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 >

Wei Li^{1, 2, 3}, Min Zhou^{1, *}, Hairong Dong¹

Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 531-538, 2020, DOI:10.32604/iasc.2020.013930

Abstract Different types of stations have different functional roles in the urban rail transit network. Firstly, based on the characteristics of the urban rail transit network structure, the time series features and passenger flow features of the station smart card data are extracted. Secondly, we use the principal component analysis method to select the suitable clustering variables. Finally, we propose a station classification model based on the two-step cluster method. The effectiveness of the proposed method is verified in the Beijing subway. The results show that the proposed model can successfully identify the types of urban More >

Ping Wang¹ HongGuo Cai^2,*, 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 >

Arun Kumar Sangaiah^1,*, Ford Lumban Gaol², Krishn K. Mishra³

Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 515-517, 2020, DOI:10.32604/iasc.2020.013928

Abstract This article has no abstract. More >

Fu-I Chou¹, Wen-Hsien Ho^2,3, Chiu-Hung Chen^4,*

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 >

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 >

R. Uma Maheswari^1,*, 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 >

L. Ezhilarasi^1,*, A.P. Shanthi², V. Uma Maheswari¹

Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 465-478, 2020, DOI:10.32604/iasc.2020.013923

Abstract Development of new Artificial Intelligence related data analy sis methodologies w ith rev olutionary information technology has made a radical change in prediction, forecasting, and decision making for real-w orld data. The challenge arises w hen the real w orld dataset consisting of v oluminous data is uncertain. The rough set is a mathematical formalism that has emerged significantly for uncertain datasets. It represents the know ledge of the datasets as decision rules. It does not need any metadata. The rules are used to predict or classify unseen ex amples. The objectiv e of this… More >

Gulsah Karaduman^*, Mehmet Karakose, Ilhan Aydin, Erhan Akin

Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 455-463, 2020, DOI:10.32604/iasc.2020.013922

Abstract The use of railways has continually increased with high-speed trains. The increased speed and usage wear on the rails poses a serious problem. In recent years, to detect wear and cracks in the rails, image-based detection methods have been developed. In this paper, wears on the surface of railheads are detected by contactless image processing and image analysis techniques. The shadow removal algorithm with a minimal entropy method is implemented onto the noise-free images to eliminate the light variations that can occur on the rail. The Hough transform is applied on the noise and shadow More >

Mehiar, D.A.F., Azizul, Z.H.^*, Loo, C.K.

Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 447-454, 2020, DOI:10.32604/iasc.2020.013921

Abstract In this paper we show how the quantum-based particle swarm optimization (QPSO) method is adopted to derive a new derivation for robotics application in search and rescue simulations. The new derivation, called the Quantum Robot Darwinian PSO (QRDPSO) is inspired from another PSO-based algorithm, the Robot Darwinian PSO (RDPSO). This paper includes comprehensive details on the QRDPSO formulation and parameters control which show how the swarm overcomes communication constraints to avoid obstacles and achieve optimal solution. The results show the QRDPSO is an upgrade over RDPSO in terms of convergence speed, trajectory control, obstacle avoidance More >