Journal of Intelligent & Fuzzy Systems - Volume 37, issue 1

Authors: Jing, Yun | Guo, Siye | Zhang, Zhenhua | Jeng, Embrima

Article Type: Research Article

Abstract:  The propose of this paper is building the flow shop model with full-loaded constraints and maximum wagons within the stage. Based on sequence theory, technical operations of marshalling station are described as process of flow shop. By definition of key trains, the adjustment of the classification schedule of inbound trains is attributed to the adjustment of key trains for reducing invalid solution. Based on the LS rules to construct an initial solution, tabu search algorithm (TS) dynamically adjusts taboo step, and build a network model of static wagon-flow allocation for the objective function, to ensure the feasibility of solutions. Finally, …the example demonstrates the effectiveness of the algorithm, and differences between full-loaded and full-cars constrains. Show more

Keywords: Marshaling station, wagon-flow allocating, sequence theory, taboo search, full-loaded

DOI: 10.3233/JIFS-179106

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 527-536, 2019

Authors: Hou, Jing | Meng, Jianfeng | Zhu, Lianmei

Article Type: Research Article

Abstract: Support vector machine need to choose kernel function according to data distribution characteristics, while iterative algorithm of function parameter optimization can effectively improve the validity of data analysis. Using a sample of A-share listed firms in China from 2007–2017, this paper discusses the impact of corporate innovation on stock price crash risk and the moderating effect of investors’ attention on the relationship between the two under the triple effect of enhancing confidence, interpreting information and releasing panic. The results show that: (1) the innovation output is negatively correlated with the stock price crash risk, and the inhibition of substantive innovation …is more significant than that of strategic innovation; Investors’ focus mainly has the effect of enhancing investor confidence, thus strengthening the negative correlation between the two. (2) R&D is positively correlated with the stock price crash risk. Investors’ focus helps to alleviate the information asymmetry and play the effect of information interpretation, thus weakening the positive correlation between the two; (3) the capitalization of development expenses in R&D has not really promoted the enterprise value but has become a means for insider to reduce their holdings and cash. The stock price crash risk is aggravated by the widespread sell-off caused by panic reaction of investors. The research in this paper has certain theoretical and practical significance to improve the substantial innovation of corporates, restrain insider trading behavior, protect the interests of investors and then maintain the stable development of capital market. Show more

Keywords: Fuzzy mathematics, stock price crash risk, corporate innovation, investor focus

DOI: 10.3233/JIFS-179107

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 537-549, 2019

Article Type: Other

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 551-551, 2019

Authors: Rahman, Atta

Article Type: Research Article

Abstract: In this research, a novel block-based, integer wavelet transform (IWT) domain digital image watermarking scheme for optimum information embedding using a Fuzzy Rule Based System (FRBS) is proposed. There are three famous conflicting parameters in digital image watermarking, namely, robustness, imperceptibility and payload are linked with each other and a change in one parameter affects others and vice versa. That’s why it is hard to optimize them, jointly because of the inherent non-linearity and in the literature, any pair of parameters is optimized while third is assumed as fixed. In this proposal, this non-linear problem is solved using FRBS by …using the logical relationship among three parameters and it consequently suggests the image from the image-bank that may convey the desired payload (capacity) with maximum imperceptibility and robustness. The proposed FRBS is two-fold. Firstly, selection of candidate image blocks from the given image and secondly selection of the candidate coefficients from the already chosen blocks for embedding the desired payload. Images having coefficients greater than a certain threshold are chosen and the payload is embedded. Consequently, the watermarked images are passed through various attacks and the image with maximum robustness is selected. The effectiveness of the proposed scheme is demonstrated through MATLAB simulations and comparison with state-of-the-art techniques. Show more

