Journal of Intelligent & Fuzzy Systems - Volume 37, issue 2

Authors: Lin, Cheng-Jian | Lee, Chin-Ling

Article Type: Research Article

Abstract: In recent years, multiple robots have been successfully applied in various fields, including the handling of logistics factories, agriculture, and disaster relief. This study proposes a novel method for multi-robot deployment and navigation in dynamic environments. To address the problem of location deployment, a grid-based method was used to simplify environmental input information, and a self-clustering method was used to adjust location deployment. To address the problem of navigation, a behavior manager was used as a navigation strategy to control the towards-goal behavior and wall-following behavior (WFB) of mobile robots. An interval type-2 fuzzy controller based on improved particle swarm …optimization (IPSO) was proposed to implement the WFB control. The proposed IPSO improved the search ability and enhanced the convergence speed of traditional PSO. Additionally, an escape mechanism was proposed to avoid a dead cycle. Experimental results show that the proposed IPSO is superior to other methods used for WFB and navigation control. Show more

Keywords: Robot navigation control, location deployment, particle swarm optimization, type-2 fuzzy controller, self-clustering

DOI: 10.3233/JIFS-182003

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 2, pp. 2181-2195, 2019

Authors: Savas, Ekrem

Article Type: Research Article

Abstract: The goal of this paper is to introduce the concept of λ -statistical convergence of weight g of fuzzy numbers by using ideal. In addition to this concept, some inclusion theorems are also presented.

Keywords: Ideal, Filter, I-statistical convergence of weight g, Iλ-statistical convergence

DOI: 10.3233/JIFS-18216

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 2, pp. 2197-2202, 2019

Authors: Zhao, Tao | Wu, Qing | Li, Shengchuan | Guo, Rui | Dian, Songyi | Jia, Hairui

Article Type: Research Article

Abstract: In this paper, a general type-2 fuzzy logic controller (GT2FLC), which is optimized by the particle swarm optimization (PSO) algorithm, is applied to a power-line inspection (PLI) robot. The information fusion is used to design the GT2FLC to avoid the rule explosion. The proposed controller has the ability to deal with uncertainties when the PLI robot works on the insulated access cable. In order to compare the performance of the proposed controller with that of other controllers, the type-1 fuzzy logic controller (T1FLC) and the interval type-2 fuzzy logic controller (IT2FLC) are both optimized by the PSO to adjust the …PLI robot. To show the ability of different controllers to deal with uncertainties, external disturbances and parameter perturbations are added to the PLI robot. According to simulations, the performance of the proposed controller is better than that of other controllers, and the proposed controller has better ability to deal with uncertainties. Show more

Keywords: Power-line inspection robot, particle swarm optimization algorithm, general type-2 fuzzy logic controller

DOI: 10.3233/JIFS-182515

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 2, pp. 2203-2214, 2019

Authors: Hojaghani, Leily | Nematian, Javad | Shojaie, Amir Abbas | Javadi, Mehrdad

Article Type: Research Article

Abstract: The route length is taken by the operator is deemed to be an effective parameter in minimization of response time’s orders in a typical warehouses with a manual picking system, in which the picker collects goods through depot. Therefore, reduction of the route length has been increasingly received considerable attention from the scholars in this area. The response time and system’s costs are regarded as the most essential components necessitating the utilization of order batching process for rival companies, particularly when there is no information about time and amount of inbound orders, and even when there is substantial amounts of …orders in large warehouses working with an online order entry system. This process has a profound impact on reducing the route length and thus decreasing the organization costs. Present study takes aim at investigation of order classification in the first time in the picker-to-part system as a manual picking system and an online order batching system, with the intent of minimizing the turnover time and idle time. Besides, an order batching model in a blocked warehouse using a zoning system is proposed which is called Online Order Batching in Blocked Warehouse with One Picker for each Block (OOBBWOPB). This is investigated by online order entry system using a nonlinear programming model based on meta-heuristic method of Teaching Learning Based Optimization (TLBO) algorithm. The average turnover time of the customer’s orders is witnessed insignificant reduction using the proposed model, which lead to greatly enhance the total efficiency of warehouse system. Show more

Keywords: Warehousing system, online order batching, warehouse blocking, zoning system, idle time and TLBO algorithm

DOI: 10.3233/JIFS-182527

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 2, pp. 2215-2229, 2019

Authors: Zhang, Xing-Xian | Wang, Ying-Ming | Chen, Sheng-Qun | Chu, Jun-Feng

Article Type: Research Article

Abstract: Dempster-Shafer theory (DST) of evidence has wide application prospect in the fields of information aggregation and decision analysis. To solve the issues of interval evidence combination and normalization, we have reinvestigated the methods provided for interval evidence combination within the frameworks of DST and evidential reasoning (ER) approach, respectively, and pointed out the shortcomings of existing methods. A more general interval evidence combination approach based on the ER rule is constructed. Numerical examples are provided to indicate that the proposed method not only suitable to the conflict-free interval evidence combination, but also to the conflicting interval evidence combination, and interval …evidence specificity can be kept intact in the interval evidence combination process. Moreover, the interval evidence combination methods based on DST or ER are special cases of the proposed method in some cases. Show more

Keywords: Dempster-Shafer theory of evidence, interval evidence, ER approach, ER rule, combination

DOI: 10.3233/JIFS-182529

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 2, pp. 2231-2242, 2019

Authors: Hewahi, Nabil M.

