Journals / IASC / Vol.24, No.3

  • ARTICLE

    Structure from Motion Using Bio-Inspired Intelligence Algorithm and Conformal Geometric Algebra

    Nancy Arana-Daniel, Carlos Villaseñor, Carlos López-Franco, Alma Y. Alanís, Roberto Valencia-Murillo
    Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 461-467, 2018, DOI:10.1080/10798587.2017.1299356
    Abstract Structure from Motion algorithms offer good advantages, such as extract 3D information in monocular systems and structures estimation as shown in Hartley & Zisserman for numerous applications, for instance; augmented reality, autonomous navigation, motion capture, remote sensing and object recognition among others. Nevertheless, this algorithm suffers some weaknesses in precision. In the present work, we extent the proposal in Arana-Daniel, Villaseñor, López-Franco, & Alanís that presents a new strategy using bio-inspired intelligence algorithm and Conformal Geometric Algebra, based in the object mapping paradigm, to overcome the accuracy problem in two-view Structure form motion algorithms. For this instance, we include two… More >

  • ARTICLE

    Comparison of Local Descriptors for Humanoid Robots Localization Using a Visual Bag of Words Approach

    Noé G. Aldana-Murillo, Jean-Bernard Hayet, Héctor M. Becerra
    Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 471-481, 2018, DOI:10.1080/10798587.2017.1304508
    Abstract In this paper, we address the problem of the appearance-based localization of a humanoid robot, in the context of robot navigation. We only use information obtained by a single sensor, in this case the camera mounted on the robot. We aim at determining the most similar image within a previously acquired set of key images (also referred to as a visual memory) to the current view of the monocular camera carried by the robot. The robot is initially kidnapped and the current image has to be compared with the visual memory. To solve this problem, we rely on a hierarchical… More >

  • ARTICLE

    Application of Multi Agent Systems in Automation of Distributed Energy Management in Micro-grid using MACSimJX

    Leo Rajua, R. S. Miltonb, Senthilkumaran Mahadevana
    Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 483-491, 2018, DOI:10.1080/10798587.2017.1305647
    Abstract The objective of this paper is to monitor and control a micro-grid model developed in MATLABSimulink through Multi Agent System (MAS) for autonomous and distributed energy management. Since MATLAB/Simulink is not compatible with parallel operations of MAS, MAS operating in Java Agent Development Environment (JADE) is linked with MATLAB/Simulink through Multi Agent Control using Simulink with Jade extension (MACSimJX). This allows the micro-grid system designed with Simulink to be controlled by MAS for realizing the advantages of MAS in distributed and decentralized microgrid systems. JADE agents receive environmental information through Simulink and they coordinate to take best possible action, which… More >

  • ARTICLE

    Highly Accurate Recognition of Handwritten Arabic Decimal Numbers Based on a Self-Organizing Maps Approach

    Amin Alqudah1,2, Hussein R. Al-Zoubi2, Mahmood A. Al-Khassaweneh2,3, Mohammed Al-Qodah1
    Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 493-505, 2018, DOI:10.31209/2018.100000005
    Abstract Handwritten numeral recognition is one of the most popular fields of research in automation because it is used in many applications. Indeed, automation has continually received substantial attention from researchers. Therefore, great efforts have been made to devise accurate recognition methods with high recognition ratios. In this paper, we propose a method for integrating the correlation coefficient with a Self-Organizing Maps (SOM)-based technique to recognize offline handwritten Arabic decimal digits. The simulation results show very high recognition rates compared with the rates achieved by other existing methods. More >

  • ARTICLE

    Synthesis Optimization of Piezo Driven Four Bar Mechanism Using Genetic Algorithm

    Laith Sawaqed1, Khaled S. Hatamleh1,2, Mohammad A. Jaradat1,2, Qais Khasawneh1,3
    Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 507-515, 2018, DOI:10.31209/2018.100000039
    Abstract Over the past few years, there has been a growing demand to develop efficient precision mechanisms for fine moving applications. Therefore, several piezoelectric driven mechanisms have been proposed for such applications. In this work an optimal synthesis of a four-bar mechanism with three PEAs is proposed. Two evolutionary multi-objective Genetic Algorithms (GAs) are formulated and applied; A Genetic Algorithm Synthesis method (GAS) is first used to obtain a synthesis solution for the mechanism regardless of power consumption. Then another Genetic Algorithm Minimum Power Synthesis method (GAMPS) is used to obtain the synthesis solution of minimum power consumption. For that purpose,… More >

  • EDITORIAL

    Special Issue on Machine Learning and Data Mining for Cyber-Physical Systems

    Zheng Xu, Zhiguo Yan
    Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 517-518, 2018, DOI:10.31209/2018.100000018
    Abstract This article has no abstract. More >

  • ARTICLE

    A User Authentication Protocol Combined with the Trust Model, Biometrics and ECC for Wireless Sensor Networks

