Open Access

ARTICLE

Abayomi-Alli A.¹, Misra S.^2,3, Fernández-Sanz L.⁴, Abayomi-Alli O.^2,*, Edun A. R.¹
Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 385-396, 2020, DOI:10.32604/iasc.2020.013915
Abstract University timetable scheduling is a complicated constraint problem because educational institutions use timetables to maximize and optimize scarce resources, such as time and space. In this paper, an examination timetable system using Genetic Algorithm and Tabu Search memory with course sandwiching (GAT_CS), was developed for a large public University. The concept of Genetic Algorithm with Selection and Evaluation was implemented while the memory properties of Tabu Search and course sandwiching replaced Crossover and Mutation. The result showed that GAT_CS had hall allocation accuracies of 96.07% and 99.02%, unallocated score of 3.93% and 0.98% for first More >

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ARTICLE

Deisy Chaves^1,5,*, Maria Trujillo¹, Edward Garcia², Juan Barraza², Edward Lester³, Maribel Barajas⁴, Billy Rodriguez⁴, Manuel Romero⁴, Laura Fernández-Robles⁵
Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 397-405, 2020, DOI:10.32604/iasc.2020.013916
Abstract Precise automated determination of char morphologies formed by coal during combustion can lead to more efficient industrial control systems for coal combustion. Commonly, char particles are manually classified following the ICCP decision tree which considers four morphological features. One of these features is unfused material, and this class of material not characteristic of Colombian coals. In this paper, we propose new machine learning algorithms to classify the char particles in an image based system. Our hypothesis is that supervised classification methods can outperform the 4 ‘class’ ICCP criteria. In this paper we evaluate several morphological More >

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ARTICLE

Ti-Hung Chen¹, Ming-Feng Yeh^2,*
Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 407-420, 2020, DOI:10.32604/iasc.2020.013917
Abstract On the basis of JADE (adaptive differential evolution with optional external archive) and the modified differential evolution with p-best crossover (MDE_pBX), this study attempts to propose a modified mutation strategy termed "DE/(pbest)/1" for the differential evolution (DE) algorithm, where “(pbest)” represents the mean of p top-best vectors. Two modified parameter adaptation mechanisms are also proposed to update the crossover rate and the scale factor, respectively, in an adaptive manner. The DE variant with the proposed mutation strategy and two modified adaptation mechanisms is termed adaptive differential evolution with mean-of-pbest mutation strategy, denoted by ADE_pBM is comparable to or More >

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ARTICLE

Lihua Guo^*
Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 421-427, 2020, DOI:10.32604/iasc.2020.013918
Abstract Compared with deep neural learning, the extreme learning machine (ELM) can be quickly converged without iteratively tuning hidden nodes. Inspired by this merit, an extreme learning machine with elastic net regularization (ELM-EN) is proposed in this paper. The elastic net is a regularization method that combines LASSO and ridge penalties. This regularization can keep a balance between system stability and solution's sparsity. Moreover, an excellent optimization method, i.e., accelerated proximal gradient, is used to find the minimum of the system optimization function. Various datasets from UCI repository and two facial expression image datasets are used More >

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ARTICLE

T. Zhang^1,2, D. G. Zhang^1,2,*, X. H. Liu^1,2, C. L. Gong^1,2
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 >

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ARTICLE

Divneet Singh Kapoor^1,*, Amit Kumar Kohli²
Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 439-446, 2020, DOI:10.32604/iasc.2020.013920
Abstract This research paper represents an intelligent receiver based on the artificial-neuralnetworks (ANNs) for a 4x1 space-frequency-block-coded orthogonal-frequencydivision-multiplexing (SFBC-OFDM) system, working under slow time-varying frequency-selective fading channels. The proposed equalizer directly recovers transmitted symbols from the received signal, without the explicit requirement of the channel estimation. The ANN based equalizer is modelled by using feedforward as well as the recurrent neural-network (NN) architectures, and is trained using error backpropagation algorithms. The major focus is on efficiency and efficacy of three different strategies, namely the gradient-descent with momentum (GDM), resilient-propagation (RProp), and Levenberg-Marquardt (LM) algorithms. The recurrent More >

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ARTICLE

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 >

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ARTICLE

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 >

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ARTICLE

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 >

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ARTICLE

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 >

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ARTICLE

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 >

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ARTICLE

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 >

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EDITORIAL

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 >

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ARTICLE

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 >

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ARTICLE

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 >

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ARTICLE

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 >

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ARTICLE

Fan Bingxu^*
Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 549-555, 2020, DOI:10.32604/iasc.2020.013932
Abstract Poverty alleviation has always been the focus of China's work. According to the survey, the poverty population in rural areas has been reduced to a large extent, and the unemployed have had the lowest historical record in history. Big data technology is a new technology that has slowly emerged in recent years. The use of big data technology to create a visual platform for rural poverty alleviation is a relatively new idea at this stage. And we use the Map-reducebased big data missing value filling algorithm, which is designed to solve the data loss phenomenon More >