Keywords: Digital image watermarking, IWT, optimum embedding, PSNR, block-based

DOI: 10.3233/JIFS-162405

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 553-564, 2019

Authors: Pakhira, Nilesh | Maiti, Manas Kumar | Maiti, Manoranjan

Article Type: Research Article

Abstract: Here two-level supply chain model is considered for a deteriorating item where the retailer’s warehouse in the market place has a limited capacity. Therefore the retailer can rent a warehouse (RW) if needed with a higher cost compared to own warehouse (OW). This model includes one wholesaler and one retailer and our aim is to maximize the total profit. The demand rate in retailer is stock-dependent and in case of any shortages, the demand is partially backlogged. Retailer also introduces some promotional cost to boost the base demand of the item. It is established that if the wholesaler shares a …part of promotional cost then channel profit as well as individual profit increase. The supply chain model is also considered for imprecise environment when different inventory parameters are fuzzy/rough in nature. In this case individual profits as well as channel profit become fuzzy/rough in nature. As optimization of fuzzy/rough objective is not well defined, following credibility/trust measure of fuzzy/rough event, an approach is proposed for comparison of fuzzy/rough objectives and a Particle Swarm Optimization (PSO) algorithm is used to find marketing decisions. Models are illustrated with numerical examples. Show more

Keywords: Deterioration, Two-warehouse model, Promotional Cost, Credibility/Trust measure, Particle Swarm Optimization

DOI: 10.3233/JIFS-16913

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 565-581, 2019

Authors: Fahmi, A. | Amin, F. | Abdullah, S. | Aslam, M. | Ul Amin, N.

Article Type: Research Article

Abstract:  This paper presents a new concept of trapezoidal cubic fuzzy numbers and solves the plant location selection (PLS) problem based on a new decision method with cubic fuzzy information captured through trapezoidal cubic fuzzy numbers. In the decision process, the unknown weights of the criteria are unearthed by using the Shannon entropy theory and the weights of the decision makers by integrating the Evidence theory with Bayes approximation. Based on trapezoidal cubic fuzzy numbers, we extend the classical VIKOR method to solve the MAGDM problems under cubic fuzzy environment based on the TrCFNs on proposed method.

Keywords: The definition and arithmetical operations of trapezoidal cubic fuzzy numbers, A MAGDM approach based on an extended VIKOR method using trapezoidal cubic fuzzy numbers, The extended VIKOR method using trapezoidal cubic fuzzy numbers, plant location selection, shannon entropy

DOI: 10.3233/JIFS-171049

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 583-596, 2019

Authors: Hassan, Sabo Miya | Ibrahim, Rosdiazli | Saad, Nordin | Asirvadam, Vijanth Sagayan | Bingi, Kishore

Article Type: Research Article

Abstract: The accelerated particle swarm optimisation (APSO) is an improved variant of the PSO algorithm that guarantees convergence through the use of only global best to update both velocity and position of particles. However, like its predecessor, the APSO is also prone to being trapped in local minima. Therefore, this paper proposes two hybrid algorithms synergizing the social ability of the APSO and the exploitative ability of both spiral dynamic algorithm (SDA) and Adaptive SDA (ASDA). The exploration phase of the proposed algorithms APSO-SDA and APSO-ASDA, will be achieved through the APSO algorithm. The exploration phase solutions of the APSO are …then fed to the SDA and ASDA to achieve the exploitation phase. The proposed algorithms have been evaluated with benchmark function and have also been used to tune a filtered predictive proportional-integral (FPPI) controller for WirelessHART networked control systems (WHNCS). The results obtained from Friedman’s rank test show that the proposed APSO-SDA and APSO-ASDA outperformed their constituent algorithms. Time domain analysis of the FPPI controller also show that the APSO-SDA and APSO-ASDA outperformed the APSO, SDA and ASDA in terms of settling times and overshoot. Show more

Keywords: Accelerated PSO, Hybrid optimisation algorithm, predictive PI controller, spiral dynamic algorithm, WirelessHART

