Journal of Intelligent & Fuzzy Systems - Volume 39, issue 3

Authors: Li, Xiaoping | Tao, Yujie | Li, Yanhong

Article Type: Research Article

Abstract: A polygonal fuzzy numbers can describe fuzzy information by means of finite ordered real numbers. It not only overcomes the complexity of traditional fuzzy number operations, but also keeps some good properties of trapezoidal fuzzy numbers, and it can approximate general fuzzy numbers with arbitrary precision. In this paper, a weighted arithmetic average operator is defined by the ordered representation and its operations of the polygonal fuzzy numbers, and a new Euclidean distance for measuring the polygonal fuzzy numbers is given. Secondly, in view of cost attribute and benefit attributes, the polygonal fuzzy decision matrix is normalized, and the weighted …Euclidean distance is used to solve the positive (negative) ideal solution and the relative closeness of the decision matrix, and then a new decision method is given. Finally, the effectiveness of the proposed decision-making method is illustrated by an example of the evaluation of logistics companies by shopping websites. Show more

Keywords: Polygonal fuzzy number, ordered representation, Euclidean distance, positive (negative) ideal solution, multiple attribute decision making

DOI: 10.3233/JIFS-191588

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3151-3166, 2020

Authors: Sinha, Bam Bahadur | Dhanalakshmi, R.

Article Type: Research Article

Abstract: In the current era of big data, the recommender system aspires to provide users with a tailored set of personalized items from a pool of a large population. The most popular collaborative filtering system performs this information filtering process by computing similarity among users or items. This paper proposes a similarity metric that comprises of weights and values. Values are calculated by considering the matching set of users for which similarity is to be computed. The optimal values of weights are decided using an upgraded form of the Crow Search Algorithm (CSA). The exploration and exploitation stability of CSA is …improvised by making use of Levy flight diffusion, adaptive operator adjustment, and event factor. The performance of the implemented metaheuristic approach is validated on Jester, MovieLens 100K, and MovieLens 1M dataset. Comparative analysis of proposed model against several other traditional metaheuristic based personalization systems reveal that our model is less delicate to the dimension of datasets and it also presents exceptional refinement in terms of prediction complexity and accuracy. Show more

Keywords: Collaborative filtering, similarity, crow search algorithm, optimization, movielens, jester

DOI: 10.3233/JIFS-191594

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3167-3182, 2020

Authors: Li, Jieya | Yang, Liming

Article Type: Research Article

Abstract: The classical principal component analysis (PCA) is not sparse enough since it is based on the L 2 -norm that is also prone to be adversely affected by the presence of outliers and noises. In order to address the problem, a sparse robust PCA framework is proposed based on the min of zero-norm regularization and the max of L p -norm (0 < p  ≤ 2) PCA. Furthermore, we developed a continuous optimization method, DC (difference of convex functions) programming algorithm (DCA), to solve the proposed problem. The resulting algorithm (called DC-LpZSPCA) is convergent linearly. In addition, when choosing different p …values, the model can keep robust and is applicable to different data types. Numerical simulations are simulated in artificial data sets and Yale face data sets. Experiment results show that the proposed method can maintain good sparsity and anti-outlier ability. Show more

Keywords: Principal component analysis, sparseness, robustness, zero-norm, DC programming, face reconstruction

DOI: 10.3233/JIFS-191617

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3183-3193, 2020

Authors: Mehrani, Mohammad | Attarzadeh, Iman | Hosseinzadeh, Mehdi

Article Type: Research Article

Abstract: Wireless Body Area Networks (WBANs) have been introduced as a useful way in controlling health status of the monitored patients, during recent years. Each WBAN includes a number of biosensors attached to the patient’s body, collecting his vital sign features and communicating them to the coordinator to make appropriate decisions. Managing energy consumption of biosensors and continuous monitoring of the patients are two main issues in WBANs. Hence, denoting efficient sampling frequency of biosensors is very important in WBANs. In this paper, we propose a scheme which aims at determining and forecasting sampling rate of active biosensors in WBANs. In …this regard, from the first round until a certain round, the sampling rate of biosensors would be determined. Accordingly, we introduce our modified Fisher test, develop spline interpolation method and introduce three main parameters. These parameters are information of patient’s activity, patient’s risk and pivot biosensor’s value. Then, by employing mentioned parameters in addition to the introduced statistical and mathematical based strategies, the sampling rate of active biosensors in the next round would be determined at the end of each entire round. By reaching a pre-denoted round, the sampling rate of biosensors would be predicted through forecasting methods. For this purpose, we develop two machine learning based techniques namely Adaptive Neuro Fuzzy Inference System (ANFIS) and Long Short Term Memory (LSTM). For estimation our approaches we simulate them in MATLAB R2018b software. Simulation results demonstrate that our methods can decrease the number of communicated data by 81%, reduce energy expenditure of biosensors by 73% and forecast the sampling rate of biosensors in the future rounds with 97% accuracy and 2.2753 RMSE. Show more

