Journal of Intelligent & Fuzzy Systems - Volume 46, issue 1

Authors: Li, Zhaowen | Wei, Shengxue | Liu, Suping

Article Type: Research Article

Abstract: Outlier detection is critically important in the field of data mining. Real-world data have the impreciseness and ambiguity which can be handled by means of rough set theory. Information entropy is an effective way to measure the uncertainty in an information system. Most outlier detection methods may be called unsupervised outlier detection because they are only dealt with unlabeled data. When sufficient labeled data are available, these methods are used in a decision information system, which means that the decision attribute is discarded. Thus, these methods maybe not right for outlier detection in a a decision information system. This paper …proposes supervised outlier detection using conditional information entropy and rough set theory. Firstly, conditional information entropy in a decision information system based on rough set theory is calculated, which provides a more comprehensive measure of uncertainty. Then, the relative entropy and relative cardinality are put forward. Next, the degree of outlierness and weight function are presented to find outlier factors. Finally, a conditional information entropy-based outlier detection algorithm is given. The performance of the given algorithm is evaluated and compared with the existing outlier detection algorithms such as LOF, KNN, Forest, SVM, IE, and ECOD. Twelve data sets have been taken from UCI to prove its efficiency and performance. For example, the AUC value of CIE algorithm in the Hayes data set is 0.949, and the AUC values of LOF, KNN, SVM, Forest, IE and ECOD algorithms in the Hayes data set are 0.647, 0.572, 0.680, 0.676, 0.928 and 0.667, respectively. The advantage of the proposed outlier detection method is that it fully utilizes the decision information. Show more

Keywords: Rough set theory, outlier detection, outlier factor, conditional information entropy

DOI: 10.3233/JIFS-236009

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 1899-1918, 2024

Authors: Kahraman, Cengiz

Article Type: Research Article

Abstract: The direct assignment of decimal numbers for membership and non-membership degrees of an element in intuitionistic fuzzy sets is not practical. The problem is that the expert cannot assign the same values to the degrees of membership, non-membership and hesitancy in decimal numbers for the same proposition in every attempt. Rather than the former, the assignment of proportional relationships between membership and non-membership degrees is more appropriate. We propose proportion-based models for intuitionistic fuzzy sets that include arithmetic and aggregation operators. Proportional intuitionistic fuzzy (PIF) sets require only the proportion relations between an intuitionistic fuzzy set’s parameters. These models will …make it easier to define intuitionistic fuzzy sets with more accurate data that better represents expert judgments. We transform AHP method, one of the traditional multi-criteria decision making methods, to PIF AHP using PIF sets. We compare the proposed PIF AHP method by interval-valued intuitionistic fuzzy AHP method existing in the literature. A wind turbine selection problem is handled to show the validity of the proposed PIF AHP method. Show more

Keywords: Proportional intuitionistic fuzzy sets, aggregation operators, multi-criteria decision making, AHP

DOI: 10.3233/JIFS-236035

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 1919-1933, 2024

Authors: Lai, Yibo | Fan, Libo | Sun, Zhiqing | Fang, Xiang | Shen, Bin | Tu, Yongwei

Article Type: Research Article

Abstract: Aiming at the problems of low convective heat transfer coefficient and high energy consumption in the air-cooled data center of immersed liquid cooling, an improved deep learning algorithm is proposed for the data center system of immersed liquid cooling equipment room. By improving the design of the immersed liquid cooling system, heat exchange is carried out between the immersed liquid cooling system and heating components such as the central processing unit of the server. The insulation coolant and cooling water achieve server heat dissipation through energy exchange, achieving data management of the immersed liquid cooling room. The proposed algorithm improves …data management efficiency while ensuring computational accuracy by conducting in-depth training and learning on the obtained immersed liquid cooling data, thus achieving the management of data in the immersed liquid cooling room. Through experiments, it has been proven that the immersed liquid cooling system in this study has high data management efficiency and low error, and can maintain server memory heat below 37 ° C, with a research accuracy of up to 92%. Show more

Keywords: Immersive liquid cooling, liquid cooling heat exchanger, deep learning, non relaxation hash algorithm, data management system

