Journal of Intelligent & Fuzzy Systems - Volume 37, issue 5

Authors: Singh, Abhilash | Sharma, Sandeep | Singh, Jitendra | Kumar, Rahul

Article Type: Research Article

Abstract: Wireless sensor networks (WSNs) found application in many diverse fields, starting from environment monitoring to machine health monitoring. The sensor in WSNs senses information. Sensing and transmitting this information consume most of the energy. Also, this information requires proper processing before final usages. This paper deals with minimising the redundant information sensed by the sensors in WSNs to reduce the unnecessary energy consumption and prolong the network lifetime. The redundant information is expressed in terms of the overlapping sensing area of the working sensors set. A mathematical model is proposed to find the redundant information in terms of the overlapping …area. A combined meta-heuristic approach is used to achieve the optimal coverage, and the effect of the overlapping area is considered in the objective function to reduce the amount of redundant information sensed by the working sensors set. Improved genetic algorithm (IGA) and Binary ant colony algorithm (BACA) are used as meta-heuristic tools to optimise the multi-objective function. The objective was to find the minimum number of sensors that cover a complete scenario with minimum overlapping sensing region. The results show that optimal coverage with the minimum working sensor set is achieved and then by incorporating the concept of overlapping area in the objective function, sensing of redundant information is further reduced. Show more

Keywords: Improved genetic algorithm, Binary ant colony algorithm, Redundant information, Objective function, Overlapping area

DOI: 10.3233/JIFS-190605

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6829-6839, 2019

Authors: Yu, Qian | Dian, Songyi | Li, Yong | Liu, Jiaxin | Zhao, Tao

Article Type: Research Article

Abstract:  Since the non-singleton fuzzy logic controllers (NFLCs) can effectively reflect the uncertainty brought by the inputs, they are used for balance control and position control of the mobile two-wheeled self-balancing robot (MTWSBR) in this paper. The similarity between the inputs and the antecedent fuzzy sets as the firing strength, that is, the similarity-based non-singleton fuzzy logic controller (Sim-NFLC), is proposed to deal with the problem of information loss caused by the standard non-singleton fuzzy logic controller (Sta-NFLC) in terms of the interaction of the inputs and antecedents. A comparative study among singleton fuzzy logic controllers (SFLCs), Sta-NFLCs and Sim-NFLCs, and …interval type-2 fuzzy logic controllers (IT2FLCs) and general type-2 fuzzy logic controllers (GT2FLCs) are also shown. The simulation results show that the performance of Sim-NFLCs is better than that of SFLCs and Sta-NFLCs. The similarity-based general type-2 fuzzy logic controller (Sim-NGT2FLC) gets the best performance in handling the input uncertainty. Show more

Keywords: Mobile two-wheeled self-balancing robot, non-singleton general type-2 fuzzy logic controllers, similarity measure, firing strength

DOI: 10.3233/JIFS-190683

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6841-6854, 2019

Authors: Elakkiya, R. | Vanitha, V.

Article Type: Research Article

Abstract:  Vision-based Sign Language Recognition has been an open research problem since decades. Many existing methods for sign recognition works well under restricted laboratory conditions but failed to support real-time scenarios because extraction of manual and non-manual movements with constantly changing shapes of signs are considered as tedious problem in machine vision and machine learning. To overcome these shortcomings, an interactive real time class level gesture similarity based sign recognition using Artificial Neural Network is presented in this paper. The method uses the sign images and starts with enhancing the image quality. The quality enhancement is performed by equalizing the histograms …of luminance and contrast. The features of hand as subunits from quality improved image have been extracted by template matching techniques. Extracted features are used to generate neural network and trained with different class of signs. The classification is performed by measuring the class level gesture similarity measure towards each class of signs and images. Based on the measure estimated, the method classifies the image and sign. The result produced to the user has been iterated based on the actions provided by the user. The method is capable of iterating the result and recognition till the user gets satisfied. The method produces higher accuracy in sign recognition and reduces the false ratio. Show more

Keywords: ANN, sign recognition, gesture similarity, CLGSM, template matching, interactive systems

DOI: 10.3233/JIFS-190707

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6855-6864, 2019

Authors: Enayattabr, M. | Ebrahimnejad, A. | Motameni, H. | Garg, H.

