CMES-Computer Modeling in Engineering & Sciences

ISSN: 1526-1492 (print) Impact Factor: 0.805
ISSN: 1526-1506 (online) Publication Frequency: Monthly

About the Journal

This journal publishes original research papers of reasonable permanent value, in the areas of computational mechanics, computational physics, computational chemistry, and computational biology, pertinent to solids, fluids, gases, biomaterials, and other continua. Various length scales (quantum, nano, micro, meso, and macro), and various time scales (picoseconds to hours) are of interest. Papers which deal with multi-physics problems, as well as those which deal with the interfaces of mechanics, chemistry, and biology, are particularly encouraged. New computational approaches, and more efficient algorithms, which eventually make near-real-time computations possible, are welcome. Original papers dealing with new methods such as meshless methods, and mesh-reduction methods are sought.

Indexing and Abstracting

Science Citation Index (Web of Science): 2019 Impact Factor 0.805; Current Contents: Engineering, Computing & Technology; Scopus Citescore (Impact per Publication 2019): 1.0; SNIP (Source Normalized Impact per Paper 2019): 0.499; RG Journal Impact (average over last three years); Engineering Index (Compendex); Applied Mechanics Reviews; Cambridge Scientific Abstracts: Aerospace and High Technology, Materials Sciences & Engineering, and Computer & Information Systems Abstracts Database; CompuMath Citation Index; INSPEC Databases; Mathematical Reviews; MathSci Net; Mechanics; Science Alert; Science Navigator; Zentralblatt fur Mathematik; Portico, etc...

Current Issue - Vol.125, No.1, 2020 Most Viewed

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REVIEW
Nanomechanics and Ultrastructure of Bone: A Review
Mohammad Maghsoudi-Ganjeh, Xiaodu Wang^*, Xiaowei Zeng^*
CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 1-32, 2020, DOI:10.32604/cmes.2020.012123
Abstract In this review, a brief presentation is first given to the hierarchical structure and mechanical behavior of bone. Then, the recent advancements in nanoscale characterization of bone ultrastructure and ingredients are discussed based on an extensive quantity of references in the literature.Moreover, computational and analytical bone mechanics at ultrastructure levels are critically reviewed with the growing body of knowledge in the field. The computational and analytical models are summarized in several categories for ease of understanding bone nanomechanics and their applicability/limitations. This review is expected to provide a well-informed foundation for the researchers interested in interrogating the complex biomechanical response… More
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ARTICLE
Online AUV Path Replanning Using Quantum-Behaved Particle Swarm Optimization with Selective Differential Evolution
Hui Sheng Lim^1,*, Christopher K. H. Chin¹, Shuhong Chai¹, Neil Bose^1,2
CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 33-50, 2020, DOI:10.32604/cmes.2020.011648
Abstract This paper presents an online AUV (autonomous underwater vehicle) path planner that employs path replanning approach and the SDEQPSO (selective differential evolution-hybridized quantum-behaved particle swarm optimization) algorithm to optimize an AUV mission conducted in an unknown, dynamic and cluttered ocean environment. The proposed path replanner considered the effect of ocean currents in path optimization to generate a Pareto-optimal path that guides the AUV to its target within minimum time. The optimization was based on the onboard sensor data measured from the environment, which consists of a priori unknown dynamic obstacles and spatiotemporal currents. Different sensor arrangements for the forward-looking sonar… More
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ARTICLE
Modelling Strategy and Parametric Study of Metal Gaskets for Automotive Applications
Fabio Bruzzone, Cristiana Delprete, Carlo Rosso^*
CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 51-64, 2020, DOI:10.32604/cmes.2020.011023
Abstract This paper is focused on finite element simulation of cylinder head gaskets. Finite element codes support several methodologies, each of which has its own strengths and weaknesses. One of the key points lies in the influence of the gasket geometry on its final behaviour. Such a contribution can come from the detailed modelling of the gasket or by defining a global non-linear behaviour in which material and geometry non-linearities are summarised. Two approaches were used to simulate the gasket behaviour. The first one consists in using a 2D approach, which allows to model through-thickness non-linear behaviour of gasket. The second… More
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ARTICLE
Ziegler–Nichols Customization for Quadrotor Attitude Control under Empty and Full Loading Conditions
Ivan Paulo Canal^1,*, Manuel Martin Pérez Reimbold², Maurício de Campos²
CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 65-75, 2020, DOI:10.32604/cmes.2020.010741
Abstract An aircraft quadrotor is a complex control system that allows for great flexibility in flight. Controlling multirotor aerial systems such as quadrotors is complex because the variables involved are not always available, known, and accurate. The inclusion of payload changes the dynamic characteristics of the aircraft, making it necessary to adapt the control system for this situation. Among the various control methods that have been investigated, proportional-integralderivative (PID) control offers good results and simplicity of application; however, achieving stability and high performance is challenging, with the most critical task being tuning the controller gains. The Ziegler–Nichols (ZN) theory was used… More
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ARTICLE
Periodic Lattice Porous Structure Produced by Selective Laser Melting: Process, Experiment and Numerical Simulation Analysis
Jianrui Zhang^1,2, Min Chi¹, Bo Qian^1,*, Zhijun Qiu²
CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 77-94, 2020, DOI:10.32604/cmes.2020.010518
Abstract To accurately perform the coupled simulation of temperature field and stress field of complex parts and porous structures under the optimal manufacturing process parameters, three kinds of porous structures with different complexity were designed in this paper. Firstly, ANSYS additive software was used to conduct the stress/deformation simulation of the whole structure under different scanning strategies. Secondly, the optimal scanning strategy for different porous structures was determined, then the experimental preparation was performed, and mechanical properties of compression were tested and studied. The results show that the elastic modulus and yield strength increase with the increase of pole diameter/wall thickness.… More
Views:84 Downloads:63 Download PDF

