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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: Layegh Rafat, Mahmood | Shabakhty, Naser | Bahrpeyma, Abdolhamid
Article Type: Research Article
Abstract: Reliability-based dome optimization (RBDO) is one of the most robust methods nowadays, which has made it possible to achieve a high degree of safety and optimum structural design at the same time. The purpose of optimization, based on the reliability of space domes, is to find the best set of sections of the structural members, which leads to the minimum structural weight, incorporating the probabilistic constrains. In the contest of reliability or probabilistic constrain, the applied loads, the module of elasticity, and the cross-sections of the members are considered as random variables with the specified probability distributions. The particle swarm …method (PSO) is used as optimization algorithm because it is a simple and robust method in the case of nonlinear objective functions. In order to investigate the effect of probabilistic constraints selections based on three displacement, stress, and combination of displacement and stress, three space domes with different height to span ratios are considered in this research. The results indicate the optimal structural weight of space domes vary with changes the height-to-span ratio and type of the constraint model selections. Therefore, in order to obtain the optimum space domes in regards to the structural weight, incorporation of both probabilistic constraints of combined stress and displacement is essential in design step. Show more
Keywords: Space domes, particle swarm method, reliability index, probabilistic constraints, reliability-based optimization
DOI: 10.3233/JIFS-18034
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 645-655, 2019
Authors: Chu, Chun-Hsiao | Lin, Scott Shu-Cheng | Julian, Peterson
Article Type: Research Article
Abstract: Xu (2017) published a paper in Journal of Intelligent and Fuzzy Systems in which he constructs a new distance measure that not only satisfies the axiom of intuitionistic fuzzy sets, but also fulfills the axiom for traditional distance. However, several questionable results arise in Xu (2017). Thus, the purpose of this paper is threefold. First, his proof is improved. Second, his criticism for two previously published distance measures are amended. Third, it is shown that in his numerical examples, there are several poorly-founded discussions. The refinement will help readers understand Xu (2017) and then apply his new distance measure to …pattern recognition problems and medical diagnosis problems. Show more
Keywords: Distance measure, similarity measure, intuitionistic fuzzy sets
DOI: 10.3233/JIFS-181003
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 657-667, 2019
Authors: Li, Yongkun | Shen, Shiping
Article Type: Research Article
Abstract: In this paper, a class of quaternion-valued BAM neural networks with time-varying delays on time scales is proposed. Based on inequality analysis techniques on time scales, a fixed point theorem and the theory of calculus on time scales, the existence and global exponential stability of almost automorphic solutions for this class of neural networks is established. The obtained results are completely new and supplement to the known results. Finally, a numerical example is given to illustrate the feasibility of our results.
Keywords: BAM neural networks, Almost automorphic solution, Quaternion, Global exponential stability, Time scales
DOI: 10.3233/JIFS-181118
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 669-685, 2019
Authors: Khan, Muhammad Adnan | Umair, Muhammad | Saleem, Muhammad Aamer | Ali, Muhammad Nadeem | Abbas, Sagheer
Article Type: Research Article
Abstract: In modern communication, MIMO technology appeared to be one of the important technologies. System capacity and service quality are enhanced by using this technology. The mission of both channel and data estimation based on the principle of maximum likelihood is achieved by means of continuous and discrete TOMPSO algorithm over Rayleigh Fading Channel. The algorithm has three levels. At the first stage, channel and data populations are prepared. The continuous TOMPSO is using to estimate channel parameters at the second stage. Once the channel is estimated, it is used at stage 3 along with discrete TOMPSO to estimate transmitted symbols. …It is observed that due to included total opposite based learning of swarmand velocity factor the TOMPSO gives a fast convergence rate and attractive results in terms of MMSE and MMCE. Show more