Article Type: Research Article

Abstract: Researchers have studied several different types of directed shortest path (SP) problems under fuzzy environment. However, few researchers have focused on solving this problem in an interval-valued fuzzy network. Thus, in order to light these, we investigate a generalized kind of the SP problem under interval-valued fuzzy environment namely all pairs shortest path (APSP) problem. The main contributions of the present study are fivefold: (1) In the interval-valued fuzzy network under consideration, each arc weight is represented in terms of interval-valued fuzzy number. (2) We seek the shortest weights between every pair of nodes in a given interval-valued fuzzy network …based on a dynamic approach. (3) In contrast to most existing approaches, which provide the shortest path between two predetermined nodes, the proposed approach provides the interval-valued fuzzy shortest path between every pair of nodes. (4) Similarly to the competing methods in the literature, the proposed approach not only gives the interval-valued fuzzy weights of all pairs shortest path but also provides the corresponding interval-valued fuzzy APSP. (5) The efficiency of the proposed approach is illustrated through two applications of APSP problems in wireless sensor networks and robot path planning problems. Show more

Keywords: Shortest path problem, dynamic programming, interval-valued fuzzy numbers, wireless sensor network

DOI: 10.3233/JIFS-190711

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6865-6877, 2019

Authors: Liu, Zhiyong | Jia, Fangyun | Wang, Ali | Luo, Lianhe

Article Type: Research Article

Abstract: This study investigated fault information estimation and diagnosis using a novel approach based on an integrated fault estimator and state estimator for an electric motor in coal mine. The proposed scheme uses a self-constructing fuzzy unscented Kalman filter (UKF) system to simultaneously estimate the system state and approximate the fault information. To achieve this, a generalized linear discrete-time system of the electric motor in coal mine without faults was first transformed into an equivalent standard state-space system with faults. Then, the self-constructing fuzzy UKF system was designed in order to obtain the fault information. According to fault information obtained fault …detection experiments based on fuzzy clustering were performed with the proposed scheme and the fault feature parameters required for fault isolation were determined. Finally, the scheme was applied to an electric motor in coal mine to demonstrate the effectiveness of the proposed fault estimation and diagnosis approach. Results of the simulation illustrate the effectiveness of the proposed method. Show more

Keywords: Self-constructing fuzzy system, unscented Kalman filter (UKF), state estimation, fault information, electric motor, coal mine

DOI: 10.3233/JIFS-190755

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6879-6890, 2019

Authors: Liu, Shiqin

Article Type: Research Article

Abstract: Uncertain differential equation with jumps is a type of uncertain differential equation driven by both Liu process and uncertain renewal process. Many concepts of stability for uncertain differential equation with jumps have been investigated. This paper presents a concept of exponential stability for uncertain differential equations with jumps, and gives a sufficient and necessary condition for the linear uncertain differential equation with jumps being exponentially stable. The relationships among stability in measure, stability in in mean, stability in p -th moment, and almost sure stability for uncertain differential equation are also discussed.

Keywords: Uncertain differential equation, exponential stability, uncertainty theory

DOI: 10.3233/JIFS-190771

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6891-6898, 2019

Authors: Jia, Heming | Li, Yao | Lang, Chunbo | Peng, Xiaoxu | Sun, Kangjian | Li, Jinduo