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ARTICLE
Short-Term Traffic Flow Prediction Based on LSTM-XGBoost Combination Model
Xijun Zhang^*, Qirui Zhang
CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 95-109, 2020, DOI:10.32604/cmes.2020.011013
Abstract According to the time series characteristics of the trajectory history data, we predicted and analyzed the traffic flow. This paper proposed a LSTMXGBoost model based urban road short-term traffic flow prediction in order to analyze and solve the problems of periodicity, stationary and abnormality of time series. It can improve the traffic flow prediction effect, achieve efficient traffic guidance and traffic control. The model combined the characteristics of LSTM (Long Short-Term Memory) network and XGBoost (Extreme Gradient Boosting) algorithms. First, we used the LSTM model that increases dropout layer to train the data set after preprocessing. Second, we replaced the… More
Views:374 Downloads:131 Download PDF

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ARTICLE
Prediction of Intrinsically Disordered Proteins with a Low Computational Complexity Method
Jia Yang¹, Haiyuan Liu^1,*, Hao He²
CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 111-123, 2020, DOI:10.32604/cmes.2020.010347
Abstract The prediction of intrinsically disordered proteins is a hot research area in bio-information. Due to the high cost of experimental methods to evaluate disordered regions of protein sequences, it is becoming increasingly important to predict those regions through computational methods. In this paper, we developed a novel scheme by employing sequence complexity to calculate six features for each residue of a protein sequence, which includes the Shannon entropy, the topological entropy, the sample entropy and three amino acid preferences including Remark 465, Deleage/Roux, and Bfactor(2STD). Particularly, we introduced the sample entropy for calculating time series complexity by mapping the amino… More
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ARTICLE
Deep Residual Network Based on Image Priors for Single Image Super Resolution in FFA Images
G. R. Hemalakshmi^*, D. Santhi, V. R. S. Mani, A. Geetha, N. B. Prakash
CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 125-143, 2020, DOI:10.32604/cmes.2020.011331
Abstract Diabetic retinopathy, aged macular degeneration, glaucoma etc. are widely prevalent ocular pathologies which are irreversible at advanced stages. Machine learning based automated detection of these pathologies facilitate timely clinical interventions, preventing adverse outcomes. Ophthalmologists screen these pathologies with fundus Fluorescein Angiography Images (FFA) which capture retinal components featuring diverse morphologies such as retinal vasculature, macula, optical disk etc. However, these images have low resolutions, hindering the accurate detection of ocular disorders. Construction of high resolution images from these images, by super resolution approaches expedites the diagnosis of pathologies with better accuracy. This paper presents a deep learning network for Single… More
Views:90 Downloads:47 Download PDF

