Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Purchase individual online access for 1 year to this journal.
Price: EUR 315.00Impact Factor 2024: 1.7
The purpose of the Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology is to foster advancements of knowledge and help disseminate results concerning recent applications and case studies in the areas of fuzzy logic, intelligent systems, and web-based applications among working professionals and professionals in education and research, covering a broad cross-section of technical disciplines.
The journal will publish original articles on current and potential applications, case studies, and education in intelligent systems, fuzzy systems, and web-based systems for engineering and other technical fields in science and technology. The journal focuses on the disciplines of computer science, electrical engineering, manufacturing engineering, industrial engineering, chemical engineering, mechanical engineering, civil engineering, engineering management, bioengineering, and biomedical engineering. The scope of the journal also includes developing technologies in mathematics, operations research, technology management, the hard and soft sciences, and technical, social and environmental issues.
Authors: Cai, Jianxian | Dai, Xun | Gao, Zhitao | Shi, Yan
Article Type: Research Article
Abstract: Seismic data obtained from seismic stations are the major source of the information used to forecast earthquakes. With the growth in the number of seismic stations, the size of the dataset has also increased. Traditionally, STA/LTA and AIC method have been applied to process seismic data. However, the enormous size of the dataset reduces accuracy and increases the rate of missed detection of the P and S wave phase when using these traditional methods. To tackle these issues, we introduce the novel U-net-Bidirectional Long-Term Memory Deep Network (UBDN) which can automatically and accurately identify the P and S wave phases …from seismic data. The U-net based UBDN strongly maintains the U-net’s high accuracy in edge detection for extracting seismic phase features. Meanwhile, it also reduces the missed detection rate by applying the Bidirectional Long Short-Term Memory (Bi-LSTM) mode that processes timing signals to establish the relationship between seismic phase features. Experimental results using the Stanford University seismic dataset and data from the 2008 Wenchuan earthquake aftershock confirm that the proposed UBDN method is very accurate and has a lower rate of missed phase detection, outperforming solutions that adapt traditional methods by an order of magnitude in terms of error percentage. Show more
Keywords: U-net, bidirectional long short term memory, phase identification, wenchuan aftershocks
DOI: 10.3233/JIFS-211792
Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5227-5236, 2022
Authors: Xiao, Liming | Huang, Guangquan | Zhang, Genbao
Article Type: Research Article
Abstract: Failure mode and effects analysis (FMEA) is an effective tool utilized in various fields for discovering and eliminating potential failures in products and services, which is usually implemented based on experts’ linguistic assessments. However, incomprehensive weigh information of risk factors and experts, lacking the consideration of experts’ randomness and hesitation, and incomplete risk factor system is essential challenges for the traditional FMEA model. Therefore, to properly handle these challenges and further enhance the performance of the traditional FMEA, this study develops a new FMEA strategy for assessing and ranking failures’ risks. First, a novel concept of intuitionistic fuzzy clouds (IFCs) …is developed by combining the merits of the intuitionistic fuzzy set theory and the cloud model theory in manipulating uncertain information. Some basic operations and the Minkowski-type distance measure of IFCs are also presented and discussed. Further, in the proposed FMEA model, two combination weighting methods are developed to determine the synthetic weights of experts and risk factors, respectively, which consider subjectivity and objectivity simultaneously. In addition, maintenance (M) is considered as a new risk factor to enrich the assessment factor system and facilitate a more reasonable risk assessment result. Finally, a case study is implemented along with comparisons to demonstrate the feasibility and superiority of the presented FMEA model. Show more
Keywords: Failure mode and effects analysis (FMEA), intuitionistic fuzzy set theory, cloud model, risk analysis, technique for order performance by similarity to ideal solution (TOPSIS)
DOI: 10.3233/JIFS-211793
Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5237-5263, 2022
Authors: Ding, Xiong | Gao, Jinding
Article Type: Research Article
Abstract: In addition to the tragic loss of life, precious natural and personal property, forest fires pose a huge threat to ecologically healthy forests and environmental protection. A forest-fire-identification is explored in this article. Because the color space model FCS brings a high false alarm rate in flame recognition, this paper proposes an improved flame recognition color space (IFCS) based on chaos theory and k-medoids particle swarm optimization algorithm. The use of IFCS color space for flame recognition can ensure simple and fast calculations and more prominent flame/non-flame pixel color attribute difference characteristics when it is compared to FCS. The IFCS …flame recognition color space is obtained by using methods such as initializing the particles in the chaotic sequence, adaptively adjusting the inertia weight, dynamic nonlinear adjustment of the learning factor, and jumping out of the local optimum from the chaotic search. In the IFCS flame color space, the binary image is obtained by the classic Otsu threshold method, and the Flame Recognition algorithm (IOFR) algorithm is established based on IFCS and Otsu. The experimental results show that based on the FCS flame recognition algorithm, the IOFR algorithm effectively reduces the flame misjudgment rate. Show more
