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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: Ali, Asif | Rashid, Tabasam
Article Type: Research Article
Abstract: Best-worst method (BWM) extended to uncertain situations, generalized interval-valued trapezoidal fuzzy best-worst method (GITrFBWM) is proposed by using generalized interval-valued trapezoidal fuzzy multiplicative preference relation for multiple criteria group decision-making problems. The reference comparison of the best criterion and the worst criterion are described by the linguistic terms, which are expressed in generalized interval-valued trapezoidal fuzzy numbers, of the decision-makers. Weights of criteria are calculated by using graded mean integration representation method. Using the concept of BWM, nonlinearly constrained optimization problems are formed to obtain generalized interval-valued trapezoidal fuzzy weights of different criteria and alternatives. To check the reliability of …the GITrFBWM, consistency ratio is proposed. The advantage and suitability of the proposed GITrFBWM are determined by three case studies. The results indicate that the GITrFBWM, due to higher comparison consistency as compared to BWM and fuzzy-best worst method, obtain plausible preference ranking for alternatives. Show more
Keywords: Generalized interval-valued trapezoidal fuzzy best worst method, Generalized interval-valued trapezoidal fuzzy numbers, Generalized interval-valued trapezoidal fuzzy reference comparison, Consistency ratio, Multiple criteria decision-making
DOI: 10.3233/JIFS-182932
Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 2, pp. 1705-1719, 2020
Authors: Lu, Haishu | Li, Rong | Zhang, Kai
Article Type: Research Article
Abstract: This paper introduces new concepts of fuzzy generalized quasi-weak transfer continuity and fuzzy generalized pseudo quasi-weak transfer continuity for fuzzy generalized discontinuous games with infinite players. Furthermore, by using a collectively maximal element theorem, we obtain some new existence results of Nash equilibria in fuzzy generalized discontinuous games with infinite players. Finally, as applications, some existence results of Nash equilibria in generalized discontinuous games are given in crisp senses. The results presented in this paper improve and generalize some known results in the literature.
Keywords: Fuzzy generalized discontinuous game, Nash equilibrium, maximal element, transfer continuity
DOI: 10.3233/JIFS-182954
Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 2, pp. 1721-1736, 2020
Authors: Jamil, M. | Rahman, K. | Abdullah, S. | Khan, M.Y.
Article Type: Research Article
Abstract: For the multi-attribute group decision-making problems where attribute values are the interval-valued intuitionistic fuzzy numbers, the group decision-making method based on induced generalized Einstein geometric aggregation operators is developed. Firstly, induced generalized interval-valued intuitionistic fuzzy Einstein ordered weighted geometric (I-GIVIFEOWG) aggregation operator and induced generalized interval-valued intuitionistic fuzzy Einstein hybrid weighted geometric (I-GIVIFEHWG) aggregation operator, were proposed. Some general properties such as, idempotency, commutativity, monotonicity and boundedness, were discussed and some special cases were analyzed. Furthermore, the method for multi-attribute group decision-making problems was developed, and the operational processes were illustrated in detail. The main advantage of using the proposed …methods and operators is that these operators and methods give a more complete view of the problem to the decision makers. The proposed methods provide more general, more accurate and precise results. Therefore these methods play a vital role in real world problems. Finally the proposed operators have been applied to decision making problems to show the validity, practicality and effectiveness of the new approach. Show more
Keywords: Group decision-making, I-GIVIFEOWG aggregation operator, I-GIVIFEHG aggregation operator, some einstein operations
DOI: 10.3233/JIFS-182955
Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 2, pp. 1737-1752, 2020
Authors: Chen, Kelvin H.-C. | Wei, Hui-Chuan | Li, Ai-Tzu | Wang, Wei-Ni | Liao, Yu-Hsien
Article Type: Research Article
Abstract: By considering the supreme-utilities among fuzzy action vectors, we adopt several sensible inequality constraints to propose a different generalization of the core on multicriteria fuzzy transferable-utility (TU) games. We also adopt the duality results of linear programming theory to analyze the non-emptiness for this extended core under inequality constraints. Further, we define an extended reduction to characterize this extended core. Based on the notion of domination among fuzzy payoff vectors, some coincidences are investigated.
