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  • Open Access

    ARTICLE

    Improvement of the Economic Management System Based on the Publicity of Railway Transportation Products

    Bai Yan*

    Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 539-547, 2020, DOI:10.32604/iasc.2020.013931

    Abstract The traditional view is that due to the natural monopoly and external publicity of the railway transportation, the economic regulation should have been implemented. However, due to the inaccurate grasp of the technical and economic characteristics of various components in the system and the current social and economic situation in China, the economic regulation has been implemented for a long time. Based on a detailed analysis of the characteristics of the railway transportation infrastructure and the market characteristics of the road transportation products, combined with China's actual national conditions, the economic regulation schemes for each… More >

  • Open Access

    ARTICLE

    Design of Intelligent English Translation Algorithms Based on a Fuzzy Semantic Network

    Ping Wang1 HongGuo Cai2,*, LuKun Wang3

    Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 519-529, 2020, DOI:10.32604/iasc.2020.013929

    Abstract In order to improve the quality of intelligent English translation, an intelligent English translation algorithm based on the fuzzy semantic network is designed. By calculating the distance of fuzzy semantic network, classifying and ordering the English semantics to determine the optimal similarity and outputting the optimal translation results, the experiments show the average BLEU and NIST of the three test sets are 25.85 and 5.8925 respectively. The translation accuracy is higher than 95%. The algorithm can translate 246 Chinese sentences per second. This shows it is a high-performance intelligent translation algorithm and can be applied More >

  • Open Access

    ARTICLE

    Niche Genetic Algorithm for Solving Multiplicity Problems in Genetic Association Studies

    Fu-I Chou1, Wen-Hsien Ho2,3, Chiu-Hung Chen4,*

    Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 501-512, 2020, DOI:10.32604/iasc.2020.013926

    Abstract This paper proposes a novel genetic algorithm (GA) that embeds a niche competition strategy (NCS) in the evolutionary flow to solve the combinational optimization problems that involve multiple loci in the search space. Unlike other niche-information based algorithms, the proposed NCSGA does not need prior knowledge to design niche parameters in the niching phase. To verify the solution capability of the new method, benchmark studies on both the travelling salesman problem (TSP) and the airline recovery scheduling problem were first made. Then, the proposed method was used to solve single nucleotide polymorphism (SNP) barcodes generation More >

  • Open Access

    ARTICLE

    The Design of a TLD and Fuzzy-PID Controller Based on the Autonomous Tracking System for Quadrotor Drones

    Pi-Yun Chen, Guan-Yu Chen*

    Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 489-500, 2020, DOI:10.32604/iasc.2020.013925

    Abstract The objective of this paper is to design a new Quadrotor Autonomous Following System, and the main three contents are as follows: Object tracking, quadrotor attitude determination and the controller. The image tracking portion performs object detection and keeps tracking by way of the Tracking-Learning-Detection (TLD), and gets the information of the target motion estimation positions. The attitude determination of the Quadrotor has adopted the Inertial Navigation System and sensors of the accelerometer, gyroscope and electronic compass, etc. for retrieving the information. The Kalman filter is also utilized for estimating the current values in order More >

  • Open Access

    ARTICLE

    Wind Turbine Drivetrain Expert Fault Detection System: Multivariate Empirical Mode Decomposition based Multi-sensor Fusion with Bayesian Learning Classification

    R. Uma Maheswari1,*, R. Umamaheswari2

    Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 479-488, 2020, DOI:10.32604/iasc.2020.013924

    Abstract To enhance the predictive condition-based maintenance (CBMS), a reliable automatic Drivetrain fault detection technique based on vibration monitoring is proposed. Accelerometer sensors are mounted on a wind turbine drivetrain at different spatial locations to measure the vibration from multiple vibration sources. In this work, multi-channel signals are fused and monocomponent modes of oscillation are reconstructed by the Multivariate Empirical Mode Decomposition (MEMD) Technique. Noise assisted methodology is adapted to palliate the mixing of modes with common frequency scales. The instantaneous amplitude envelope and instantaneous frequency are estimated with the Hilbert transform. Low order and high More >