DOI: 10.3233/JIFS-233140

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 1935-1944, 2024

Authors: Wu, Jian-Zhang | Zhang, Xue | Beliakov, Gleb

Article Type: Research Article

Abstract: Both the nonadditivity index and nonmodularity index have emerged as valuable indicators for characterizing the interaction phenomenon within the realm of fuzzy measures. The axiomatic representation plays a crucial role in distinguishing and elucidating the relationship and distinctions between these two interaction indices. In this paper, we employ a set of fundamental and intuitive properties related to interactions, such as equality, additivity, maximality, and minimality, to establish a comprehensive axiom system that facilitates a clear comprehension of the interaction indices. To clarify the impact of new elements’ participation on the type and density of interactions within an initial coalition, we …investigate and confirm the existence of proportional and linear effects in relation to null and dummy partnerships, specifically concerning the nonadditivity and nonmodularity indices. Furthermore, we propose the concept of the t -interaction index to depict a finer granularity for the interaction situations within a coalition, which involves subsets at different levels and takes the nonadditivity index and nonmodularity index as special cases. Finally, we establish and discuss the axiomatic theorems and empirical examples of this refined interaction index. In summary, the contributions of this work shed light on the axiomatic characteristics of the t -interaction indices, making it a useful reference for comprehending and selecting appropriate indices within this category of interactions. Show more

Keywords: Fuzzy measure, capacity, nonadditivity index, nonmodularity index, t-interaction index

DOI: 10.3233/JIFS-233196

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 1945-1956, 2024

Authors: Gobinath, C. | Gopinath, M.P.

Article Type: Research Article

Abstract: PURPOSE: Many researchers have found that the improvement in computerised medical imaging has pushed them to their limits in terms of developing automated algorithms for the identification of illness without the need for human participation. The diagnosis of glaucoma, among other eye illnesses, has continued to be one of the most difficult tasks in the area of medicine. Because there are not enough skilled specialists and there are a lot of patients seeking treatment from ophthalmologists, we have been encouraged to build efficient computer-based diagnostic methods that can assist medical professionals in early diagnosis and help reduce the amount of …time and effort they spend working on healthy situations. The Optic Disc position is determined with the help of the LoG operator, and a Disc Image map is projected with the help of a U-net architecture by utilising the location and intensity profile of the optic disc. After this, a Generative adversarial network is suggested as a possible solution for segmenting the disc border. In order to verify the performance of the model, a well-defined investigation is carried out on many retinal datasets. The usage of a multi-encoder U-net framework for optic cup segmentation is the second key addition made by this proposed work. This framework greatly outperforms the state-of-the-art in this area. The suggested algorithms have been tested on public standard datasets such as Drishti-GS, Origa, and Refugee, as well as a private community camp-based difficult dataset obtained from the All-India Institute of Medical Sciences (AIIMS), Delhi. All of these datasets have been verified. In conclusion, we have shown some positive outcomes for the detection of diseases. The unique strategy for glaucoma treatment is called ensemble learning, and it combines clinically meaningful characteristics with a deep Convolutional Neural Network. Show more

Keywords: Glaucoma, Cup-To-Disc Ratio (CDR), neuro-retinal rim (NRR) Loss, peripapillary atrophy (PPA), retinal nerve fiber layer (RNFL), deep convolutional neural network

DOI: 10.3233/JIFS-234363

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 1957-1971, 2024

Authors: Li, Junwei | Liu, Huanyu | Jin, Yong | Zhao, Aoxiang

Article Type: Research Article

Abstract: Research on conflict evidence fusion is an important topic of evidence theory. When fusing conflicting evidence, Dempster-Shafer evidence theory sometimes produces counter-intuitive results. Thus, this work proposes a conflict evidence fusion method based on improved conflict coefficient and belief entropy. Firstly, the proposed method uses an improved conflict coefficient to measure the degree of conflict, and the conflict matrix is constructed to get the support degree of evidence. Secondly, in order to measure the uncertainty of evidence, an improved belief entropy is proposed, and the information volume of evidence is obtained by the improve entropy. Next, connecting with the support …degree and information volume, We get the weight coefficient, and use it to modify the evidence. Finally, using the combination rule of Dempster for fusion. Simulation experiments have demonstrated the effectiveness and superiority of the proposed method in this paper. Show more

Keywords: Evidence theory, conflict evidence, conflict coefficient, beleief entropy, combination rule

DOI: 10.3233/JIFS-221507

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 1973-1984, 2024

Authors: Yapali, Reha | Korkmaz, Erdal | Çinar, Muhammed | Çoskun, Hüsamettin

Article Type: Research Article

Abstract: The idea of lacunary statistical convergence sequences, which is a development of statistical convergence, is examined and expanded in this study on L - fuzzy normed spaces, which is a generalization of fuzzy spaces. On L - fuzzy normed spaces, the definitions of lacunary statistical Cauchy and completeness, as well as associated theorems, are provided. The link between lacunary statistical Cauchyness and lacunary statistical boundedness with regard to L - fuzzy norm is also shown.