Keywords: Forest fire prevention, flame recognition, fire color space, chaos, k-medoids, particle swarm optimization (PSO)
DOI: 10.3233/JIFS-211816
Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5265-5281, 2022
Authors: Zhang, Qiang
Article Type: Research Article
Abstract: Unmanned vehicles need to gather the surrounding information comprehensively. Perception of automotive information is one of the important information. In the field of automotive perception, the stereo vision plays a vital role and stere-vision can calculate the length, width, and height, making the object more specific. However, under the existing technology, it is impossible to obtain accurate detection in a complex environment by relying on a single sensor. Therefore, it is particularly important to study the calibration technology based on multi-sensor fusion. This paper proposes a method based on feature point pair matching. Two rectangular planks are used to …extract the 3D point cloud of the edge of the board in stereo vision and LiDAR coordinate systems, which is then used to obtain the corner coordinates. Finally, the Kabsch algorithm is used to solve the coordinate transformation between the paired feature points, and a clustering method is used to remove outliers from the multiple measurements and obtain the average value. By setting up an experiment, this method can be implemented on the Nvidia Jetson Tx2 embedded development board, and accurate registration parameters can be obtained, thus verifying the theoretical method’s feasibility. It finishes calibration of the LiDAR and binocular camera based on present methods. The result shows that, it can reduce the effects of noise, and acquire registration parameters accurately of LiDAR and cameras. Compared with the approved method of the same type, our proposed method has less errors and good practical value. Show more
Keywords: Target, calibration, 3D LiDAR, binocular camera, unmanned vehicles
DOI: 10.3233/JIFS-211827
Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5283-5290, 2022
Authors: Mahmood, Tahir | Izatmand, | Ali, Zeeshan | Panityakul, Thammarat
Article Type: Research Article
Abstract: In the real decision process, an important problem is how to express the attribute value more efficiently and accurately. In the real world, because of the complexity of decision-making problems and the fuzziness of decision-making environments, it is not enough to express attribute values of alternatives by exact values. For this managing with such sorts of issues, the principle of Linear Diophantine uncertain linguistic set is a valuable and capable technique to manage awkward and inconsistent information in everyday life problems. In this manuscript, we propose the original idea of Linear Diophantine uncertain linguistic set and elaborated their essential laws. …Additionally, to determine the association among any numbers of attributes, we elaborated the Linear Diophantine uncertain linguistic arithmetic Heronian mean operator, Linear Diophantine uncertain linguistic weighted arithmetic Heronian mean operator, Linear Diophantine uncertain linguistic geometric Heronian mean operator, Linear Diophantine uncertain linguistic weighted geometric Heronian mean operator, and their properties are also discovered. By using these operators, we utilize the multi-attribute decision-making procedure by using elaborated operators. To determine the consistency and validity of the elaborated operators, we illustrate some examples by using explored operators. Finally, the superiority and comparative analysis of the elaborated operators with some existing operators are also determined and justified with the help of a graphical point of view. Show more
Keywords: Linear Diophantine uncertain linguisticsets, arithmetic/geometric Heronian mean operators, decision-making methods
DOI: 10.3233/JIFS-211839
Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5291-5319, 2022
Authors: Zhang, Yan | Li, Shiyu | Deng, Yang | Chen, Honggen | Yan, Xin | Li, Jing
Article Type: Research Article
Abstract: This paper develops a joint decision-making model approach to preventive maintenance and SPC (statistical process control) with delayed monitoring considered. The proposal of delayed monitoring policy postpones the sampling process till a scheduled time and contributes to six renewal scenarios of the production process, where maintenance actions are triggered by scheduled duration of preventive maintenance or the alert of X ¯ chart for monitoring the shift of process mean resulted by deterioration of equipment. By analyzing the evolution of the system in different scenarios, a mathematical model is given to minimize the expected cost …per unit time by optimizing values of five variables (scheduled duration without monitoring, scheduled duration of preventive maintenance, sample size, sampling interval and control limit). The results of a numerical example indicate that the hourly cost of the proposed model is lower than the model that delayed monitoring is not considered when the system has a low hazard rate during the early period. Finally, a sensitivity analysis is performed to demonstrate the effect of model parameters. Show more
Keywords: Repairable system, delayed monitoring, preventive maintenance, statistical process control, joint economic design
DOI: 10.3233/JIFS-211853
Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5321-5334, 2022
Authors: Rajeswari, G. | Ithaya Rani, P.