Article Type: Research Article

Abstract: In this paper we present a new algorithm called Neural Network Pruning Based on Input Importance (NNPII) that prunes the neural network based on the input importance. The algorithm depends on the frequency of using a certain value of an attribute in all the given instances in the dataset. Pruning will include only links between input layer and hidden layer. The algorithm has three phases, the first phase is the preprocessing phase, where the data inputs are replaced with their importance. The second phase is a forward pass, which is similar to forward pass in the backpropgation algorithm, but instead …of using the real inputs as inputs, we use the input importance obtained in the preprocessing stage. The third pass is the backward phase which is again as backpropgation algorithm, but in this stage we use the input importance instead of real inputs, and β factor that measures the value changing for every input attribute, β will be incorporated in the formula in updating the weights between the input layer and the hidden layer. The elimination process is performed based on criterion that depends on Ω factor that represents a threshold value for a certain input attribute for all instances. It is worth mentioning that the pruning is performed within the usual training phases. The proposed algorithm has been tested through three types of experiments, a comparison between backpropgation and NNPII, Applying NNPII with various parameter values and finally comparing NNPII with other various pruning algorithms. Results show that NNPII performs well and compete with other pruning algorithms. NNPII outperforms all other algorithms when the classes are fairly distributed in the datasets. Show more

Keywords: Neural networks, pruning, backpropgation

DOI: 10.3233/JIFS-182544

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 2, pp. 2243-2252, 2019

Authors: Zhong, Yu | Chen, Fan-Hong | Shi, Fu-Gui

Article Type: Research Article

Abstract: In this paper, the notions of L -fuzzy convex subgroup and L -fuzzy convex subgroup degree are introduced and their characterizations are given. A new method for describing L -fuzzy convexity is obtained. Also, L -fuzzy convexity preserving mappings and L -fuzzy convex-to-convex mappings are analyzed. Besides, we provide a counter example to illustrate one of the conclusions.

Keywords: L-fuzzy convex subgroup, L-fuzzy convex subgroup degree, L-fuzzy convexity

DOI: 10.3233/JIFS-182568

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 2, pp. 2253-2264, 2019

Authors: Li, Qing-Hua | Huang, Han-Liang | Xiu, Zhen-Yu

Article Type: Research Article

Abstract: By using the residual implication on a frame L , a degree approach to special mappings in L -convex spaces and L -interval spaces is introduced. In the framework of L -convex spaces, degrees of L -CP mappings and L -CC mappings between L -convex spaces are defined. Also, in the situation of L -interval spaces, degrees of L -IP mappings and L -AIP mappings are proposed. Moreover, many conclusions with respect to theses mappings are discussed in a degree sense.

Keywords: L-convex space, L-interval space, L-CP mapping, L-CC mapping, L-IP mapping

DOI: 10.3233/JIFS-182569

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 2, pp. 2265-2274, 2019

Authors: Baghbani, R. | Jamasb, S. | Khodabakhshi, MB.

Article Type: Research Article

Abstract:  A method for image edge detection is proposed, which employs interval-valued fuzzy (IVF) sets such that each pixel has an interval membership constructed from its original and neighboring intensities. This method relies on triangular norms and co-norms to develop operators generating lower (LIB) and upper (UIB) interval bounds, which are employed in a novel membership function. This membership function is then applied to the image represented as fuzzy singletons to generate an image containing the edges associated with the original image. The proposed method is applied to medical images for edge detection and the results are compared with those obtained …based on application of other fuzzy methods as well as a classical method for implementation of edge detectors. The quantitative comparison of the edge binary images determined by each method is performed by employing a metric based on the Hausdorf distance as well as a metric based on the local refinement error known as global consistency error (GCE). The proposed method consistently produced lower values of Baddeley’s Delta metric as well as lower values of GCE. The proposed method was also characterized by values of Pratt’s figure of merit closer to unity as compared with the other methods. Furthermore, the proposed method outperforms a number of commonly employed edge detectors in terms of the processing time required for edge detection. Show more

Keywords: Fuzzy edge, fuzzy relation (FR), interval-valued fuzzy relation (IVFR), membership function

DOI: 10.3233/JIFS-182576

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 2, pp. 2275-2288, 2019

Authors: Jan, Naeem | Zedam, Lemnaouar | Mahmood, Tahir | Ullah, Kifayat

Article Type: Research Article

Abstract:  Recently, Jun et al. have introduced the concept of cubic set as a generalization of the concept of fuzzy set and that of the interval valued fuzzy set. This concept has been widely applied in many circumstances like pattern recognition, decision making etc. So far, no attention has been paid towards graph of cubic set therefore leads us in this manuscript to study the concepts of interval valued bipolar fuzzy graph (IVBFG) and cubic bipolar fuzzy graph (CBFG). Some graph theoretic terms for CBFGs are defined along with the several operations. Illustrative examples are provided to explain the defined terms …and several results are discussed. As application, a cubic bipolar fuzzy influence graph in a social group is elaborated. Show more

Keywords: Cubic fuzzy graphs, bipolar fuzzy graphs, cubic bipolar fuzzy graph, strong cubic bipolar fuzzy graphs

DOI: 10.3233/JIFS-182579

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 2, pp. 2289-2307, 2019