Keywords: ℒ-fuzzy normed space, lacunary double sequences, lacunary statistically convergence, lacunary statistical Cauchy, lacunary statistical boundedness

DOI: 10.3233/JIFS-222695

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 1985-1993, 2024

Authors: Prabaharan, P.

Article Type: Research Article

Abstract: Recent developments in wireless sensor networks (WSNs) have generated interest in the area of sensor tracking events. The proposed work aims to decrease energy usage by identifying functional relay nodes utilizing the enhanced energy proficient clustering (EEPC) method. To minimize long-distance interaction between CH and BS, a power-efficient relay chosen technique is proposed using improved Grasshopper Optimization algorithm (IGOA). The network is constructed using both mobile and fixed nodes. Mobile nodes first choose cluster head (CH) among fixed nodes after broadcasting information. Depending on the related positioning and power density, mobile nodes choose their CH. CH receives information from mobile …sensor nodes (SNs). Based on the nodes’ velocity and position, the EEPC method computes particle fitness value and chooses the relay nodes. Performance metrics include Throughput, End-to-End Delay, Packet Delivery Ratio (PDR), Quantity of Received Packets, Total Residual Energy, and Total Energy Consumption, network lifetime. The suggested technique enhances network lifetime and reduces energy consumption when compared to other existing protocols. After 200 simulation rounds, the suggested EEPC displays 98.87% PDR. However, during 200 simulation cycles, ANFISRS, ORNS and DTC-ORS show 97.82%, 96.03%, and 89.585% PDR, respectively. Show more

DOI: 10.3233/JIFS-231729

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 1995-2008, 2024

Authors: Sandhu, Muhammad Abdullah | Amin, Asjad | Tariq, Sana | Mehmood, Shafaq

Article Type: Research Article

Abstract: Dengue mosquitoes are the only reason for dengue fever. To effectively combat this disease, it is important to eliminate dengue mosquitoes and their larvae. However, there are currently very few computer-aided models available in scientific literature to prevent the spread of dengue fever. Detecting the larvae stage of the dengue mosquito is particularly important in controlling its population. To address this issue, we propose an automated method that utilizes deep learning for semantic segmentation to detect and track dengue larvae. Our approach incorporates a contrast enhancement approach into the semantic neural network to make the detection more accurate. As there …was no dengue larvae dataset available, we develop our own dataset having 50 short videos with different backgrounds and textures. The results show that the proposed model achieves up to 79% F-measure score. In comparison, the DeepLabV3, Resnet achieves up to 77%, and Segnet achieves up to 76% F-measure score on the tested frames. The results show that the proposed model performs well for small object detection and segmentation. The average F-measure score of all the frames also indicates that the proposed model achieves a 76.72% F-measure score while DeepLabV3 achieves a 75.37%, Resnet 75.41%, and Segnet 74.87% F-measure score. Show more

Keywords: Dengue larvae, detection, tracking, semantic segmentation, image enhancement

DOI: 10.3233/JIFS-233292

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 2009-2021, 2024

Authors: Keikha, Abazar | Sabeghi, Narjes

Article Type: Research Article

Abstract: As the rapidly progressing applications of uncertainty theories, the need for modifications to some of their existing mathematical tools or creating new tools to deal correctly with them in various environments is also exposed. Hesitant fuzzy numbers (HFNs), as a particular case of fuzzy numbers, are not an exception to this rule. Considering the necessity of determining the distance between given HFNs in many of their practical applications, this article shows that the existing methods either do not provide correct results or are not able to meet the needs of users. This paper aims to present new methods for distance …measures of hesitant fuzzy numbers. To do them, three prevalent distance measures, i.e., the generalized distance measure, the Hamming distance measure, and the Euclidean distance measure, will be optimized into three distinct trinal categories. With the approach of reducing error propagation via reducing some unnecessary mathematical computations, new distance measures on HFNs will be introduced, first. The middle is the modification of the first category, which is more suitable when the given HFNs are equal-distance by the previous formula. Also, as the third category, the weighted form of these distance measures has been proposed, to be used where the real and membership parts of HFNs are not of equal importance. As an application of these, a TOPSIS-based technique for solving multi-attribute group decision-making problems with HFNs has been proposed. A numerical example will be implemented to describe the presented method. Finally, along with the validation of the proposed method, its numerical comparison with some other existing methods will be discussed in detail. Show more

Keywords: Hesitant fuzzy numbers, MAGDM, Hamming distance, Euclidean distance, TOPSIS

DOI: 10.3233/JIFS-234619

Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 2023-2035, 2024