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ARTICLE
Simulation Analysis on Mechanical Property Characterization of Carbon Nanotubes Reinforced Epoxy Composites
Dan Li¹, Li Ding¹, Zhengang Liu², Qiang Li³, Kaiyun Guo¹, Hailin Cao^1,4,*
CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 145-171, 2020, DOI:10.32604/cmes.2020.010822
Abstract Carbon nanotube (CNT)-reinforced composites have ultra-high elastic moduli, low densities, and fibrous structures. This paper presents the multi-scale finite element modeling of CNT-reinforced polymer composites from micro- to macro-scales. The nanocomposites were modeled using representative volume elements (RVEs), and finite element code was written to simulate the modeling and loading procedure and obtain equivalent mechanical properties of the RVEs with various volume fractions of CNTs, which can be used directly in the follow-up simulation studies on the macroscopic model of CNT-reinforced nanocomposites. When using the programming to simulate the deformation and fracture process of the CNT-reinforced epoxy composites, the mechanical… More
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ARTICLE
The Efficient Finite Element Methods for Time-Fractional Oldroyd-B Fluid Model Involving Two Caputo Derivatives
An Chen^*
CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 173-195, 2020, DOI:10.32604/cmes.2020.011871
Abstract In this paper, we consider the numerical schemes for a timefractional Oldroyd-B fluid model involving the Caputo derivative. We propose two efficient finite element methods by applying the convolution quadrature in time generated by the backward Euler and the second-order backward difference methods. Error estimates in terms of data regularity are established for both the semidiscrete and fully discrete schemes. Numerical examples for two-dimensional problems further confirm the robustness of the schemes with first- and second-order accurate in time. More
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ARTICLE
A Novel Binary Firey Algorithm for the Minimum Labeling Spanning Tree Problem
Mugang Lin^1,2,*, Fangju Liu³, Huihuang Zhao^1,2, Jianzhen Chen^1,2
CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 197-214, 2020, DOI:10.32604/cmes.2020.09502
Abstract Given a connected undirected graph G whose edges are labeled, the minimum labeling spanning tree (MLST) problem is to find a spanning tree of G with the smallest number of different labels. The MLST is an NP-hard combinatorial optimization problem, which is widely applied in communication networks, multimodal transportation networks, and data compression. Some approximation algorithms and heuristics algorithms have been proposed for the problem. Firey algorithm is a new meta-heuristic algorithm. Because of its simplicity and easy implementation, it has been successfully applied in various fields. However, the basic firefly algorithm for the MLST problem is proposed in this… More
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ARTICLE
Exploring the Abnormal Brain Regions and Abnormal Functional Connections in SZ by Multiple Hypothesis Testing Techniques
Lan Yang¹, Shun Qi^2,3,#, Chen Qiao^1,*, Yanmei Kang¹
CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 215-237, 2020, DOI:10.32604/cmes.2020.010796
（This article belongs to this Special Issue: Data Science and Modeling in Biology, Health, and Medicine)
Abstract Schizophrenia (SZ) is one of the most common mental diseases. Its main characteristics are abnormal social behavior and inability to correctly understand real things. In recent years, the magnetic resonance imaging (MRI) technique has been popularly utilized to study SZ. However, it is still a great challenge to reveal the essential information contained in the MRI data. In this paper, we proposed a biomarker selection approach based on the multiple hypothesis testing techniques to explore the difference between SZ and healthy controls by using both functional and structural MRI data, in which biomarkers represent both abnormal brain functional connectivity and… More
Views:75 Downloads:66 Download PDF

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ARTICLE
Performance Analysis of Intelligent CR-NOMA Model for Industrial IoT Communications
Yinghua Zhang^1,2, Jian Liu¹, Yunfeng Peng¹, Yanfang Dong², Changming Zhao^3,*
CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 239-257, 2020, DOI:10.32604/cmes.2020.010778
（This article belongs to this Special Issue: Intelligent Models for Security and Resilience in Cyber Physical Systems)
Abstract Aiming for ultra-reliable low-latency wireless communications required in industrial internet of things (IIoT) applications, this paper studies a simple cognitive radio non-orthogonal multiple access (CR-NOMA) downlink system. This system consists of two secondary users (SUs) dynamically interfered by the primary user (PU), and its performance is characterized by the outage probability of the SU communications. This outage probability is calculated under two conditions where, a) the transmission of PU starts after the channel state information (CSI) is acquired, so the base station (BS) is oblivious of the interference, and b) when the BS is aware of the PU interference, and… More
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ARTICLE
Effect of Hole Density and Confining Pressure on Mechanical Behavior of Porous Specimens: An Insight from Discrete Element Modeling
Yuanchao Zhang¹, Zhiyuan Xia^2,*, Yujing Jiang¹, Miao Chen³, Jiankang Liu¹, Qian Yin⁴
CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 259-280, 2020, DOI:10.32604/cmes.2020.011076
（This article belongs to this Special Issue: Modeling and Simulation of Fluid flows in Fractured Porous Media: Current Trends and Prospects)
Abstract Hole-like defects are very common in natural rock or coal mass, and play an important role in the failure and mechanical behaviors of rock or coal mass. In this research, multi-holed coal specimens are constructed numerically and calibrated based on UDEC-GBM models. Then, the strength, deformation and failure behavior of the porous specimens are analyzed, with consideration of hole density (P) and confining pressure (σ₃). The simulation results are highly consistent with those available experiment results, and show that the compressive strength decreases exponentially with the increasing hole density. The strength loss is mainly caused by the reduction of cohesion… More
Views:434 Downloads:176 Download PDF

