Journal of Intelligent & Fuzzy Systems - Volume 39, issue 2

Authors: Wumaier, Heniguli | Gao, Jian | Zhou, Jin

Article Type: Research Article

Abstract: In order to overcome the problems of low accuracy and long time-consuming in traditional short-term forecasting methods for dynamic traffic flow, a short-term forecasting method for dynamic traffic flow based on stochastic forest algorithm is proposed in this paper. This method chooses short-term forecasting equipment for dynamic traffic flow, eliminates invalid data from the collected data, and normalizes the available data to complete data preprocessing before traffic flow forecasting. A combined forecasting model is established to optimize the output of the pretreatment results and complete the dynamic traffic flow rate forecasting. On this basis, the stochastic forest algorithm is introduced …to train the sampling set of flow rate decision tree and generate short-term flow decision tree to realize short-term forecasting of dynamic traffic flow. The experimental results show that the forecasting time of the proposed method is short, always less than 0.5 s, and the forecasting accuracy is high, with more than 97%, so it is feasible. Show more

Keywords: Stochastic forest algorithm, dynamic traffic, short-term forecasting, traffic flow, forecasting method

DOI: 10.3233/JIFS-179924

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 2, pp. 1501-1513, 2020

Authors: Lechen, Xie | Wenlan, Wang

Article Type: Research Article

Abstract: In order to enhance the risk investment evaluation algorithm precision of forestry rights mortgage of farmers, this paper provides a method of risk investment validating process of forestry rights mortgage of farmers based on dynamic Bayes network (DBN) and fuzzy system. For that have to be processed fuzzy data in time arrangement and evaluate the circumstance viably, Intuitionistic Fuzzy Dynamic Bayesian Network (IFDBN) is assembled. Intuitionistic fuzzy thinking is implanted into DBN as a virtual node in this method. Also, another technique to change over the intuitionistic fuzzy thinking yield into likelihood that could contribution to DBN as proof is …proposed. Firstly, it analyzes the risk investment of forestry rights mortgage of farmers, raises the risk evaluation system and adopts normalization and factor analysis methods to pre-process the model index; secondly, by aid of a four-layer DBN model, it puts forward the hierarchical DBN model of risk investment, having input layer, fuzzy layer, fuzzy inference layer and output layer, designs the composition and calculation mode of fuzzy function module and DBN module; Finally, it verifies the viability of the calculation through experimental examination. Show more

Keywords: Multi-factor, dynamic bayes, mortgage loan, demand analysis, fuzzy system

DOI: 10.3233/JIFS-179925

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 2, pp. 1515-1523, 2020

Authors: Zhong, Meisu | Yang, Yongsheng | Zhou, Yamin | Postolache, Octavian

Article Type: Research Article

Abstract: With the development of the large ship, automated container terminals (ACTs) have serious energy consumption and carbon emission problems, reducing the loading and unloading time of ships can ease energy consumption, improve the working efficiency and service level of automated terminals. This paper studies the integrated scheduling problem of the gantry cranes (QCs), automated guided vehicles (AGVs) and automated rail-mounted gantry (ARMG) in automated terminal. According to the loading and unloading operation mode, we build the mixed integer programming model with the goal of minimizing the ship loading and unloading time, and through various algorithms of heuristic and hybrid improved …to solve this problem, it proves the effectiveness of the model to obtain optimized scheduling scheme by numerical experiments, and comparing the different performance of algorithms, the results show that the hybrid GA-PSO algorithm with adaptive auto tuning is superior to other algorithms in terms of solution time and quality, which can effectively solve the problem of integrated scheduling to save the energy of automated container terminal. Show more

Keywords: Automated container terminal, intelligent control fuzzy system, loading and unloading operation, intelligent optimization

