Journal of Intelligent & Fuzzy Systems - Volume 40, issue 4

Authors: Li, Qian | Li, Shuyuan

Article Type: Research Article

Abstract: Aiming at the precocious convergence, low search accuracy and easy divergence of most particle swarm optimizations with velocity terms, a particle swarm optimization (IWPSO) with random inertia weights and quantization is proposed. First, the inertia weights are obeyed to be distributed randomly, and the learning factors are adjusted asynchronously to optimize the parameters in BP network. Secondly, BP network is trained using the IWPSO algorithm based on the sample data. Finally, simulation experiments prove that the algorithm has significantly improved search speed, convergence accuracy, and stability compared with existing improved algorithms. Due to the characteristics of IWPSO algorithm, the BP …neural network optimized by IWPSO has better global convergence performance and is an efficient particle swarm optimization. Show more

Keywords: Optimization, artificial neural network, swarm intelligence algorithm

DOI: 10.3233/JIFS-189454

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6163-6173, 2021

Authors: Fang, Zhichun | Zhu, Zhengguo | Chen, Xinyu

Article Type: Research Article

Abstract: The construction of tunnels is often long and deep buried tunnels, and the geological conditions are more complex. Based on Jianshan tunnel in Gansu Province, the special geological conditions such as high ground stress and weak interbedded surrounding rock make the excavation of tunnel easy to produce large deformation. In this article, the software finite difference software FLAC3D was used to establish numerical models and select the best construction method by comparing the deformation of the tunnel under different construction methods. Aiming at the deformation characteristics of soft rock tunnels in highland interbedded layers, the control measures of tunnel deformation …are discussed. Mainly consider the two aspects of the bolt support plan and the second lining construction time, comprehensively compare the deformation characteristics of the tunnel, and select the best working condition. The research results show that the combination of three-step temporary invert method and three-step ultra short bench method is recommended for the tunnel construction; when the bench length is 4 m, the deformation control effect of the tunnel is the best; by improving the length and angle of the anchor rod, the deformation of the tunnel can also be well controlled. Show more

Keywords: High ground stress, interbedded soft rock, construction technology, deformation control

DOI: 10.3233/JIFS-189455

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6175-6183, 2021

Authors: Shao, Mengliang | Qi, Deyu | Xue, Huili

Article Type: Research Article

Abstract: Outlier detection is an important branch of data mining. This paper proposes an advanced fast density peak outlier detection algorithm based on the characteristics of big data. The algorithm is an outlier detection method based on the improved density peak clustering algorithm. This paper improves the original algorithm. From the perspective of outlier detection, although it is a clustering idea, it avoids the clustering process, reduces the time complexity of the cluster-based outlier detection algorithm, and absorbs. The outlier detection based on neighbors is not sensitive to data dimensions and other advantages. In the power industry, outlier detection can be …used in areas such as grid fault detection, equipment fault detection, and power abnormality detection. The simulation experiment of outlier detection based on the daily load curve of single and multiple transformers in a certain province shows that the improved algorithm can effectively detect outliers in the data. Show more

Keywords: Outlier detection, big data, KNN algorithm, density clustering

DOI: 10.3233/JIFS-189456

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6185-6194, 2021

Authors: Yu, Hui | Hu, Lingyan

Article Type: Research Article

Abstract: Usually the highlights can be calculated with the specular term of the bidirectional reflectance distribution functions developed for glossy or matte materials. However, as for the translucent materials, complex appearance could be caused by the scattering of light inside the medium. An efficient highlight generation model is presented to simulate the highlight effects on smooth or rough surfaces or around the boundaries of objects made from translucent materials. The presented model is derived from the directional dipole model approximation of the diffusive part of the bidirectional scattering surface reflectance distribution function. Unlike the previous specular reflection models, the presented model …builds a relationship between the highlights and the scattered lights inside the medium by considering the refracted ray of the incident point and the ray toward the emergent point, which could represent the variation in fluence due to the internal scattering at the surface. By integrating a rendering process with the directional dipole model, the resulting highlight effects term could be represented in a similar way by the specular term of a bidirectional reflectance distribution function model. The number and the strength of the generated highlight pixels were compared among typical highlight generation models. It is demonstrated that the presented model could generate highlight effects at the appropriate positions and enhance the perceptual translucency of specific edge areas greatly. Show more

Keywords: Highlights, bidirectional scattering surface reflectance distribution function, bidirectional reflectance distribution function, directional dipole, subsurface scattering, translucency appearance

DOI: 10.3233/JIFS-189457

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6195-6204, 2021

Authors: Li, Wenguang | Feng, Guosheng | Jia, Sumei

Article Type: Research Article

Abstract: This paper studies a hybrid power system composed of fuel cells, super capacitors and batteries. Super capacitors are used as auxiliary energy sources to provide the required high power when the car starts and accelerate, while absorbing braking energy when the car is braking. Fuzzy control is used to optimize its energy management strategy. The fuzzy controller of the three-energy source system takes the battery, super capacitor, and bus demand power as the input of the fuzzy controller, and the battery demand power and the fuel cell demand power as the fuzzy controller output. The system realizes the energy distribution …of super capacitors, fuel cells and storage batteries according to power requirements, thereby improving the performance of the system and extending the life of components. And with hydrogen consumption as the optimization goal, the particle swarm algorithm is used to optimize the parameters of the fuzzy membership function. Compared with the fuzzy control strategy without particle swarm optimization, the optimized fuzzy energy management strategy reduces the hydrogen consumption of fuel cell vehicles. 10 L/(100 km)-1, which improves the economy of the vehicle. Show more

Keywords: Fuel cell vehicles, hybrid powertrain, energy management strategy, fuzzy control, particle swarm optimization

