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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: Phu, Nguyen Dinh | Hung, Nguyen Nhut | Ahmadian, Ali | Salahshour, Soheil | Senu, Norazak
Article Type: Research Article
Abstract: This study presents a possible relationship between two main objects, which are three-dimensional copulas (3D-Cs) and geometric picture fuzzy numbers (GPFNs). This opens up a potential field for future studies for these two objects that three-dimensional copulas can become useful tools for handling uncertainty information in the form of a picture fuzzy set (PFS). Specifically, we define a GPFN as a base element of the PFS and a defined domain of three-dimensional copulas that contains a set of GPFNs, then we show some examples of three-dimensional copulas identified on this domain. In this framework, we present the theorems related to …these two objects. At the same time, we provide some examples for three-dimensional semi-copulas, three-dimensional quasi-copulas, and three-dimensional empirical copulas defined on D , which is a defined domain of a three-dimensional copula and contains a set of GPFNs D g * . In addition, we also introduce a new approach to non-linear programming problems. Show more
Keywords: Three-dimensional distribution functions, three-dimensional copulas (3D-Cs), geometric picture fuzzy numbers (GPFNs), additional set of geometric picture fuzzy numbers (Ad-GPFNs), non-linear programming approach
DOI: 10.3233/JIFS-182519
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 1, pp. 1-12, 2021
Authors: Wu, Xiu-Yun
Article Type: Research Article
Abstract: In this paper, notions of L -interval spaces and L -2-arity convex spaces are introduced. It is showed that there is a Galois’s connection between the category of L -convex spaces and the category of L -interval spaces. In particular, the category of L -2-arity convex spaces can be embedded in the category of L -interval spaces as a coreflective subcategory. Further, some properties of L -interval spaces are introduced including L -geometric (resp. L -Peano, L -Pasch and L -sand-glass) property. It is proved that an L -2-arity convex space is an L -JHC convex space iff its segment …operator has L -Peano property. It is also proved that an L -JHC convex space with an L -idempotent segment operator has L -sand-glass property. Further, it is also proved that an L -idempotent interval space having L -Peano+L -Pasch property has L -geometric property and L -sand-glass property. Show more
Keywords: L-convex space, L-2-arity convex space, L-interval space, L-geometric (Peano, Pasch, sand-glass) interval space
DOI: 10.3233/JIFS-182525
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 1, pp. 13-25, 2021
Authors: Wang, Jingjing | Xu, Minli | Jian, Huiyun
Article Type: Research Article
Abstract: This paper considers a two-stage supply chain consisting of one manufacturer and one retailer, exploring the impact of the fuzzy uncertainty of product yield and demand and the deciders’ risk attitudes on the optimal order quantity of the retailer. At the same time, this study tries to analyze the coordination problem in the two-stage supply chain with consideration of the retailer and the manufacturer’s risk attitudes. Firstly, this study develops a supply chain optimal decision model in a centralized decision framework. In the proposed model, the L-R fuzzy numbers are used to depict the yield and demand with fuzzy characteristics. …Then, the coordination of quantity discount in a supply chain is studied. Consequently, this research further investigates a special case in which the market demand and yield are assumed to be triangular fuzzy numbers, and the optimal solution of the order quantity and the wholesale price are obtained. At last, this paper utilizes several numerical examples to validate the proposed model. The results show that the quantity discount contract can coordinate the supply chain in a fuzzy environment, and the optimal order quantity decreases with the increasing of the risk bias coefficient of the retailer and the manufacturer. It also suggests that risk-seeking retailer will order more products, in addition, the manufacturer tend to choose a risk-seeking retailer as partner and the retailer is more likely to choose a risk-seeking rather than risk-aversion manufacturer as partner. Show more
Keywords: Fuzzy yield, fuzzy demand, weighted average value, L-R fuzzy number, risk preference
DOI: 10.3233/JIFS-182693
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 1, pp. 27-41, 2021
Authors: Fadel, Ibrahim A. | Alsanabani, Hussein | Öz, Cemil | Kamal, Tariq | İskefiyeli, Murat | Abdien, Fawzia
Article Type: Research Article
Abstract: Genetic algorithm is one of data mining classification techniques and it has been applied successfully in a wide range of applications. However, the performance of Genetic algorithm fluctuates significantly. This research work combines Genetic algorithm with fuzzy logic to adapt dynamically crossover and mutation parameters of Genetic algorithm. Two different datasets are taken during the experiment. Several experiments have been performed to prove the effectiveness of the proposed algorithm. Results show that the rules generated from a proposed algorithm are significantly better with high fitness and more efficient as compared to a normal Genetic algorithm.