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ARTICLE
An Emotion Analysis Method Using Multi-Channel Convolution Neural Network in Social Networks
Xinxin Lu^1,*, Hong Zhang²
CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 281-297, 2020, DOI:10.32604/cmes.2020.010948
（This article belongs to this Special Issue: Recent Advances on Deep Learning for Medical Signal Analysis (RADLMSA))
Abstract As an interdisciplinary comprehensive subject involving multidisciplinary knowledge, emotional analysis has become a hot topic in psychology, health medicine and computer science. It has a high comprehensive and practical application value. Emotion research based on the social network is a relatively new topic in the field of psychology and medical health research. The text emotion analysis of college students also has an important research significance for the emotional state of students at a certain time or a certain period, so as to understand their normal state, abnormal state and the reason of state change from the information they wrote. In… More
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ARTICLE
Least-Square Support Vector Machine and Wavelet Selection for Hearing Loss Identi
Chaosheng Tang¹, Deepak Ranjan Nayak², Shuihua Wang^1,3,4,*
CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 299-313, 2020, DOI:10.32604/cmes.2020.011069
（This article belongs to this Special Issue: Recent Advances on Deep Learning for Medical Signal Analysis (RADLMSA))
Abstract Hearing loss (HL) is a kind of common illness, which can significantly reduce the quality of life. For example, HL often results in mishearing, misunderstanding, and communication problems. Therefore, it is necessary to provide early diagnosis and timely treatment for HL. This study investigated the advantages and disadvantages of three classical machine learning methods: multilayer perceptron (MLP), support vector machine (SVM), and least-square support vector machine (LS-SVM) approach and made a further optimization of the LS-SVM model via wavelet entropy. The investigation illustrated that themultilayer perceptron is a shallowneural network,while the least square support vector machine uses hinge loss function… More
Views:308 Downloads:158 Download PDF

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REVIEW
Importance of Features Selection, Attributes Selection, Challenges and Future Directions for Medical Imaging Data: A Review
Nazish Naheed¹, Muhammad Shaheen¹, Sajid Ali Khan¹, Mohammed Alawairdhi^2,*, Muhammad Attique Khan^3,*
CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 315-344, 2020, DOI:10.32604/cmes.2020.011380
（This article belongs to this Special Issue: Recent Advances on Deep Learning for Medical Signal Analysis (RADLMSA))
Abstract In the area of pattern recognition and machine learning, features play a key role in prediction. The famous applications of features are medical imaging, image classification, and name a few more. With the exponential growth of information investments in medical data repositories and health service provision, medical institutions are collecting large volumes of data. These data repositories contain details information essential to support medical diagnostic decisions and also improve patient care quality. On the other hand, this growth also made it difficult to comprehend and utilize data for various purposes. The results of imaging data can become biased because of… More
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ARTICLE
A Multi-View Gait Recognition Method Using Deep Convolutional Neural Network and Channel Attention Mechanism
Jiabin Wang^*, Kai Peng
CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 345-363, 2020, DOI:10.32604/cmes.2020.011046
（This article belongs to this Special Issue: Recent Advances on Deep Learning for Medical Signal Analysis (RADLMSA))
Abstract In many existing multi-view gait recognition methods based on images or video sequences, gait sequences are usually used to superimpose and synthesize images and construct energy-like template. However, information may be lost during the process of compositing image and capture EMG signals. Errors and the recognition accuracy may be introduced and affected respectively by some factors such as period detection. To better solve the problems, a multi-view gait recognition method using deep convolutional neural network and channel attention mechanism is proposed. Firstly, the sliding time window method is used to capture EMG signals. Then, the back-propagation learning algorithm is used… More
Views:372 Downloads:167 Download PDF