Article Type: Research Article
Abstract: Facial occlusions like sunglasses, masks, caps etc. have severe consequences when reconstructing the partially occluded regions of a facial image. This paper proposes a novel hybrid machine learning approach for occlusion removal based on Structural Similarity Index Measure (SSIM) and Principal Component Analysis (PCA), called SSIM_PCA. The proposed system comprises two stages. In the first stage, a Face Similar Matrix (FSM) guided by the Structural Similarity Index Measure is generated to provide the necessary information to recover from the lost regions of the face image. The FSM generates Related Face (RF) images similar to the probe image. In the second …stage, these RF images are considered as related information and used as input data to generate eigenspaces using PCA to reconstruct the occluded face region exploiting the relationship between the occluded region and related face images, which contain relevant data to recover from the occluded area. Experimental results with five standard datasets viz. Caspeal-R1, IMFDB, and FEI have proven that the proposed method works well under illumination changes and occlusion of facial images. Show more
Keywords: Face recognition, SSIM, eigenspaces, PCA, FSM, related face
DOI: 10.3233/JIFS-211890
Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5335-5350, 2022
Authors: Mishra, Rohit | Malviya, Shrikant | Ghosh, Rudra Chandra | Tiwary, Uma Shanker
Article Type: Research Article
Abstract: Impreciseness and uncertainty are the fabrics that make life interesting. For decades, human beings have developed strategies to cope with uncertainties and automate them. In personnel selection for the I.T. field, selectors often find it very difficult to select candidates by going through a set of resumes containing similar kinds of skills. Hence the selection task becomes a fuzzy decision making with the uncertainty involved. A combination of fuzzy clustering and Interval Type-2 fuzzy sets (IT2FS) is proposed in such scenarios. An experiment is conducted over a resume dataset containing fifteen hundred resumes for a particular job description. Firstly, Fuzzy …C-means clustering (FCM) is applied for selective clustering, while decision-making under uncertainty is carried through IT2FS. The candidates in the selected cluster are given a score for ranking as per the skillset criteria. The final decision for shortlisting the resumes is carried through IT2FS. The model shows an average accuracy of 88.2% with an F1-score of 0.76 compared to (K-means + IT2FS) model with an F1-score of 0.72. Thus, the proposed model performs better while decision-making under uncertainty. Show more
Keywords: Personnel selection, fuzzy clustering, interval Type-2 fuzzy sets, decision making, resume shortlisting
DOI: 10.3233/JIFS-211892
Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5351-5359, 2022
Authors: Işık, Gürkan | Kaya, İhsan
Article Type: Research Article
Abstract: Defectiveness of items is generally considered as a certain value in acceptance sampling plans (ASPs). It is clear that, it may not be certainly known in some real-case problems. Uncertainties of the inspection process such as measurement errors, inspectors’ hesitancies or vagueness of the process etc. should be taken into account to obtain more reliable results. The fuzzy set theory (FST) is one of the best methods to overcome these problems. There are some studies in the literature formulating the ASPs with the help of FST. Deciding the right membership functions of the fuzzy sets (FSs) has a vital importance …on the quality of the uncertainty modeling. Additionally, the fuzzy set extensions have been offered to model more complicated uncertainties to achieve better modeling. As one of these extensions, type-2 fuzzy sets (T2FSs) gives an ability to model uncertainty in situations where it is not possible to determine exact membership function parameters. In this study, single and double ASPs based on interval T2FSs (IT2FSs) have been designed for binomial and Poisson distributions. Thus, it becomes possible to make more flexible, sensitive and descriptive sensitivity analyzes. The main characteristic functions of ASPs have been derived and the suggested formulations have been illustrated on a comparative application from manufacturing process. Results allowing for more comprehensive analysis as against to the traditional and T1FSs based plans have been obtained. Show more
Keywords: Acceptance sampling plans, binomial distribution, fuzzy sets, interval type-2 fuzzy sets, poisson distribution
DOI: 10.3233/JIFS-211915
Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5361-5373, 2022
Authors: Zhang, Lei | Pan, Jiaxing | Xia, Pengfei | Wei, Chuyuan | Jing, Changfeng | Guo, Maozu | Guo, Quansheng
Article Type: Research Article
Abstract: With the increasing number of motor vehicles, exhaust emission has become a major source of urban pollution. Most studies are limited to the prediction of pollutant concentration, which cannot clearly indicate the change of pollution emissions and regional relationship. In this paper, we propose an emission propagation model of vehicle source pollution based on complex network in order to intelligently mine the interaction and propagation rules hidden behind dynamic spatiotemporal data. First, aiming at the problems of low resolution and insufficient data volume of vehicle emission data, a high-resolution pollution emission data is generated based on the COPERT (Computer Program …to Calculate Emissions from Road Transport). For study the influence of causality between regions, a propagation model is designed based on the convergent cross mapping method to transform the emission time series into a complex network. In addition, we propose a novel key node mining algorithm using hybrid local and global information to identify areas of heavy pollution. Experimental results on real datasets demonstrate that the spread of pollution follows certain rules and is also affected by regional influences. Moreover, the proposed algorithm is superior to the state-of-the-art methods. Show more
Keywords: Vehicle source pollution, complex network, propagation characteristic, convergent cross mapping, key node mining
DOI: 10.3233/JIFS-211921
Citation: Journal of Intelligent & Fuzzy Systems, vol. 42, no. 6, pp. 5375-5384, 2022
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
sales@iospress.com
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
info@iospress.nl
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office info@iospress.nl
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
china@iospress.cn
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
如果您在出版方面需要帮助或有任何建, 件至: editorial@iospress.nl