    Tao Liu, Gan Huang*, Ping Zhang
    Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 519-529, 2018, DOI:10.31209/2018.100000019
    Abstract In this article, a new user authentication protocol using trust model, elliptic curve cryptography and biometrics for WSNs is submitted. The result of the trust model analysis indicates that the model can improve the model’s ability of withstanding attacks from the malicious nodes. The results of safety analysis and performance analysis for our proposed user authentication protocol demonstrate that this protocol can be flexible to all sorts of common known attacks and performs similarly or better compared with some active user authentication protocols. It is suitable for WSNs which have a prominent request for the security and the performance. More >

  • ARTICLE

    The Machine Learning Based Finite Element Analysis on Road Engineering of Built-in Carbon Fiber Heating Wire

    Yuhua Penga, Dingyue Chena, Lihao Chenb, Jiayu Yub, Mengjie Baoa
    Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 531-539, 2018, DOI:10.31209/2018.100000020
    Abstract For the study of the effect of deicing with carbon fiber heating wire in the bridge pavement structure, through built-in carbon fiber heating wire in the bridge pavement structure, experimental studies were carried out indoor on the effects of thermal conductivity in different embedding positions, layout spacing and the installs power of carbon fiber heating wire. With indoor laboratory test data as the basic parameters, using ABAQUS finite element software simulation, an analysis was carried out of the degree that the surface temperature of the heating wire, the thermal physical parameters of asphalt concrete, and environmental conditions have influence on… More >

  • ARTICLE

    Delay-dependent Stability of Recurrent Neural Networks with Time-varying Delay

    Guobao Zhanga,b, Jing-Jing Xionga,b, Yongming Huanga,b, Yong Lua,b,c, Ling Wanga,b
    Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 541-551, 2018, DOI:10.31209/2018.100000021
    Abstract This paper investigates the delay-dependent stability problem of recurrent neural networks with time-varying delay. A new and less conservative stability criterion is derived through constructing a new augmented Lyapunov-Krasovskii functional (LKF) and employing the linear matrix inequality method. A new augmented LKF that considers more information of the slope of neuron activation functions is developed for further reducing the conservatism of stability results. To deal with the derivative of the LKF, several commonly used techniques, including the integral inequality, reciprocally convex combination, and free-weighting matrix method, are applied. Moreover, it is found that the obtained stability criterion has a lower… More >

  • ARTICLE

    A Computable General Equilibrium Model Based Simulation on Water Conservancy Investment

    JUN WANG
    Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 553-561, 2018, DOI:10.31209/2018.100000022
    Abstract The water conservancy industry is one of the oldest fundamental industries in human history with high attention all the time, which is a vital factor to national well-being and people’s livelihood. The “Five Water Governance” is one of important strategies as a breakthrough to force transforming and upgrading for ecological water conservancy and sustainable development. A regional dynamic CGE model was constructed to simulate and analyze the short-term and longterm influence of the water conservancy investment to water conservancy industry itself, other national economy sectors and macro economy, so as to provide scientific proof for policy-making of water conservancy, and… More >

  • ARTICLE

    Optimal Learning Slip Ratio Control for Tractor-semitrailer Braking in a Turn based on Fuzzy Logic

    Jinsong Donga, Hongwei Zhanga, Ronghui Zhangb,*, Xiaohong Jinc, Fang Chend
    Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 563-570, 2018, DOI:10.31209/2018.100000023
    Abstract The research on braking performance a of tractor-semitrailer is a hard and difficult point in the field of vehicle reliability and safety technology. In this paper, the tire braking model and the dynamic characteristic model of the brake torque with the variable of the controlling air pressure were established. We also established a nonlinear kinematic model of the tractor-semitrailer when it brakes on a curve. The parameters and variables of the model were measured and determined by the road experiment test. The optimal control strategy for the tractor-semitrailer based on the optimal slipping ratio was proposed. Then the PID controller… More >

  • ARTICLE

    Kinematic Calibration of a Parallel Manipulator for a Semi-physical Simulation System

    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 >

  • ARTICLE

    The Virtual Prototype Model Simulation on the Steady-state Machine Performance

    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 >

  • ARTICLE

    The SLAM Algorithm for Multiple Robots Based on Parameter Estimation

    MengYuan Chen1,2
    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 >

  • ARTICLE

    The Lateral Conflict Risk Assessment for Low-altitude Training Airspace Using Weakly Supervised Learning Method

    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 >

  • ARTICLE

    Simulation and Data Analysis of Energy Recovery Sensing on a Parallel Hydraulic Hybrid Crane

    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 >

  • ARTICLE

    Intelligent Control for Integrated Guidance and Control Based on the Intelligent Characteristic Model

    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 >

  • ARTICLE

    NARX Network Based Driver Behavior Analysis and Prediction Using Time-series Modeling

    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 >

  • ARTICLE

    The Data Analyses of a Vertical Storage Tank Using Finite Element SOFT Computing

    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 >

  • ARTICLE

    Association Link Network Based Concept Learning in Patent Corpus

    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 >

  • ARTICLE

    Multi-phase Oil Tank Recognition for High Resolution Remote Sensing Images

    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 >

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