Keywords: Data mining, hybrid fuzzy genetic algorithm, prediction rules, growth rate
DOI: 10.3233/JIFS-182729
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 1, pp. 43-52, 2021
Authors: Sun, Xin | Li, Dong | Wang, Wei | Yao, Hongxun | Xu, Dongliang | Du, Zhanwei | Sun, Mingui
Article Type: Research Article
Abstract: We present a novel graph cut method for iterated segmentation of objects with specific shape bias (SBGC). In contrast with conventional graph cut models which emphasize the regional appearance only, the proposed SBGC takes the shape preference of the interested object into account to drive the segmentation. Therefore, the SBGC can ensure a more accurate convergence to the interested object even in complicated conditions where the appearance cues are inadequate for object/background discrimination. In particular, we firstly evaluate the segmentation by simultaneously considering its global shape and local edge consistencies with the object shape priors. Then these two cues are …formulated into a graph cut framework to seek the optimal segmentation that maximizing both of the global and local measurements. By iteratively implementing the optimization, the proposed SBGC can achieve joint estimation of the optimal segmentation and the most likely object shape encoded by the shape priors, and eventually converge to the candidate result with maximum consistency between these two estimations. Finally, we take the ellipse shape objects with various segmentation challenges as examples for evaluation. Competitive results compared with state-of-the-art methods validate the effectiveness of the technique. Show more
Keywords: graph cut, shape, elliptical pattern
DOI: 10.3233/JIFS-182759
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 1, pp. 53-63, 2021
Authors: Zhou, Peng | Tian, Junxing | Sun, Jian | Yao, Jinmei | Zou, Defang | Yu, Wenda
Article Type: Research Article
Abstract: According to the characteristics of the tool hydraulic control system of the double cutters experimental pplatform, intelligent control methodology forecasted by fuzzy neural network is introduced into the control system. The two level control systems of fuzzy neural network predictive control and fuzzy control are designed. The fuzzy neural network predictive controller mainly completes the analysis and control of the speed and pressure in the tool hydraulic system. The speed control signal and pressure control signal from the first level are output to the fuzzy controller. Then, through logical reasoning, the control signal is output and the actuator is driven …by the fuzzy controller to complete the control function of the tool system. In this paper, compared with the traditional PID control, the fuzzy neural network predictive control technology has better control accuracy, dynamic response performance and steady-state accuracy. The fuzzy neural network predictive control technology can be used to control the tool hydraulic system of Tunnel Boring Machine. Show more
Keywords: Neural network, fuzzy neural network, predictive control, fuzzy control, tool hydraulic control system
DOI: 10.3233/JIFS-182804
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 1, pp. 65-76, 2021
Authors: Shalini Lakshmi, A.J. | Vijayalakshmi, M.