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1406

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ARTICLE

Chun Di^*
Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 557-567, 2020, DOI:10.32604/iasc.2020.013934
Abstract In response to the rapidly changing market environment and adapting to many impacts such as political, economic and technological conditions, supply chain managers are increasingly demanding a high-speed and efficient way to adjust the design to optimize the supply chain structure. In order to facilitate the participating companies in the supply chain to quickly and effectively implement the supply chain design optimization strategy, improve the competitiveness of enterprises and the ability of the entire supply chain to resist risks. Enterprises have gradually reduced the space for enhancing the competitive advantage by reducing raw material consumption,… More >

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ARTICLE

Shuangying Liu¹, Weidong Zhang^2,*
Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 569-575, 2020, DOI:10.32604/iasc.2020.013935
Abstract The constant development of computer technology has greatly facilitated our life. In the past, the agricultural products trade and agricultural products business model were an offline development, through face-to-face transactions. However, with the continuous application of Internet technology, we also have a new exploration on the e-commerce path of agricultural products. The fuzzy neural network algorithm was used to study the electronic commerce path of agricultural products and helped us to carry out the exploration computation of the electronic commerce path of agricultural products. And good calculation results have been obtained. Through our testing of More >

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ARTICLE

Linlin Zhang^*
Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 577-583, 2020, DOI:10.32604/iasc.2020.013936
Abstract The change of entrepreneurial social relations will have a negative impact on the enterprise performance. There is a significant positive correlation between the change of entrepreneurs' social relations and the negative impact of corporate performance. In order to reduce the negative impact of the social relationship of entrepreneurs and improve the profitability of the enterprises, a communication model of the entrepreneur social relationship change and the negative influence of the enterprise performance is proposed based on the closeness decision. The communication model of the negative impact of the enterprise performance and the enterprise performance are… More >

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ARTICLE

Shaoyun Long^1,*, Qianying Long²
Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 585-595, 2020, DOI:10.32604/iasc.2020.013937
Abstract The traditional factor analysis models, such as the generalized linear regression model and the gistic regression model have disadvantages of large standard error of analysis results. For this purpose, a multilevel factor analysis model based on time series and independent variable data is designed. The OLS estimation analysis method is used to establish the basic environment form, to derive the model calculation parameters and to complete the environment construction of the multilevel analysis model. On the basis of the construction environment, the double-level environment reference module and the multilevel factor analysis module are designed to More >

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ARTICLE

Meng Wei^*, Ningxin Zhang, Yuan Tong, Yu Song
Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 597-607, 2020, DOI:10.32604/iasc.2020.013938
Abstract The traditional radar signal detection mode of the analog digital converter (ADC) has a low prediction efficiency. Therefore, the advanced prediction model of the tunnel geological radar based on the cluster computing was designed. The completeness factor of the detection radar signal was calculated by the computer cluster effect, and then the information extraction and information integration of the radar pulse for the radar detection signal was determined. Moreover, the multi-order nonlinear regression forecasting model restructured the received signal. Thus, the prediction of the radar detection signal was achieved. In order to ensure the effectiveness More >

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ARTICLE

Hao Peng^*, Qiao Li
Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 609-616, 2020, DOI:10.32604/iasc.2020.013939
Abstract This paper represents a neural network model for the Web page information extraction based on the depth learning technology, and implements the model algorithm using the TensorFlow system. We then complete a detailed experimental analysis of the information extraction effect of Web pages on the same website, then show statistics on the accuracy index of the page information extraction, and optimize some parameters in the model according to the experimental results. On the premise of achieving ideal experimental results, an algorithm for migrating the model to the same pages of other websites for information extraction… More >

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ARTICLE

Fanxiu Dong^*
Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 617-624, 2020, DOI:10.32604/iasc.2020.013940
Abstract At present, the allocation of the medical service resources is directed at a single service resource, and there are many unreasonable problems, which causes medical cost to be high. Based on this, the application of the DRGs and the fuzzy demand in the medical service resource allocation based on the data mining algorithm is proposed. The application research of the DRGs and the data mining algorithm is simply analyzed, then the uncertain demand estimation is applied to the fuzzy demand processing based on the fuzzy demand theory and the medical service resources are configured under More >

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ARTICLE

Zhenhua Guo^1,2, Lixin Zhang^1,*, Xue Hu¹, Huanmei Chen²
Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 625-630, 2020, DOI:10.32604/iasc.2020.013941
Abstract Wind speed prediction is an important part of the wind farm management and wind power grid connection. Having accurate prediction of short-term wind speed is the basis for predicting wind power. This paper proposes a short-term wind speed prediction strategy based on the wavelet analysis and the multilayer perceptual neural network for the Dabancheng area, in China. Four wavelet neural network models using the Morlet function as the wavelet basis function were developed to forecast short-term wind speed in January, April, July, and October. Predicted wind speed was compared across the four models using the More >

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ARTICLE

Qiming Zou¹, Ling Wang^{1, *}, Jie Liu¹, Yingtao Jiang²
Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 631-639, 2020, DOI:10.32604/iasc.2020.012549
Abstract The real-time requirements imposed on a feedback control system are often hard to be met, as the controller spends a disproportionately large amount of time waiting for a control cycle to reach its final state. When such a final state is established, multiple tasks have to be prioritized and launched altogether simultaneously, and the system is given an extremely short time window to generate its output. This huge gap between the wait and action times, perceived as a load unbalancing problem, hinders a control decision to be made in real time. To address this challenging… More >

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