.26 when the detection object is the lena image b, and the highest PSNR value of 41.26 when the detection object is the lena image b. The proposed algorithm has the highest PSNR value of 33.84 when the detection object is the lena image b. In summary, the analysis of both subjective and objective indicators shows that the inscription image processing algorithm used in this paper has better processing effect, and the processed images become clearer with less distortion, which is helpful for both inscription image and text extraction. Show more

Keywords: Fuzzy logic, inscription picture, EA, picture processing technology

DOI: 10.3233/JIFS-230218

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 2, pp. 2465-2475, 2023

Authors: Yang, Long-Hao | Ye, Fei-Fei | Wang, Ying-Ming | Huang, Yan | Hu, Haibo

Article Type: Research Article

Abstract: Performance evaluation is one of the most important standards to measure the competitiveness and productivity of enterprises. Although existing studies could obtain the specific values of enterprises performance based on historical data, they usually failed to effectively evaluate enterprises performance in the consideration of different indicators. Meanwhile, as the characteristics of existing performance evaluation models are uneven, how to choose a reasonable data envelopment analysis (DEA) model for enterprises performance evaluation must be considered. Therefore, a new ensemble model on the basis of homogeneous, heterogeneous, and hybrid efficiency evaluation together with the evidential reasoning (ER) approach is proposed in this …study for enterprises performance evaluation, so called the ER-based ensemble model. The ER-based ensemble model can overcome the inconsistency results caused by the application of different indicators and different DEA models. In case study, 40 state-own holding enterprises in China are selected and all these enterprises are evaluated and ranked using the integrated efficiency obtained from the ER-based ensemble model. Comparative analysis demonstrates that the ER-based model is better than some traditional efficiency evaluation models in enterprises performance evaluation and performance ranking. Show more

Keywords: Data envelopment analysis, efficiency evaluation, efficiency ensemble, enterprise performance, evidential reasoning

DOI: 10.3233/JIFS-230247

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 2, pp. 2477-2495, 2023

Authors: Zhou, Jiaqi | Wu, Tingming | Yu, Xiaobing | Wang, Xuming

Article Type: Research Article

Abstract: Accurate and reliable prediction of PM2.5 concentrations is the basis for appropriate warning measures, and a single prediction model is often ineffective. In this paper, we propose a novel decomposition-and-ensemble model to predict the concentration of PM2.5 . The model utilizes Ensemble Empirical Mode Decomposition (EEMD) to decompose PM2.5 series, Support Vector Regression (SVR) to predict each Intrinsic Mode Function (IMF), and a hybrid algorithm based on Differential Evolution (DE) and Grey Wolf Optimizer (GWO) to optimize SVR parameters. The proposed prediction model EEMD-SVR-DEGWO is employed to forecast the concentration of PM2.5 in Guangzhou, Wuhan, and Chongqing of …China. Compared with six prediction models, the proposed EEMD-SVR-DEGWO is a reliable predictor and has achieved competitive results. Show more

Keywords: PM2.5, prediction, decomposition-and-ensemble, support vector regression

DOI: 10.3233/JIFS-230343

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 2, pp. 2497-2512, 2023

Authors: Yi, Weiguo | Ma, Bin | Zhang, Heng | Ma, Siwei

Article Type: Research Article

Abstract:  Compared with other traditional community discovery algorithms, density peak clustering algorithm is more efficient in getting network structures through clustering. However, DPC needs to contain the distance information between all nodes as sources, so it cannot directly processing the complex network represented by the adjacency matrix. DPC introduces truncation distance when calculating the local density of nodes, which is usually set as a fixed value according to experience, and lacks self-adaptability for different network structures. A feasible solution to those problems is to combined rough set theory and kernel fuzzy similarity measures. In this work, we present overlapping community detection …algorithm based on improved rough entropy fusion density peak. The algorithm applied rough set theory to attribute reduction of massive high-dimensional data. Another algorithm defines the similarity of sample points by the inner product between two vectors on the basis of fuzzy partition matrix. Finally, a community detection algorithm based on rough entropy and kernel fuzzy density peaks clustering (CDRKD) has proposed by combining the two algorithms above, we perform an extensive set of experiments to verify the effectiveness and feasibility of the algorithm. Show more

Keywords: Overlapping community detection, rough neighborhood mutual information entropy, density peaks clustering, kernel fuzzy similarity measure

DOI: 10.3233/JIFS-230614

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 2, pp. 2513-2527, 2023

Authors: Xu, Li | Bai, Jinniu

Article Type: Research Article

Abstract: Brain cancer is one of the most deadly forms of cancer today, and its timely and accurate diagnosis can significantly impact the patient’s quality of life. A computerized tomography scan (CT) and magnetic resonance imaging (MRI) of the brain is required to diagnose this condition. In the past, several methods have been proposed as a means of diagnosing brain tumors through the use of medical images. However, due to the similarity between tumor tissue and other brain tissues, these methods have not proven to be accurate. A novel method for diagnosing brain tumors using MRI and CT scan images is …presented in this paper. An architecture based on deep learning is used to extract the distinguishing characteristics of brain tissue from tumors. The use of fusion images allows for more accurate detection of tumor types. In comparison with other approaches, the proposed method has demonstrated superior results. Show more