Keywords: WBANs, sampling rate determining, sampling rate forecasting, energy efficiency, overhead data, modified fisher test, spline, ANFIS, LSTM.

DOI: 10.3233/JIFS-191622

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3195-3227, 2020

Authors: Bai, Nan | Chen, Guangzhu | Hou, Rui | Ying, Feng

Article Type: Research Article

Abstract: With the sustainable development of mobile communication technology and the increasing demand for indoor services, Location-based Service (LBS) is attracting more and more attention. Determining the mobile target’s location is a core problem of LBS. The traditional WiFi signal fingerprint-based positioning technology mainly determines the location information of the mobile target by received RSS, which has high real-time positioning but low positioning accuracy. The fingerprint-based positioning technology using image mainly determines the location information of the mobile target by matching the features of the foreground images, which has the high positioning accuracy but low real-time positioning. This paper presents an …indoor positioning method fusing information of the WiFi signal and RGB image to improve the positioning performance. The WiFi signal is transformed into the W-image according to indoor space and correction radius parameters, then the W-image and RGB image information are fused with LBP feature by the uniform-LBP algorithm. A fusion positioning model based on the sparse representation is established and solved using Lasso and BPDN positioning method. The positioning methods are tested in manufacturing workshop, and the experimental results show that the proposed method can reduce the complexity of the positioning method and achieve the higher positioning accuracy under same conditions. Show more

Keywords: Indoor positioning, WiFi signal, RGB image, manufacturing workshop, sparse representation

DOI: 10.3233/JIFS-191647

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3229-3240, 2020

Authors: Xu, Xinggui | Yang, Ping | Ran, Bing | Xian, Hao | Liu, Yong

Article Type: Research Article

Abstract: The tough challenges of object recognition in long-distance scene involves contour shape deformation invariant features construction. In this work, an effective contour shape descriptor integrating critical points structure and Scale-invariant Heat Kernel Signature (SI-HKS) is proposed for long-distance object recognition. We firstly propose a general feature fusion model. Then, we capture the object contour structure feature with Critical-points Inner-distance Shape Context (CP-IDSC). Meanwhile, we pull-in the SI-HKS for capturing the local deformation-invariant properties of 2D shape. Based on the integration of the above two feature descriptors, the fusion descriptor is compacted by mapping into a low dimensional subspace using the …bags-of-features, allowing for an efficient Bayesian classifier recognition. The extensive experiments on synthetic turbulence-degraded shapes and real-life infrared image show that the proposed method outperformed other compared approaches in terms of the recognition precision and robustness. Show more

Keywords: Imaging through turbulent media, shape invariant descriptor, heat kernel signature, shape context, contour shape recognition

DOI: 10.3233/JIFS-191649

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3241-3257, 2020

Authors: Shahsavari-Pour, Nasser | Bahram-Pour, Najmeh | Kazemi, Mojde

Article Type: Research Article

Abstract: The location-routing problem is a research area that simultaneously solves location-allocation and vehicle routing issues. It is critical to delivering emergency goods to customers with high reliability. In this paper, reliability in location and routing problems was considered as the probability of failure in depots, vehicles, and routs. The problem has two objectives, minimizing the cost and maximizing the reliability, the latter expressed by minimizing the expected cost of failure. First, a mathematical model of the problem was presented and due to its NP-hard nature, it was solved by a meta-heuristic approach using a NSGA-II algorithm and a discrete multi-objective …firefly algorithm. The efficiency of these algorithms was studied through a complete set of examples and it was found that the multi-objective discrete firefly algorithm has a better Diversification Metric (DM) index; the Mean Ideal Distance (MID) and Spacing Metric (SM) indexes are only suitable for small to medium problems, losing their effectiveness for big problems. Show more