Keywords: MIMO, TOMPSO, BER, MMSE, MMCE
DOI: 10.3233/JIFS-181127
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 687-692, 2019
Authors: Li, Xiao-Yang | Xiong, Yun | Duan, Chun-Yan | Liu, Hu-Chen
Article Type: Research Article
Abstract: Failure mode and effect analysis (FMEA) is a powerful reliability management tool for identifying and eliminating known and potential failures in systems, designs, processes, or services to improve their safety and reliability. At present, FMEA has been widely used in various industries. However, the traditional risk priority number (RPN) method has been criticized for many defects. For example, it ignores the relative importance of the risk factors severity (S), occurrence (O), and detection (D), and it is difficult for experts to evaluate the risk of failure modes using precise values from 1 to 10. In this study, we develop a …new FMEA model that combines interval type-2 fuzzy sets (IT2FSs) and fuzzy Petri nets (FPNs) to overcome the drawbacks and improve the effectiveness of the traditional FMEA. The rationality and accuracy of the proposed FMEA are illustrated by an example of aerospace electronics manufacturing project. The results show that the new risk assessment model can produce more reliable and reasonable risk ranking results of failure modes in the practical application. Show more
Keywords: Failure mode and effect analysis (FMEA), interval type-2 fuzzy set (IT2FS), fuzzy petri net (FPN), fuzzy reasoning
DOI: 10.3233/JIFS-181133
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 693-709, 2019
Authors: Huu, Quynh Nguyen | Viet, Dung Cu | Thuy, Quynh Dao Thi | Quoc, Tao Ngo | Van, Canh Phuong
Article Type: Research Article
Abstract: Over the years, many content-based image retrieval (CBIR) methods, which use SVM-based relevant feedback, are proposed to improve the performance of image retrieval systems. However, the performance of these methods is low due to the following limitations: (1) ignore the unlabeled samples; (2) only exploit the global Euclidean structure and (3) not taking advantage of the various useful aspects of the object. In order to solve the first problem, we propose a graph-based semisupervised learning (GSEL), which can add positive samples and construct balanced sets. With the second problem, we propose a manifold learning for dimensional reduction (MAL), which exploits …the geometric properties of the manifold data. With the third problem, we propose a combination of classifiers by aspect (CCA), which exploits the various useful aspects of the object. Experimental results reported in the Corel Photo Gallery (with 31,695 images), which demonstrate the accuracy of our proposed method in improving the performance of the content-based image retrieval system. Show more
Keywords: Content-based image retrieval (CBIR), relevance feedback, support vector machines (SVM), Graph-based Semisupervised learning and manifold learning
DOI: 10.3233/JIFS-181237
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 711-722, 2019
Authors: Hu, Linmin | Cao, Xuerui | Li, Zhenzhen
Article Type: Research Article
Abstract: The objective of this paper is to establish some reliability models for redundant systems based on the assumption that the conversion switches are imperfect and distribution parameters are uncertain variables. Some new concepts of random uncertain distributions associated with random uncertain variables are proposed, which are applied to redundant series-parallel systems, including cold redundant system and warm redundant system. In each type of redundant system, we consider two methods to describe the switch lifetimes: random uncertain 0-1 switch lifetime and random uncertain geometric switch lifetime. The reliability and the mean time to failure of these systems are analyzed. Some numerical …examples are presented to demonstrate the proposed reliability models and perform a comparison for the system models with uncertain parameters and constant parameters. Show more
Keywords: Redundant system, Imperfect switch, Uncertain variable, Reliability, MTTF
DOI: 10.3233/JIFS-181260
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 723-735, 2019
Authors: Birjandi, A. | Mousavi, S. Meysam | Hajirezaie, M. | Vahdani, B.