Keywords: Multicriteria fuzzy TU games, the core, supreme-utilities, inequality constraint, domination
DOI: 10.3233/JIFS-18811
Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 2, pp. 1753-1760, 2020
Authors: Yasrebi, Mohammad | Rafe, Vahid | parvin, Hamid | Nejatian, Samad
Article Type: Research Article
Abstract: Since complexity of computer systems is growing increasingly, assuring flawless operation of these systems has become more difficult. Therefore, it is important that these systems whether software or hardware are executed as expected. Consequently, verifying system before implementation at model level is necessary. Model checking is a formal technique for validating the system automatically which decides whether the finite state system satisfies temporal property by scanning the whole state space or not. One of the most important problems in model checking is state space explosion of models which results in memory shortage in generation of all states. Therefore, this paper …presents a method which employs machine learning techniques without exploring the whole state space to predict temporal properties of trajectories in systems based on graph transmission system. the proposed method is implemented in Groove; results indicate desirable accuracy and speed of this method compared to other methods. Show more
DOI: 10.3233/JIFS-190023
Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 2, pp. 1761-1773, 2020
Authors: Tian, Zhang-peng | Nie, Ru-xin | Wang, Jian-qiang | Luo, Hanyang | Li, Lin
Article Type: Research Article
Abstract: Uncertain linguistic Z-numbers (ULZNs), which inherit the prominent characteristics of linguistic term sets and Z-numbers, can flexibly describe qualitative information as well as its reliability. To cautiously solve a qualitative multi-criteria decision-making (MCDM) problem with larger number of criteria than alternatives, this paper develops an ULZN-based QUALIFLEX (QUALItative FLEXible multiple criteria method) by considering the decision-maker (DM)’s psychological behavior character. First, the likelihood and diversity degree of ULZNs are determined and a comparison method is proposed. Second, a decision model combining the QUALIFLEX and prospect theory is developed to address MCDM problems with ULZNs, considering the incomplete compensation of criteria. …An extended maximizing deviation method is developed to objectively obtain the weights of the criteria. Subsequently, an illustrative example concerning risk evaluation of high-tech project investment with larger number of criteria than alternatives is provided to demonstrate the application of the proposed approach. Finally, sensitivity analysis and comparative analyses are conducted to validate the proposed approach. The result shows that the proposed approach can effectively address MCDM problems with ULZNs, considering the DM’s psychological behavior. Show more
Keywords: Z-numbers, linguistic Z-numbers, multi-criteria decision-making, QUALIFLEX, prospect theory
DOI: 10.3233/JIFS-190065
Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 2, pp. 1775-1787, 2020
Authors: Bordbar, Hashem | Song, Seok-Zun | Bordbar, Mohammad Rahim | Jun, Young Bae | (To the memory of Professor Lotfi A. Zadeh)
Article Type: Research Article
Abstract: In the paper [P.K. Maji, R. Biswas, A.R. Roy, Fuzzy soft sets, J. Fuzzy Math. 9 (3) (2001) 589–602], Maji et al. introduced the concept of fuzzy soft sets as a generalization of the standard soft sets, and presented an application of fuzzy soft sets in a decision making problem. The aim of this paper is to apply fuzzy soft set for dealing with several kinds of theories in hyper BCK -algebras. The notions of fuzzy soft hyper BCK -ideal, fuzzy soft weak hyper BCK -ideal, fuzzy soft s -weak hyper BCK -ideal and fuzzy soft strong hyper BCK -ideal …are introduced, and related properties and relations are investigated. Show more
Keywords: fuzzy soft hyper BCK-ideal,, fuzzy soft weak hyper BCK-ideal,, fuzzy soft s-weak hyper BCK-ideal,, fuzzy soft strong hyper BCK-ideal, 06F35, 03G25, 06D72
DOI: 10.3233/JIFS-190103
Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 2, pp. 1789-1797, 2020
Authors: Wu, Hongzhuang | Liu, Songyong | Cheng, Cheng | Du, Changlong
Article Type: Research Article
Abstract: In this paper, a novel observer based direct adaptive interval type-2 (IT2) fuzzy sliding mode control (SMC) method is proposed for a certain class of high order unknown nonlinear dynamical systems with unmeasured states. Firstly, a high-gain observer is designed to estimate the tracking errors of the system states. Then on the basis of the observer, an IT2 fuzzy logic system (FLS) is established to approximate the equivalent control law, in which the estimate of the sliding surface function is applied as the input. The sliding mode control law is developed to guarantee the robustness of the system, in which …an adaptive switching control gain is designed to handle the chattering problem. The free parameters of the controller are adjusted online by the adaptive laws. Finally, the stability of the overall closed-loop system is proved in the Lyapunov sense based on Meyer-Kalman-Yakubovich (MKY) lemma. In the proposed control system, the constraints on the knowledge of mathematical model, disturbances, and state vector can be avoid completely, and the trajectory tracking control can be achieved only using the information of system output. Simulation results demonstrate the effectiveness and the high control performance of the proposed controller. Show more
Keywords: Adaptive control, interval type-2 fuzzy logic system, observer, sliding mode control, unknown nonlinear systems
DOI: 10.3233/JIFS-190132
Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 2, pp. 1799-1810, 2020
Authors: Ambika, M. | Raghuraman, G. | SaiRamesh, L. | Ayyasamy, A.