Article Type: Research Article
Abstract: The resourceful mobile devices with augmented capabilities around human pave the way for utilizing it as delegators for resource-constrained devices to run compute-intensive applications. Such collaborative resource sharing policy among mobile devices throws challenges like identifying competent alternatives for offloading and diminishing time consumption of pre-offload process to accomplish remarkable offloading. This paper presents a Mobile Cloud Computing framework with Predictive Context-Aware Collaborative Offloading Process (PCA-COP) that fixes these challenges through conductive alternative discovery. This context-aware discovery adapts a multi-criteria decision making model of Analytic Hierarchy Process (AHP) accompanied with Fuzzy categorization to rank the alternatives and classify them into …Highly, Fairly, Less offload-suitable devices. Moreover, to make alternative selection optimal, a Dataset Curtailment enabled Artificial Neural Network (DCANN) prediction is incorporated on AHP-Fuzzy model, which truncates training dataset using Conditioned Stratified Sampling (CSS). The prototype framework is evaluated with mobile applications in the classroom under dynamic context environments. Show more
Keywords: Predictive context-aware collaborative offloading process (PCA-COP), dataset curtailment enabled artificial neural network prediction (DCANN), conditioned stratified sampling (CSS), collaborative offloading, context-aware offloading
DOI: 10.3233/JIFS-182906
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 1, pp. 77-88, 2021
Authors: Rashmanlou, Hossein | Muhiuddin, G. | Amanathulla, SK | Mofidnakhaei, F. | Pal, Madhumangal
Article Type: Research Article
Abstract: Theoretical concepts of graphs are highly utilized by computer science applications. Especially in research areas of computer science such as data mining, image segmentation, clustering, image capturing and networking. The cubic graphs are more flexible and compatible than fuzzy graphs due to the fact that they have many applications in networks. In this paper, we define the direct product, strong product, and degree of a vertex in cubic graphs and investigate some of their properties. Likewise, we introduce the notion of complete cubic graphs and present some properties of self complementary cubic graphs. Finally, We present fuzzy cubic organizational model …as an example of cubic digraph in decision support system. Show more
Keywords: Cubic set, cubic graphs, self complementary, strong cubic graphs
DOI: 10.3233/JIFS-182929
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 1, pp. 89-101, 2021
Authors: Wang, Xu | Wang, Ying-Ming
Article Type: Research Article
Abstract: China has attracted the attention of the world owing its significant economic achievements, which are supported significantly by its booming industry. However, the issues of energy and pollutants have severely challenged the sustainability of the industry. The efficiency measurement is the premise intended to realize sustainability within the Chinese industry. Because the industry is a complex production system, there exists uncertainties and fuzziness regarding its inputs and outputs. This study proposes the application of an interval to describe these fuzzy data and employ the Enhanced Russell Measure to assess the performance of the Chinese industry, accounting for undesirable output such …as pollution. In addition, for the ranking between interval efficiencies, a novel ranking approach based on the holistic acceptability of a possibility degree is proposed. The proposed method provides advice and guidance for decision makers to make appropriate and effective policies to balance industrial development and environmental protection in spite of uncertain and fuzzy data. Show more
Keywords: Data envelopment analysis, Enhanced Russell Measure, Interval data, Ranking, Industrial efficiency
DOI: 10.3233/JIFS-182943
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 1, pp. 103-115, 2021
Authors: Baranes, Amos | Palas, Rimona | Shnaider, Eli | Yosef, Arthur
Article Type: Research Article
Abstract: This study introduces computerized model for evaluation of corporate performance for companies traded in the main world stock markets. The main contribution of this study is to utilize a “Soft Regression” modeling tool, which is a soft computing tool based on fuzzy logic in financial statement analysis. Specifically, the tool is used to identify the most important financial ratios explaining the performance (as reflected by Operating Income Margin) of publicly traded companies, belonging to the manufacturing industries 2000–3999. We used data extracted from the XBRL database for years 2012 to 2016. The main results and conclusions of the study …are:1. The study identified relevant financial ratios for the manufacturing industry. It also revealed the relative importance of the various categories of financial ratios. 2. Detailed comparison of the results for 2012 and for 2016 indicated high degree of consistency and stability over time. 3. Not all financial ratios are equally relevant for all industries. 4. Proxy variables belonging to the same category of financial ratios are interchangeable in our model. It does not matter, which of the ratios belonging to the same category are used, the results are very similar for both, 2012 and for 2016. 5. All the resulting indicators imply that the model is highly reliable and robust. The study identified relevant financial ratios for the manufacturing industry. It also revealed the relative importance of the various categories of financial ratios. Detailed comparison of the results for 2012 and for 2016 indicated high degree of consistency and stability over time. Not all financial ratios are equally relevant for all industries. Proxy variables belonging to the same category of financial ratios are interchangeable in our model. It does not matter, which of the ratios belonging to the same category are used, the results are very similar for both, 2012 and for 2016. All the resulting indicators imply that the model is highly reliable and robust. The main contribution of this study is to present a soft computing modeling tool based on fuzzy logic which is intuitive, stable and not based on restrictive assumptions. Show more
Keywords: Modeling corporate earnings, financial ratios, XBRL, soft regression, corporate evaluation
DOI: 10.3233/JIFS-190109
Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 1, pp. 117-129, 2021
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