DOI: 10.3233/JIFS-171288

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 597-610, 2019

Authors: Shirazi, Abdoreza Noori | Mozaffari, Babak | Soleymani, Soodabeh

Article Type: Research Article

Abstract:  In recent years, because of the regeneration and development of power systems many of their technical and economical characteristics have been changed in different sections of generation, transmission, distribution and consumption. This issue has great impact on transmission systems because of the increased demand and limitation in creation of new lines. System stability against disturbances of big signal is one of the important issues that have been under threat as a result of this issue. In such circumstances, FACTS devices have great impact on increase of control ability and power system stability. One of the most effective FACTS devices is …generalized unified power flow controller (GUPFC). It can combine the capabilities of SSSC, STATCOM and TCPAR by control of different parameters of network and can be used as a multipurpose tool. In this essay, designing a neuro-fuzzy controller for GUPFC to improve transient stability has been investigated. For this purposed, a controllable compensator has been designed to increase transient stability margin and damp transient oscillation in such systems by use of lyapunov stability criterion. Since transient energy function of system is a suitable tool for investigating of stability issue, optimization of GUPFC energy function has been noticed in order to reach the highest margin of transient stability. This idea is the basis of producing required teaching information in ANFIS network and can be used as a GUPFC controller. In this essay, the impact of GUPFC on single machine system, infinite bus (SMIB) and 9-bus system (Anderson and Fouad, 1977) by use of supposed method has been studied. Moreover by simulation of other FACTS devices such as UPFC and IPFC, the priority of GUPFC has been shown and the comparison of its result has been proved. Show more

Keywords: Generalized unified power flow controller (GUPFC), transient stability, lyapunov energy function, critical cleaning time (CCT), neuro-fuzzy control

DOI: 10.3233/JIFS-171488

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 611-623, 2019

Authors: Cai, Nannan | Li, Shugang | Yu, Zhaoxu | Shi, Miaojing

Article Type: Research Article

Abstract: Selecting thepotential brand spokesperson on social network (SN), who has the huge growth potential and will own the largest number of fans in the future, can providehigher returns at lessrisks. In this study, smart link prediction algorithm (SLPA) is proposed to predict the evolvements of SNs and the brand spokesperson with the great future potential is selected based on the prediction results of SN evolution. In SLPA, mean roughness classification uniformity (MRCU) is developed to select the high efficient link prediction algorithm (LPA) for node pairs to be predicted from the local similarity based and quasi-local similarity based LPAs. MRCU …uses the rough set theory and granular computing to describe the similarity of LPAs, consequently the LPA selected with MRCU can share as much similarity as possible with the other base LPAs. Furthermore, SLPA adopts the branch and bound method to smartly cluster node pairs by adaptively selecting optimal LPA for given node pairs and excluding the ones with the least possibility of linking, and consequently the most reliable results of node pairs with the highest linkable possibility are acquired. The experimental results on three SN datasets confirm the validity of SLPA in selecting band spokesperson. Show more

Keywords: Brand spokesperson, rough set, link prediction, branch and bound

DOI: 10.3233/JIFS-171802

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 625-634, 2019

Authors: Chen, G. Y. | Xie, W. F.

Article Type: Research Article

Abstract: Hyperspectral imaging provides new opportunities for improving face recognition accuracy. However, it poses such challenges as difficulty in data acquisition, low signal to noise ratio (SNR), and high dimensionality. In this paper, we propose a novel method for hyperspectral face recognition with good recognition rates. We first reduce noise adaptively from each spectral band and then crop each face. We perform minimum noise fraction (MNF) transform to the cropped face data cube in order to extract a number of MNF bands. We extract histogram of oriented gradients (HOG) features from each MNF band. We conducted some experiments to test this …new method for hyperspectral face recognition with very promising results. For Hong Kong Polytechnic University Hyperspectral Face Database (PolyU-HSFD), we achieved an average correct recognition rate of 95.4% with standard deviation of 2.6 (95.4% ±2.6). For CMU Hyperspectral Face Database (CMU-HSFD), we achieved an average correct recognition rate of 98.1% with standard deviation of 0.8 (98.1% ±0.8). The reasons why we choose MNF for hyperspectral face recognition are because it can separate noise from fine features in the face data cube and at the same time reduce the dimensionality of the face data cube. In this way, our proposed face recognition method will be faster than those methods without dimensionality reduction. Show more

Keywords: Hyperspectral face recognition, minimum noise fraction (MNF), histogram of oriented gradients (HOG)

DOI: 10.3233/JIFS-17283

Citation: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 635-643, 2019