Article Type: Research Article
Abstract: Hypertension is a major non-communicable disease, a silent killer that serves as a root cause for many entangled maladies. Early analysis and detection will play vital roles in reducing the prevalence of hypertension and its associated risk factors. As medicine moves forward, there is a need for sophisticated decision support systems to make real-time predictions. Since most medical applications need to deal with multi-class problems, high diagnostic prediction accuracy is extremely important. The quality of data also significantly affects the learning model’s performance. These issues induce the need for proper exploration and investigation of the multi-class medical dataset. This research …intends to present an intelligent learning model that can explore medical data and offer decision support for domain experts and individuals. As clinical data tend to be, grimy appropriate pre-processing techniques are essential to ensure high data quality. This paper deals with the poor-quality data using computational statistical techniques. The prominent features are obtained by employing diverse feature selection techniques and provide a competitive report. We evolved a supervised learning model that can handle multi-class issues in diagnosing medical data categories. This model will learn from the data samples by using a multi-class support vector machine technique to generate precise predictions. We evaluated our learning model by using a real-time hypertension dataset obtained from primary health centres. The proposed approach improves predictive accuracy, precision and recall for handling the multi-class dataset above that of existing techniques. The outcome positively reveals that the proposed intelligent model is effective in undertaking medical decision-making task. Show more
Keywords: Medical decision support system, medical diagnosis, pre-processing, feature selection, machine learning, multi-class classifier, hypertension
DOI: 10.3233/JIFS-190143
Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 2, pp. 1811-1825, 2020
Authors: Bhatt, Priyang | Thakker, Bhaskar
Article Type: Research Article
Abstract: In an Internet of Things (IoT) environment, any object, which is equipped with sensor node and other electronic devices can involve in the communication over wireless network. Hence, this environment is highly vulnerable to botnet attack. Nevertheless, the challenge prevailed in detection of botnet attack due to its unique structurally repetitive nature, performing dissimilar activities that are non-linear, and an invisible nature by deleting the history. Even though existing mechanisms have taken action against the botnet attack proactively, it failed to capture the frequent abnormal activities of botnet attackers due to frequent monitoring. Moreover, when the number of devices in …the IoT environment has increased, existing mechanisms has missed more number of botnets due to functional complexity. Therefore, to overwhelm the issues in detecting the botnet attack, our work has proposed a Bootstrap Aggregating Surflex-PSIM Classifier. It gathers data from several sensor nodes, which are then preprocessed using Linear Random Euler complex-valued Filter (LRECF). Accordingly, the linearized data is subjected to the training phase comprising of Random Poison Forest (RPF) to predict accurately the botnet creating Distributed Denial of Service (DDoS) and Spam attacks within less time. After being trained, similar botnets are clustered using surflex-PSIM that isolates the botnet attacked clusters based on automatic trained characteristics pocket value. Thus, with the aid our proposed classifier, botnet is detected and isolated with high accuracy at reduced time, thereby ensures system reliability with enhanced system performance. Show more
Keywords: Random Poisson forest, Linear Random Euler complex-valued filter, Psim-protein similarity
DOI: 10.3233/JIFS-190183
Citation: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 2, pp. 1827-1840, 2020
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