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ARTICLE
PDNet: A Convolutional Neural Network Has Potential to be Deployed on Small Intelligent Devices for Arrhythmia Diagnosis
Fei Yang^1,2,#, Xiaoqing Zhang^1,*,#, Yong Zhu³
CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 365-382, 2020, DOI:10.32604/cmes.2020.010798
（This article belongs to this Special Issue: Recent Advances on Deep Learning for Medical Signal Analysis (RADLMSA))
Abstract Heart arrhythmia is a group of irregular heartbeat conditions and is usually detected by electrocardiograms (ECG) signals. Over the past years, deep learning methods have been developed to classify different types of heart arrhythmias through ECG based on computer-aided diagnosis systems (CADs), but these deep learning methods usually cannot trade-off between classi More
Views:403 Downloads:168 Download PDF

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ARTICLE
Robust Design Optimization and Improvement by Metamodel
Shufang Song^*, Lu Wang, Yuhua Yan
CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 383-399, 2020, DOI:10.32604/cmes.2020.09588
（This article belongs to this Special Issue: Novel Methods for Reliability Evaluation and Optimization of Complex Mechanical Structures)
Abstract The robust design optimization (RDO) is an effective method to improve product performance with uncertainty factors. The robust optimal solution should be not only satisfied the probabilistic constraints but also less sensitive to the variation of design variables. There are some important issues in RDO, such as how to judge robustness, deal with multi-objective problem and black-box situation. In this paper, two criteria are proposed to judge the deterministic optimal solution whether satisfies robustness requirment. The robustness measure based on maximum entropy is proposed. Weighted sum method is improved to deal with the objective function, and the basic framework of… More
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ARTICLE
Research on Trajectory Tracking Method of Redundant Manipulator Based on PSO Algorithm Optimization
Shifu Xu^*, Yanan Jiang
CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 401-415, 2020, DOI:10.32604/cmes.2020.09608
（This article belongs to this Special Issue: Novel Methods for Reliability Evaluation and Optimization of Complex Mechanical Structures)
Abstract Aiming at the problem that the trajectory tracking performance of redundant manipulator corresponding to the target position is difficult to optimize, the trajectory tracking method of redundant manipulator based on PSO algorithm optimization is studied. The kinematic diagram of redundant manipulator is created, to derive the equation of motion trajectory of redundant manipulator end. Pseudo inverse Jacobi matrix is used to solve the problem of manipulator redundancy. Based on the tracking ellipse of redundant manipulator, the tracking shape of redundant manipulator is determined with the overall tracking index as the second index, and the optimization method of tracking index is… More
Views:369 Downloads:173 Download PDF

