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 and second
semesters, respectively. It… More >
Open Access
ARTICLE
Deisy Chaves1,5,*, 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 features and specifically assess the… More >
Open Access
ARTICLE
Ti-Hung Chen1, Ming-Feng Yeh2,*
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 better than… More >
Open Access
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 to validate the efficiency of… More >
Open Access
ARTICLE
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 order to assess the
performance… More >
Open Access
ARTICLE
Divneet Singh Kapoor1,*, 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 neural network architecture based SFBC-OFDM… More >
Open Access
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 and connectivity
performance of the… More >
Open Access
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 free image in order to… More >
Open Access
ARTICLE
L. Ezhilarasi1,*, 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 research is to dev elop… More >
Open Access
ARTICLE
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 order statistical moments, signal feature… More >
Open Access
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 to reduce external interference, improve… More >
Open Access
ARTICLE
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 problems in a genetic association… More >
Open Access
EDITORIAL
Arun Kumar Sangaiah1,*, 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 >
Open Access
ARTICLE
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 to practical intelligent translation software. More >
Open Access
ARTICLE
Wei Li1, 2, 3, Min Zhou1, *, 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 rail transit stations, clarify the… More >
Open Access
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 market segment have been proposed… More >
Open Access
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 in the query process. It… More >
Open Access
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, labor costs and increasing production… More >
Open Access
ARTICLE
Shuangying Liu1, Weidong Zhang2,*
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 the fuzzy neural network
algorithm,… More >
Open Access
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 analyzed. In the
perspective of… More >
Open Access
ARTICLE
Shaoyun Long1,*, 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 realize the design of the… More >
Open Access
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 of the design, the simulation… More >
Open Access
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 is proposed, and the experimental… More >
Open Access
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
the established demand satisfaction rate.… More >
Open Access
ARTICLE
Zhenhua Guo1,2, Lixin Zhang1,*, 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 mean square error and regression.… More >
Open Access
ARTICLE
Qiming Zou1, Ling Wang1, *, 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 problem, in this paper, we… More >
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