DOI: 10.3233/JIFS-179926

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 2, pp. 1525-1538, 2020

Authors: Bing, Feng

Article Type: Research Article

Abstract: In order to effectively improve the accuracy of related analysis models in the application of government risk investment, a government risk investment prediction model based on fuzzy clustering discrete algorithm is put forward in this paper. First of all, government risk investment problem is analyzed. Based on Markowitz theory, the general government risk investment model is considered, and the market value constraint and the upper bound constraint are combined to improve the government risk investment model and obtain the mixed constraint government risk investment model. Secondly, the fuzzy clustering discrete algorithm is introduced in the analysis process of government venture …investment model, and it is used to solve the mixed constraint analysis model of government venture investment. In addition, to further improve the performance of discrete algorithm based on fuzzy clustering in the model solving process, automatic contraction and expansion of factors is used to carry out adaptive learning of related parameters based fuzzy clustering discrete algorithm, and improve the convergence of the algorithm. Finally, the simulation experiments on some stock samples of investment sector show that the algorithm in this paper can obtain more ideal government venture investment schemes, so as to reduce investment risk and obtain greater investment returns. Show more

Keywords: International perspective, enterprise innovation, fuzzy clustering, discrete equilibrium analysis

DOI: 10.3233/JIFS-179927

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 2, pp. 1539-1546, 2020

Authors: Xu, Cheng | Liu, Hongzhe | Pan, Zhenhua | Li, Wenfa | Ye, Zhao

Article Type: Research Article

Abstract: Vehicular ad hoc networks play an important role in current intelligent transportation networks, which have attracted much attention from academia and industry. Vehicular networks can be implemented by Long-Term Evolution Advanced (LTE-A) networks, which have been formally defined in a series of standards by third-generation partnership projects (3GPP). Abundant challenges exist in the authentication processes in LTE-A-based vehicular networks. This paper aimed to improve the security functionality of these vehicular networks by proposing a secure and efficient group authentication and privacy-preserving scheme for vehicular networks based on fuzzy system: the group authentication and privacy-preserving level (GAPL). Compared with existing schemes, …the proposed scheme can greatly reduce the number of control message transmissions from mass vehicular equipment (VEs) to the network and substantially avoid overhead in LTE-A-based vehicular networks. Privacy-preserving levels are established to protect VE privacy in authentication. Furthermore, the scheme contains security functions, including privacy preservation, non-frameability and non-repudiation verification. Show more

Keywords: Group authentication, key agreement, LTE-A, vehicular network, fuzzy system

DOI: 10.3233/JIFS-179928

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 2, pp. 1547-1562, 2020

Authors: Abudureheman, Abuduaini | Nilupaer, Aishanjiang | He, Yi

Article Type: Research Article

Abstract: Influenced by national policies and macro-economic environment, large domestic enterprises is actively promoting strategic transformation to enhance their core competitiveness, and performance evaluation of enterprises’ innovation capacity has become a hot topic in recent years. This paper proposes a performance evaluation method of enterprises’ innovation capacity based on deep learning fuzzy system model and convolutional neural network analysis of innovation network. First of all, on account of the characteristics of breakthrough innovation and drawing on the traditional innovation performance evaluation model, this paper constructs a breakthrough innovation performance evaluation index system for enterprises from the six dimensions of main resource …input, technology out-turn, process management, product performance, social value and commercial Value. Secondly, the introduction of machine learning of fuzzy convolutional neural network to assess the advancement execution of enterprises is of great significance for enterprise managers to find out the problems and causes of enterprises’ innovation, optimize the allocation of enterprises’ resources and further improve the innovation performance of enterprises. The experimental results show to verify the adequacy of the algorithm. Show more

Keywords: Innovation network, fuzzy system model, convolutional neural network (CNN)

DOI: 10.3233/JIFS-179929

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 2, pp. 1563-1571, 2020

Authors: Yonglei, Cao | Xiaodong, Zhang

Article Type: Research Article

Abstract: A control strategy of permanent magnet-oriented field synchronous motor based on intelligent fuzzy control system and generalized predictive control with non-linear identification is proposed to develop the effectiveness of the controlling method of constant magnet-oriented field synchronous motor, the accessor can be split into stabilization control part and intelligent control part. The input of traditional feedback control is used as the stabilization control part, while the feed-forward is incorporated into the intelligent part to compensate for the uncertainties of repetitive load torque and model parameters. The proposed feed forward compensation term uses simple learning rules without any load torque disturbance …observer. The additional learning feed forward term does not require information about motor parameters and load torque values, it is insensitive to load torque uncertainty and model parameters, and does not need to identify the system model. With that, the solidness and intermingling confirmation of the proposed control framework reaction is given. The exploratory outcomes demonstrate that the proposed technique has littler speed overshoot list, and the heap torque against aggravation capacity list is improved by over 30%. Show more