Keywords: Fuzzy optimization, location and routing, firefly algorithm, NSGAII algorithm, reliability, failure

DOI: 10.3233/JIFS-191654

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3259-3273, 2020

Authors: Tianhe, Yin | Mahmoudi, Mohammad Reza | Qasem, Sultan Noman | Tuan, Bui Anh | Pho, Kim-Hung

Article Type: Research Article

Abstract: A lot of research has been directed to the new optimizers that can find a suboptimal solution for any optimization problem named as heuristic black-box optimizers. They can find the suboptimal solutions of an optimization problem much faster than the mathematical programming methods (if they find them at all). Particle swarm optimization (PSO) is an example of this type. In this paper, a new modified PSO has been proposed. The proposed PSO incorporates conditional learning behavior among birds into the PSO algorithm. Indeed, the particles, little by little, learn how they should behave in some similar conditions. The proposed method …is named Conditionalized Particle Swarm Optimization (CoPSO). The problem space is first divided into a set of subspaces in CoPSO. In CoPSO, any particle inside a subspace will be inclined towards its best experienced location if the particles in its subspace have low diversity; otherwise, it will be inclined towards the global best location. The particles also learn to speed-up in the non-valuable subspaces and to speed-down in the valuable subspaces. The performance of CoPSO has been compared with the state-of-the-art methods on a set of standard benchmark functions. Show more

Keywords: Swarm intelligence, black-box optimizer, particle swarm optimization, adaptive conditionalized particle swarm optimization

DOI: 10.3233/JIFS-191685

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3275-3295, 2020

Authors: Sinha, Keshav | Priya, Annu | Paul, Partha

Article Type: Research Article

Abstract: Cloud has become one of the most demanding services for data storage. On another hand, the security of data is one of the challenging tasks for Cloud Service Provider (CSP). Cryptography is one of the ways for securing the storage data. Cryptography is not a new approach instead of the efficient utilization of cryptographical algorithms is greatly needed. In this work, we proposed a Secure Hidden Layer (SHL) and Application Programming Interface (API) for data encryption. The SHL is consisting of two major modules (i) Key Management Server (KMS) and (ii) Share Holder Server (SHS) which is used for storing …and sharing of cryptographic key. For this purpose, we proposed a server-side encryption algorithm, which is based on the asymmetric algorithm (RSA and CRT) for providing end-to-end security of multimedia data. The experimental results of text and video are evidence that the size of file is not much affected after the encryption and effectively stored at Cloud Storage Server (CSS). The parameters like ciphertext size, encryption time and throughput are considered for performance evaluation of the proposed encryption technique. Show more

Keywords: Secure hidden layer (SHL), key management server (KMS), share holder server (SHS), cloud service provider (CSP), chinese remainder theorem (CRT), cloud storage server (CSS)

DOI: 10.3233/JIFS-191687

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3297-3314, 2020

Authors: Wei, Guiwu | He, Yan | Lei, Fan | Wu, Jiang | Wei, Cun

Article Type: Research Article

Abstract: In recent years, ecological problems have become increasingly serious which are forcing people to give up the past high investment, high consumption and high emission development to promote green growth, implement the green new deal and pay attention to green supply chain research and practice. Therefore, in order to attach great importance to the economic and environmental benefits, enterprises should implement green supply chain and “green” change which has become the trend and urgent. Thus, in order to obtain an optimal green supplier, integration of combined weights and multi-attributive border approximation area comparison (MABAC) under probabilistic uncertain linguistic sets (PULTSs) …has offered a novel integrated model, in which information entropy is utilized for calculating objective weights with PULTSs to acquire the final ranking result of green supplier. Besides, so as to indicate the applicability of devised method, it is confirmed by a numerical case for green supplier selection. Some comparative studies are made with some existing methods. The proposed method can also serve for selecting suitable alternative successfully in other selection problems. Show more

Keywords: Multiple attribute group decision making (MAGDM), probabilistic uncertain linguistic term sets (PULTSs), MABAC method, entropy method, combined weights, green supplier selection

DOI: 10.3233/JIFS-191688

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3315-3327, 2020