DOI: 10.3233/JIFS-189458

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6205-6217, 2021

Authors: Zhu, Yu | Liu, Xiantao

Article Type: Research Article

Abstract: In this paper, an in-depth study on the quantification of influencing factors and big data visualization of key monitoring indicators in the refined oil products market is carried out through fuzzy mathematical methods, and a system for quantifying influencing factors and big data visualization of key monitoring indicators in the refined oil products market with the fuzzy mathematical background is designed and implemented. The system realizes the functions of flow visualization, attack visualization, target tracking visualization, etc., and optimizes the system from the perspectives of performance and visualization effect. It achieves the display and interaction of multi-dimensional data in space …and time with multiple views, angles, and dimensions. Data tagging and data correlation for key aspects of the product production process are realized through fuzzy mathematics and other means, and a quality traceability system for the manufacturing industry is realized on this basis, through which the data of some key stages of the product production process can be displayed retrospectively. The study proves that the business model of refined oil logistics platform based on value network can significantly improve the user’s perceived value and benefit all parties within the value network, realizing the complementary advantages of refined oil production enterprises and logistics platform companies, improving the efficiency of enterprise’s logistics and maximizing the profit of each subject within the value network to achieve profitability for all parties. Show more

Keywords: Fuzzy mathematics, refined products market, quantification of influences, key monitoring indicators, big data visualization

DOI: 10.3233/JIFS-189459

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6219-6229, 2021

Authors: Tian, Hui | Zhang, Zhujun | Yuan, Zhihua | Liu, Xiaochan | Qi, Yuyan | Wang, Zhenguo | Wang, Liang

Article Type: Research Article

Abstract: In view of the problems of low stiffness, small driving force and large balloon effect existing in the current soft actuator, this paper proposes an optimization method to enhance the overall stiffness of the soft gripper by using rigid components based on the multi-cavity soft pneumatic actuator. This paper introduces the main components of the actuator: the soft part poured by liquid silica gel, and the open rectangular rigid structures by 3D printed. The kinematics model of the finger is established based on the Piecewise Constant Curvature model(PCC). The bending performance of the enhanced stiffness gripper is verified by finite …element analysis(FEA): the tip force of actuator increased with the increase of the number of rigid structures when the bending angle is constant. According to the and experimental data, the overall stiffness of soft gripper is increased by the rigid structure without affecting the flexibility of operation. And the maximum weight which can grasp is 3.4 times that of the traditional soft gripper, improved the grasping range of the soft gripper effectively. Show more

Keywords: Soft gripper, stiffness-enhanced, PCC model, FEA

DOI: 10.3233/JIFS-189460

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6231-6238, 2021

Authors: Wang, Yu | Lian, Zhengmei | Zou, Jihua

Article Type: Research Article

Abstract: The main reason that hinders early treatment of ACS patients is delayed patient decision-making (PD). In order to explore the delay factors of patients with ACS, this paper builds a machine learning-based analysis model of delay factors for patients with acute coronary syndrome based on machine learning. Moreover, this paper combines structural equations to analyze the factors affecting accidents, and uses the generalized ordered logit model in statistics and the popular random forest model in machine learning to establish the analysis models of the delay factors of acute coronary syndromes, and analyze the functional structure of the models. In addition, …this paper obtains data through actual survey methods, and analyzes the data through the model constructed in this paper to explore the risk factors that affect the delay in seeking medical treatment, which is presented through charts. The research results show that the model constructed in this paper is more reliable and can be applied in practice. Show more

Keywords: Machine learning, mountain area, acute coronary syndrome, delay in seeking medical treatment, factor analysis

DOI: 10.3233/JIFS-189461

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6239-6250, 2021

Authors: Huang, Yan

Article Type: Research Article

Abstract: Enterprise marketing is affected by a variety of factors, which lead to certain fluctuations in corporate market influence, and it is difficult to effectively control the elasticity of market influence. In order to improve the elastic analysis effect of enterprise marketing investment, based on the machine learning algorithm, this paper uses the equilibrium movement model to construct an intelligent model suitable for marketing simulation analysis. The equilibrium movement model used in this paper is a simulation of a real situation, which can be used for predictive analysis and can measure how much an exogenous impact can cause endogenous variables to …change. Moreover, this paper establishes a mathematical model to express the influence of marketing with the help of producer surplus, quantify this influence, and use numbers to show the influence of marketing more intuitively. In addition, this paper uses case analysis to study the effect of model analysis. From the research process and conclusions, it can be seen that the model constructed in this paper has certain effects. Show more

Keywords: Balanced mobility model, marketing, investment, elasticity analysis

DOI: 10.3233/JIFS-189462

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6251-6261, 2021

Authors: Zhu, Bin | Zhou, Jie

Article Type: Research Article

Abstract: In order to build a virtual urban planning model and improve the effect of urban planning, this paper builds a virtual urban planning design model based on GIS big data technology and machine learning algorithms, and proposes a solution that combines multiple features. With the development of polarized SAR in the direction of high resolution, a single feature often cannot fully express the detailed information of ground objects, resulting in poor classification results and low accuracy. The combination of multiple features can express feature information well. In addition, this paper uses the ELM method to plan SAR ground object classification, …uses an extreme learning machine classification algorithm with fast learning speed and good classification effect, and uses ELM as a classifier. Finally, this paper designs experiments to explore the performance of the model constructed in this paper from two aspects: detection accuracy and planning score. The research results show that the model constructed in this paper meets the expected goals. Show more

Keywords: GIS, big data, machine learning, urban planning

DOI: 10.3233/JIFS-189463

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 6263-6273, 2021