Keywords: Nonlinear identification, generalized predictive control, permanent magnet synchronous motor, intelligent fuzzy control system

DOI: 10.3233/JIFS-179930

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 2, pp. 1573-1579, 2020

Authors: Shi, Yuanbo | Wang, Jianhui | Fang, Xiaoke | Gu, Shusheng | Wang, Xiao

Article Type: Research Article

Abstract: The utilization of fuzzy logic in WSNs is demonstrated to be a promising procedure since it permits joining and assessing various parameters in an effective way. Fuzzy logic is a decent methodology because of the execution prerequisites can be effectively supported by sensor hubs, while it can improve the general system execution. This paper studies the robust H ∞ control considering time delay and packet loss related uncertainty in wireless sensor network system based on the basic theory of intelligent fuzzy systems. The model of a wireless sensor network with questionable time lag and packet loss is given first. …The stability of the system is proved by the augmented Lyapunov functional and the linear matrix inequality (LMIs) method, with its demonstrated H ∞ property. In order to solve the uncertain time delay and packet loss, the memory robust H ∞ controller is proposed based on LMIs. Numerical examples and simulation results examines the potency of the presented method in solving the delay and packet loss of wireless sensor networks as well as the accuracy and precision of the system. Show more

Keywords: Time delay, intelligent fuzzy system, linear matrix inequality (LMIs), memory robust H∞ controller

DOI: 10.3233/JIFS-179931

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 2, pp. 1581-1590, 2020

Authors: Huang, Lingxiao | Qiao, Qiao | Zheng, Lanxiang | Liu, Libo | Zhao, Wenjuan | Jing, Hefang | Li, Chunguang

Article Type: Research Article

Abstract: In order to study the water flow movement of the Yazidang Reservoir, this paper generates the initial terrain for the researched water area with the image stitching technology and image edge detection technology, establishes a 3D k  - ɛ mathematical model, solves the equations discretely by FVM and SIMPLEC algorithms, studies the numerical simulation of the water flow movement of the reservoir under four working conditions, and analyzes the flow field on the surface and at the bottom of the reservoir. The results show the improved terrain pre-processing accuracy and efficiency of the researched water area and the rationality of …the water flow field and rate simulation results, which means that the established 3D turbulence mathematical model can be applied to the numerical simulation of the reservoirs similar to the Yazidang Reservoir. The numerical simulation of 3D turbulence in Yazidang Reservoir provides a theoretical basis and practical application value for the numerical simulation of similar reservoirs. Show more

Keywords: Water flow movement, the Yazidang Reservoir, image stitching, edge detection, 3D k - ɛ mathematical model, numerical simulation, flow field

DOI: 10.3233/JIFS-179932

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 2, pp. 1591-1600, 2020

Authors: Yu, Hongyan | Ji, Shenjia | Yang, Deli

Article Type: Research Article

Abstract: Fake online reviews are so prevalent that e-commerce platforms attempt to control it from affecting the trustworthiness between buyers and sellers. The issue has also attracted sporadic scholarly endeavor to understand this new field. To address this issue, we propose a new model to examine three interrelated stakeholders of e-Commerce platforms: experienced buyers, future buyers and the online sellers in terms of purchasing behaviors and sales with three objectives. Experienced buyers influence future consumers’ behaviors and increase sales from sellers. Using data collected from the largest online e-commerce platform in China, we test relevant hypotheses. Our findings show that experienced …buyers and their positive reviews increase future buyers’ purchasing and promote corporate sales. These findings contribute knowledge to the online feedback mechanism and literature on fake review studies. This study also provides a novel method to help buyers avoid fake online review from a market structure perspective. Show more

Keywords: Online feedback mechanism, fake online reviews, e-commerce, experienced consumer reviews

DOI: 10.3233/JIFS-179933

Citation: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 2, pp. 1601-1610, 2020