  • Open Access

    ARTICLE

    A Novel WSN-Oriented Locating Approach Based on Density

    T. Zhang1,2, D. G. Zhang1,2,*, X. H. Liu1,2, C. L. Gong1,2

    Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 429-437, 2020, DOI:10.32604/iasc.2020.013919

    Abstract It is known that the locating accuracy of the traditional Distance Vector-HOP (DV-HOP) approach in a Wireless Sensor Network (WSN) depends on the density of the anchor node. A novel WSN-oriented locating approach based on a node's density is proposed in this paper. The approach can compute the distance of the node based on the maximum likelihood estimation strategy. It can improve the accuracy ratio of the measuring distance among the nodes. The relative nodes of a WSN can find the average hop distances by estimating the distances from themselves to their circular nodes. In More >

  • Open Access

    ARTICLE

    Intelligent Speech Communication Using Double Humanoid Robots

    Li-Hong Juang1,*, Yi-Hua Zhao2

    Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 291-301, 2020, DOI:10.31209/2020.100000164

    Abstract Speech recognition is one of the most convenient forms of human beings engaging in the exchanging of information. In this research, we want to make robots understand human language and communicate with each other through the human language, and to realize man–machine interactive and humanoid– robot interactive. Therefore, this research mainly studies NAO robots’ speech recognition and humanoid communication between double -humanoid robots. This paper introduces the future direction and application prospect of speech recognition as well as its basic method and knowledge of speech recognition fields. This research also proposes the application of the… More >

  • Open Access

    ARTICLE

    Identification and Segmentation of Impurities Accumulated in a Cold-Trap Device by Using Radiographic Images

    Thamotharan B1,*, Venkatraman B2, Chandrasekaran S3

    Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 335-340, 2020, DOI:10.31209/2019.100000156

    Abstract Accumulation of impurities within cold trap device results in degradation of efficient performance in a nuclear reactor systems. The impurities have to be identified and the device has to be replaced periodically based on the accumulation level. Though there are a few techniques available to identify these impurities from the cold trap device, there are certain limitations in these techniques. In order to overcome these constraints, a new harmless and easy approach for identifying and separating the impurities using the radiographic images of cold traps is proposed in this paper. It includes a new segmentation More >

  • Open Access

    ARTICLE

    Robust Visual Tracking Models Designs Through Kernelized Correlation Filters

    Detian Huang1, Peiting Gu2, Hsuan-Ming Feng3,*, Yanming Lin1, Lixin Zheng1

    Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 313-322, 2020, DOI:10.31209/2019.100000105

    Abstract To tackle the problem of illumination sensitive, scale variation, and occlusion in the Kernelized Correlation Filters (KCF) tracker, an improved robust tracking algorithm based on KCF is proposed. Firstly, the color attribute was introduced to represent the target, and the dimension of target features was reduced adaptively to obtain low-dimensional and illumination-insensitive target features with the locally linear embedding approach. Secondly, an effective appearance model updating strategy is designed, and then the appearance model can be adaptively updated according to the Peak-to-Sidelobe Ratio value. Finally, the low-dimensional color features and the HOG features are utilized More >

  • Open Access

    ARTICLE

    LSTM Neural Network for Beat Classification in ECG Identity Recognition

    Xin Liu1,*, Yujuan Si1,2, Di Wang1

    Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 341-351, 2020, DOI:10.31209/2019.100000104

    Abstract As a biological signal existing in the human living body, the electrocardiogram (ECG) contains abundantly personal information and fulfils the basic characteristics of identity recognition. It has been widely used in the field of individual identification research in recent years. The common process of identity recognition includes three steps: ECG signals preprocessing, feature extraction and processing, beat classification recognition. However, the existing ECG classification models are sensitive to limitations of database type and extracted features dimension, which makes classification accuracy difficult to improve and cannot meet the needs of practical applications. To tackle the problem,… More >

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