Article Type: Research Article
Abstract: Multiple routes of networks in fuzzy environments are essential issues in the project scheduling problems (PSPs) with resource constraints, fuzzy RCPSP-MR. Route assignment to flexible work package defined in a project activity network indicates more complexities in front of canonical PSP. Also, in the last few decades, considering uncertainties’ concepts in project schedules have been essential and attracted the attention of researchers and project managers. Therefore, in this article, a new weighted mathematical model is presented under uncertainty conditions, and a new hybrid fuzzy approach is provided via two fuzzy primary methods. Then, a new four-part non-distinct (FPND) approach is …proposed based on PSO, binary particle swarm optimization (BPSO) and genetic algorithm (GA) to minimize project end cost. In this approach as the first part and to generate high-quality primary routes for flexible work package, six different rules are investigated, and the appropriate route is chosen. In the second part, initial solutions are generated via PSO. Then, in the third part, initial solutions are improved based on GA. Finally, in the last part, assigned routes are improved with binary PSO. To appraise the effectiveness of the presented approach, influential parameters are tuned by Taguchi method. Finally, to evaluate the performance of FPND, 70 numerical examples are designed in different dimensions, and results are compared with other well-known algorithms. Show more
Keywords: RCPSP-MR, fuzzy sets theory, multi-route work package, four-part non-distinct (FPND) approach, distribution rules, Taguchi method
DOI: 10.3233/JIFS-181293
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 737-751, 2019
Authors: Sadi-Nezhad, Soheil | Bonnar, Stephen | Andrews, Doug
Article Type: Research Article
Abstract: The concern for the relationship between demographic changes and asset markets has increased from beginning of 2000. Many researchers analyze the relationship between demographic changes and asset prices through regression models. Most of these studies apply linguistic terms for each different phase of the life cycle (e.g. late working-aged, elderly, adult, and middle-aged) and then define a specific behaviour for each of these cohorts. Although these terms are vague, all the researchers define them as a crisp set with crisp partitions. Additionally, fuzzy regression methods have attracted growing interest from researchers in various scientific, engineering, and humanities area due to …the ambiguity in real data. The motivation of this research is that it is rational to consider and apply fuzzy sets to interpret these linguistic terms instead of the crisp partitions. In this study, we propose and apply a new approach in order to calculate the fuzzy frequency for the linguistic term, which can be useful in any other demographic study. Moreover, new fuzzy regression models are developed. These regression models, that are able to consider both fuzzy and crisp regression coefficients are developed based on applying a fuzzy distance concept in which the distance between two triangular fuzzy numbers (TFNs) or between a TFN and a crisp number is a TFN. Multi-objective optimization helps us to find the results without any compromise. The models are solved using the mathematical programming solver LINGO-16 to derive the fuzzy regression coefficients. We apply these models in a numerical example also in a real case study (fuzzy input, crisp output) in which an investigation on the relationship between fuzzy demographic dynamics and monetary aggregates is made. Show more
Keywords: Fuzzy sets, fuzzy demographic changes, fuzzy regression, fuzzy distance, Marshallian K
DOI: 10.3233/JIFS-181297
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 753-769, 2019
Authors: Gopalakrishnan, Nivetha | Krishnan, Venkatalakshmi
Article Type: Research Article
Abstract: Managing and Mining mobile sensor data has become a topic of advanced research in several fields of computer science, such as the distributed systems, the database systems, and data mining. The main objective of the sensor based applications is to make the real-time decision which has been proved to be very challenging due to the high resource-constrained computing and the enormous volume of sensor data generated by Wireless Sensor Networks (WSNs). This challenge motivates the sensor research community to explore new data mining techniques to extract information from large continuous raw data streams obtained from WSNs. Existing traditional data mining …methods are not directly suited to WSNs due to the aggressive nature of sensor data and the presence of anomalies or outliers in WSNs. This work provides an overview of how traditional outlier detection method algorithms are revised and implemented in the application of Human Activity Recognition (HAR). Based on the limitations of the existing technique, a hybrid outlier detection method is proposed. Show more
Keywords: Classification, data mining, human activity, outlier detection, sensor data
DOI: 10.3233/JIFS-181315
Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 771-782, 2019
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