Keywords: Deep learning, brain tumor, visual geometry group, CT scan, MRI images

DOI: 10.3233/JIFS-230850

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 2, pp. 2529-2536, 2023

Authors: Garg, Harish | Ünver, Mehmet | Aydoğan, Büşra | Olgun, Murat

Article Type: Research Article

Abstract: As an extension of the concepts of fuzzy set and intuitionistic fuzzy set, the concept of Pythagorean fuzzy set better models some real life problems. Distance, entropy, and similarity measures between Pythagorean fuzzy sets play important roles in decision making. In this paper, we give a new entropy measure for Pythagorean fuzzy sets via the Sugeno integral that uses fuzzy measures to model the interaction between criteria. Moreover, we provide a theoretical approach to construct a similarity measure based on entropies. Combining this theoretical approach with the proposed entropy, we define a distance measure that considers the interaction between criteria. …Finally, using the proposed distance measure, we provide an extended Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) for multi-criteria decision making and apply the proposed technique to a real life problem from the literature. Finally, a comparative analysis is conducted to compare the results of this paper with those of previous studies in the literature. Show more

Keywords: Pythagorean fuzzy set, entropy measure, distance measure, extended TOPSIS, medical diagnosis

DOI: 10.3233/JIFS-231454

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 2, pp. 2537-2549, 2023

Authors: Wang, Tengfei | Shi, Peng

Article Type: Research Article

Abstract: In this paper, the problems of expressing and fusing multi-channel uncertain digital information is studied. The concept of a special high-dimensional fuzzy number called multi-level linear fuzzy ellipsoid number is given, and a method of constructing such high dimensional fuzzy number to express multi-channel uncertain digital information is established. Then a calculation formula of the centroid of multistage linear fuzzy ellipsoid number is deduced. And then, as an application example of multi-channel uncertain digital information fusion, a specific example is given to show ranking some objects which are characterized by multi-channel uncertain digital information by using the obtained results and …the concept of fuzzy order on high dimensional fuzzy number space. Show more

Keywords: Fuzzy numbers, fuzzy ellipsoid numbers, multistage linear fuzzy ellipsoid number, constructing fuzzy numbers, expressing multi-channel uncertain digital information, multi-channel uncertain digital information fusion

DOI: 10.3233/JIFS-222761

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 2, pp. 2551-2563, 2023

Authors: Memon, Abdul Sami | Laghari, J.A. | Bhayo, Muhammad Akram | Khokhar, Suhail | Chandio, Sadullah | Memon, Muhammad Saleem

Article Type: Research Article

Abstract: In the modern power system, the use of renewable energy sources is increasing rapidly, which makes the system more sensitive. Therefore, it requires effective controllers to operate within the allowable ranges. The existing techniques based on cascaded controllers implemented so far for load frequency control have the advantage of improving the system response. However, this makes the system a more complex and time-consuming process. This makes the system more straightforward, makes it easy to optimize PID parameters, and provides results in acceptable ranges. This paper attempts to solve the load frequency control (LFC) problem in an interconnected hybrid power system …with a classical PID controller employing the tunicate swarm algorithm (TSA). This algorithm is used for two areas of an interconnected hybrid power system: thermal, hydro, nuclear, and wind. The PID controller parameters are optimized by tunicate swarm algorithm using integral time absolute error (ITAE) based objective function. To show the robustness of the proposed TSA algorithm, a sensitivity analysis is performed for four case studies ranging from 20% to 30% load increments and decrements. The performance of the proposed TSA algorithm has been compared with the well-known optimization algorithms, particle swarm optimization (PSO), artificial bee colony (ABC), and arithmetic optimization algorithm (AOA) in terms of overshoot, undershoot, and settling time. The simulation results show that the proposed TSA has better optimization capability than PSO, ABC, and AOA in terms of overshoot, undershoot, and settling time. Show more

Keywords: Tunicate Swarm based Automatic generation control, hybrid power system, TSA based Optimized PID controller, Interconnected power system, multi-area power system.

DOI: 10.3233/JIFS-223227

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 2, pp. 2565-2578, 2023

Authors: Leng, Hongyong | Shao, Jinxin | Zhang, Zhe | Qian, Yurong | Ma, Mengnan | Li, Zichen

Article Type: Research Article

Abstract: To address the problem that single-channel neural networks cannot fully extract text semantic features in traditional user portrait construction methods, this paper proposes a dual-channel user portrait model based on DPCNN-BIGRU and attention mechanism. The model first uses Bidirectional Encoder Representation from Transformers(Bert) and CK-means+ to obtain the fusion vector of semantic features and topic features, and then feeds the vector into Deep Pyramid Convolutional Neural Networks (DPCNN) and Bidirectional Gated Recurrent Unit (BiGRU). Deep features and global features of the text are obtained simultaneously, and then weights are assigned by the attention mechanism. Finally, the output features of the …dual channels are fused and classified. It is tested on the Sogou user portrait datasets, and the experimental results prove that the dual-channel model outperforms the baseline model. Show more

Keywords: User profile, BERT, canopy, K-means, text classification

DOI: 10.3233/JIFS-224532

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 2, pp. 2579-2591, 2023

Authors: Fathy, E. | Ammar, E. | Helmy, M.A.

Article Type: Research Article

Abstract: Due to the importance of the multi-level fully rough interval linear programming (MLFRILP) problem to address a wide range of management and optimization challenges in practical applications, such as policymaking, supply chain management, energy management, and so on, few researchers have specifically discussed this point. This paper presents an easy and systematic roadmap of studies of the currently available literature on rough multi-level programming problems and improvements related to group procedures in seven basic categories for future researchers and also introduces the concept of multi-level fully rough interval optimization. We start remodeling the problem into its sixteen crisp linear programming …LP problems using the interval method and slice sum method. All crisp LPs can be reduced to four crisp LPs. In addition, three different optimization techniques were used to solve the complex multi-level linear programming issues. A numerical example is also provided to further clarify each strategy. Finally, we have a comparison of the methods used for solving the MLFRILP problem. Show more

Keywords: Constraint method, interval arithmetic, interactive approach, fuzzy approach, rough interval programming, slice sum method

DOI: 10.3233/JIFS-230057

Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 2, pp. 2593-2610, 2023