Article Type: Research Article

Abstract: Grasshopper optimization algorithm (GOA) is proposed for imitating grasshopper’s behavior in nature, which has the disadvantages of slow convergence speed and unbalanced exploration and exploitation, etc. Therefore, an algorithm called GOA_jDE, which combines GOA and jDE is proposed to improve the optimization performance. Firstly, the adaptive strategy is introduced into DE to improve the global search ability in the proposed algorithm. Secondly, the combination of jDE and GOA greatly improves the convergence efficiency while maintaining the population diversity. Finally, it can be observed in the work that the proposed algorithm improves the convergence speed and calculation precision. In the subsequent …experiments, 14 well-known test benchmark functions are used to compare the advantages of GOA_jDE. The experimental results illustrate that the performance of proposed algorithm has significant improvement, which also proves the feasibility and effectiveness. Considering the complexity of engineering problems, three classical engineering design problems (tension/compression spring, welded beam, and pressure vessel designs) are used to evaluate the performance of the proposed algorithm. In addition, the classical engineering design results proves the merits of this algorithm in solving real problems with unknown search spaces. Show more

Keywords: Grasshopper optimization algorithm, differential evolution, self-adapting based algorithm, hybrid optimization, functions optimization

DOI: 10.3233/JIFS-190782

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6899-6910, 2019

Authors: Feng, Jianshe | Jia, Xiaodong | Zhu, Feng | Yang, Qibo | Pan, Yubin | Lee, Jay

Article Type: Research Article

Abstract: Maintenance Scheduling and Routing (MS&R) is critical for the offshore wind farm to reduce maintenance cost. Although different models are proposed, the turbine operating conditions and the forecasted wind resources in the maintenance horizon are still less accounted in these current models. To address this issue, this research proposes a novel mathematical model to optimize the MS&R problem by highlighting the significance of turbine production loss (PL) before and during maintenance activities. In the proposed methodology, the PL term takes the most up-to-date wind turbine power curve and the forecasted wind resources as model inputs. Subsequently, a novel Genetic Algorithm …(GA) solver is designed to minimize the PL of wind turbines together with the technician salaries and the transportation costs. The outcome of the proposed model gives a detailed maintenance plan with maintenance schedules, vessel routes, technician assignments, and cost breakdowns. Validation of the proposed model is implemented on real-world data collected from an offshore wind farm with several 4 MW wind turbines. The result demonstrates the effectiveness and superiority of the proposed method, and some practical findings are also summarized in the conclusions. Show more

Keywords: Maintenance scheduling and routing, offshore wind farm, production loss, genetic algorithm

DOI: 10.3233/JIFS-190851

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6911-6923, 2019

Authors: Esfahani, Hassan Noori | Saadati, Reza

Article Type: Research Article

Abstract: We study the problem of Aleksandrov in fuzzy n -normed spaces and prove that every surjective fuzzy function preserving unit n -distance is affine, and thus is a fuzzy n -isometry. Finally, we show that every fuzzy function preserving two fuzzy unit n -distances confirmers the result of Benz theorem when target space is fuzzy n -strictly convex.

Keywords: Aleksandrov problem, f-n-UDPP, f-n-NLS, fuzzy n-isometry, f-β-n-distance, f-n-strictly convex, 54H20, 46L05, 11Y50

DOI: 10.3233/JIFS-190852

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6925-6935, 2019

Authors: Naeem, Khalid | Riaz, Muhammad | Peng, Xindong | Afzal, Deeba

Article Type: Research Article

Abstract:  We study, in this paper, some notions related to Pythagorean fuzzy soft sets (PFSSs) along with their algebraic structures. We present operations on PFSSs and their peculiar characteristics and elaborate them with real life examples and tabular representation to develop the affluence of linguistic variables based on Pythagorean fuzzy soft (PFS) information. We present an application of PFSSs to the multi-criteria group decision-making (MCGDM ) related to site selection, accompanied by Algorithm and flow chart. We develop PFS TOPSIS method and PFS VIKOR method as extensions of the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) and …VIKOR (Vlse Kriterijumska Optimizacija Kompromisno Resenje) respectively. Finally, we rendered an application in stock exchange investment problem and tackled it by both PFS TOPSIS and PFS VIKOR methods. Show more

Keywords: Pythagorean fuzzy soft sets, linguistic variable, MCGDM, aggregation operator, TOPSIS, VIKOR

DOI: 10.3233/JIFS-190905

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 6937-6957, 2019