Changjiang Liu¹, Xuling Wu², Bing Mo¹, Yi Zhang³

Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 671-678, 2018, DOI:10.31209/2018.100000033

Abstract With continuing commercialization of remote sensing satellites, the high resolution remote sensing image has been increasingly used in various fields of our life. However, processing technology of high resolution remote sensing images is still a tough problem. How to extract useful information from the massive information in high resolution remote sensing images is significant to the subsequent process. A multi-phase oil tank recognition of remote sensing images, namely coarse detection and artificial neural network (ANN) recognition, is proposed. The experimental results of algorithms presented in this paper show that the proposed processing technology is reliable and effective. More >

Wei Qin, Xiangfeng Luo

Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 653-661, 2018, DOI:10.31209/2018.100000032

Abstract Concept learning has attracted considerable attention as a means to tackle problems of representation and learning corpus knowledge. In this paper, we investigate a challenging problem to automatically construct a patent concept learning model. Our model consists of two main processes; which is the acquisition of the initial concept graph and refined process for the initial concept graph. The learning algorithm of a patent concept graph is designed based on the Association Link Network (ALN). A concept is usually described by multiple documents utilizing ALN here in concept learning. We propose a mixture-ALN, which add links between documents and the… More >

Lin Gao, Mingzhen Wang

Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 643-651, 2018, DOI:10.31209/2018.100000031

Abstract With the rapid development of the petrochemical industry, the number of largescale oil storage tanks has increased significantly, and many storage tanks are located in potential seismic regions. It is very necessary to analyze seismic response of oil storage tanks since their damage in an earthquake can lead to serious disasters and losses. In this paper, three models of vertical cylindrical oil storage tank in different sizes, which are commonly used in practical engineering are established. The dynamic characteristics, sloshing wave height and hydrodynamic pressure of the oil tank considering the liquid-structure coupling effect are analyzed by using ADINA finite… More >

Ling Wu¹, Haoxue Liu², Tong Zhu², Yueqi Hu³

Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 633-642, 2018, DOI:10.31209/2018.100000030

Abstract The objective of the current study was to examine how experienced and inexperienced driver behaviour changed (including heart rate and longitudinal speeds) when approaching and exiting highway tunnels. Simultaneously, the NARX neural network was used to predict real-time speed with the heart rate regarded as the input variable. The results indicated that familiarity with the experimental route did decrease drivers’ mental stress but resulted in higher speed. The proposed NARX model could predict synchronous speed with high accuracy. These results of the present study concern how to establish the automated driver model in the simulation environment. More >

Jun Zhou, Zhenzhen Ge

Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 623-631, 2018, DOI:10.31209/2018.100000029

Abstract In this paper, an adaptive integrated guidance and control (IGC) scheme for the homing missile is proposed based on the novel continuous characteristic model and the dynamic surface control technique. The novel continuous characteristic model is first proposed in the presence of unknown model coefficients and uncertainties. Then, the dynamic surface control technique is applied to the continuous characteristic model. The proposed IGC scheme guarantees the line-of-sight angular rates converge to an arbitrarily small neighbourhood of zero and all the closed-loop signals to be semi-globally uniformly ultimately bounded, which is proven using the Lyapunov stability theory. Finally, the effectiveness of… More >

Youquan Chen, Xinhui Liu, Xin Wang, Jinshi Chen

Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 613-622, 2018, DOI:10.31209/2018.100000028

Abstract In order to study the braking energy regeneration characteristics of the Frontmounted Parallel Hydraulic Hybrid Crane (FPHHC), the AMESim simulation models are established and analyzed by establishing the vehicle dynamics model and referencing to the actual data of the crane and physical hydraulic components, the simulation results are verified by road tests on the experimental prototype. The experiment results basically match with the simulation results. In the vehicle braking process, the hydraulic hybrid system of the experimental prototype can effectively recycle the vehicle braking energy, the energy recovery rate is up to 50.84%, and the energy-saving effect is obvious. The… More >

Kaijun Xu¹, Xueting Chen², Yusheng Yao¹, Shanshan Li¹

Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 603-611, 2018, DOI:10.31209/2018.100000027

Abstract The lateral conflict risk assessment of low-altitude training airspace strategic planning, which is based on the TSE errors has always been a difficult task for training flight research. In order to effectively evaluate the safety interval and lateral collision risk in training airspace, in this paper, TSE error performance using a weakly supervised learning method was modelled. First, the lateral probability density function of TSE is given by using a multidimensional random variable covariance matrix, and the risk model of a training flight lateral collision based on TSE error is established. The lateral conflict risk in specific training airspace is… More >

MengYuan Chen^1,2

Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 593-602, 2018, DOI:10.31209/2018.100000026

Abstract With the increasing number of feature points of a map, the dimension of systematic observation is added gradually, which leads to the deviation of the volume points from the desired trajectory and significant errors on the state estimation. An Iterative Squared-Root Cubature Kalman Filter (ISR-CKF) algorithm proposed is aimed at improving the SR-CKF algorithm on the simultaneous localization and mapping (SLAM). By introducing the method of iterative updating, the sample points are re-determined by the estimated value and the square root factor, which keeps the distortion small in the highly nonlinear environment and improves the precision further. A robust tracking… More >

Huanyu Zhao, Guoqiang Wang, Shuai Wang, Ruipeng Yang, He Tian, Qiushi Bi

Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 581-592, 2018, DOI:10.31209/2018.100000025

Abstract Articulated tracked vehicles have high mobility and steering performance. The unique structure of articulated tracked vehicles can avoid the subsidence of tracks caused by high traction from instantaneous braking and steering. In order to improve the accuracy of the steady-state steering of the articulated tracked vehicle, the velocity of both sides of the track and the deflection angle of the articulated point need to match better to achieve the purpose of steering accurately and reduce energy consumption and wear of components. In this study, a virtual prototype model of the articulated tracked vehicle is established based on the multi-body dynamic… More >

Dayong Yu

Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 571-580, 2018, DOI:10.31209/2018.100000024

Abstract In the application of a semi-physical simulation system of a space docking mechanism, the simulation precision is determined by pose accuracy of the parallel manipulator. In order to improve pose accuracy, an effective kinematic calibration method is presented to enable the full set of kinematic parameter errors to be estimated by measuring the docking mechanism’s poses. A new calibration model that takes into account geometrical parameter errors and coordinates transformation errors is derived by using a differential geometry method. Based on the calibration model, an iterative least square algorithm is utilized to calculate the above errors. Simulation and experimental results… More >