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ARTICLE
Multiple Images Steganography of JPEG Images Based on Optimal Payload Distribution
Yang Pei^1,2, Xiangyang Luo^1,2,*, Yi Zhang², Liyan Zhu²
CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 417-436, 2020, DOI:10.32604/cmes.2020.010636
（This article belongs to this Special Issue: Information Hiding and Multimedia Security)
Abstract Multiple images steganography refers to hiding secret messages in multiple natural images to minimize the leakage of secret messages during transmission. Currently, the main multiple images steganography algorithms mainly distribute the payloads as sparsely as possible in multiple cover images to improve the detection error rate of stego images. In order to enable the payloads to be accurately and efficiently distributed in each cover image, this paper proposes a multiple images steganography for JPEG images based on optimal payload redistribution. Firstly, the algorithm uses the principle of dynamic programming to redistribute the payloads of the cover images to reduce the… More
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ARTICLE
Topp-Leone Odd Fréchet Generated Family of Distributions with Applications to COVID-19 Data Sets
Sanaa Al-Marzouki¹, Farrukh Jamal², Christophe Chesneau^3,*, Mohammed Elgarhy⁴
CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 437-458, 2020, DOI:10.32604/cmes.2020.011521
（This article belongs to this Special Issue: Computer Modelling of Transmission, Spread, Control and Diagnosis of COVID-19)
Abstract Recent studies have pointed out the potential of the odd Fréchet family (or class) of continuous distributions in fitting data of all kinds. In this article, we propose an extension of this family through the so-called “Topp-Leone strategy”, aiming to improve its overall flexibility by adding a shape parameter. The main objective is to offer original distributions with modifiable properties, from which adaptive and pliant statistical models can be derived. For the new family, these aspects are illustrated by the means of comprehensive mathematical and numerical results. In particular, we emphasize a special distribution with three parameters based on the… More
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ARTICLE
Conceptual Modular Design of Auto Body Frame Based on Hybrid Optimization Method
Yonghong Zhao¹, Changsheng Wang², Huanquan Yuan¹, Yongcheng Li¹, Chunlai Shan², Wenbin Hou^{2, *}
CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.1, pp. 351-376, 2020, DOI:10.32604/cmes.2020.08058
Abstract This article presents a systematic research methodology of modular design for conceptual auto body frame by hybrid optimization method. A modified graph-based decomposition optimization algorithm is utilized to generate an optimal BIW assembly topo model composed of “potential modules”. The consistency constraint function in collaborative optimization is extended to maximize the commonality of modules and minimize the performance loss of all car types in the same product family simultaneously. A novel screening method is employed to select both “basic structures” and “reinforcement” modules based on the dimension optimization of the manufacturing elements and the optimal assembly mode; this allows for… More
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ARTICLE
Data Augmentation Technology Driven By Image Style Transfer in Self-Driving Car Based on End-to-End Learning
Dongjie Liu¹, Jin Zhao^{1, *}, Axin Xi², Chao Wang¹, Xinnian Huang¹, Kuncheng Lai¹, Chang Liu¹
CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.2, pp. 593-617, 2020, DOI:10.32604/cmes.2020.08641
Abstract With the advent of deep learning, self-driving schemes based on deep learning are becoming more and more popular. Robust perception-action models should learn from data with different scenarios and real behaviors, while current end-to-end model learning is generally limited to training of massive data, innovation of deep network architecture, and learning in-situ model in a simulation environment. Therefore, we introduce a new image style transfer method into data augmentation, and improve the diversity of limited data by changing the texture, contrast ratio and color of the image, and then it is extended to the scenarios that the model has been… More
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ARTICLE
Feature Selection with a Local Search Strategy Based on the Forest Optimization Algorithm
Tinghuai Ma^1,*, Honghao Zhou¹, Dongdong Jia¹, Abdullah Al-Dhelaan², Mohammed Al-Dhelaan², Yuan Tian³
CMES-Computer Modeling in Engineering & Sciences, Vol.121, No.2, pp. 569-592, 2019, DOI:10.32604/cmes.2019.07758
Abstract Feature selection has been widely used in data mining and machine learning. Its objective is to select a minimal subset of features according to some reasonable criteria so as to solve the original task more quickly. In this article, a feature selection algorithm with local search strategy based on the forest optimization algorithm, namely FSLSFOA, is proposed. The novel local search strategy in local seeding process guarantees the quality of the feature subset in the forest. Next, the fitness function is improved, which not only considers the classification accuracy, but also considers the size of the feature subset. To avoid… More
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ARTICLE
Vibration Analysis of a Drillstring in Horizontal Well
Xiaohua Zhu^1,*, Li Zeng¹, Bo Li¹
CMES-Computer Modeling in Engineering & Sciences, Vol.121, No.2, pp. 631-660, 2019, DOI:10.32604/cmes.2019.06755
Abstract The complicated geological conditions will bring great challenges to the drillstring of horizontal wells for the reason that the increase of the well depth in SichuanChongqing region. Since drillstring failure and friction during drilling are generally caused by drillstring vibration, great importance must be attached to computer simulation methods for the prediction of drillstring vibration. A finite element model considering axial, lateral and torsional vibration is established. In order to verify the established numerical model, an indoor experimental device based on the similarity principle was established. The vibration characteristics of three shale gas horizontal wells drillstrings are described. The reasons… More
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ARTICLE
Numerical Simulations of the Ice Load of a Ship Navigating in Level Ice Using Peridynamics
Yanzhuo Xue¹, Renwei Liu¹, Yang Liu^1,*, Lingdong Zeng¹, Duanfeng Han¹
CMES-Computer Modeling in Engineering & Sciences, Vol.121, No.2, pp. 523-550, 2019, DOI:10.32604/cmes.2019.06951
（This article belongs to this Special Issue: Recent Developments on Peridynamics)
Abstract In this study, a numerical method was developed based on peridynamics to determine the ice loads for a ship navigating in level ice. Convergence analysis of threedimensional ice specimen with tensile and compression loading are carried out first. The effects of ice thickness, sailing speed, and ice properties on the mean ice loads were also investigated. It is observed that the ice fragments resulting from the icebreaking process will interact with one another as well as with the water and ship hull. The ice fragments may rotate, collide, or slide along the ship hull, and these ice fragments will eventually… More
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ARTICLE
A Robust Roll Stabilization Controller with Aerodynamic Disturbance and Actuator Failure Consideration
Qiancai Ma¹, Fengjie Gao², Yang Wang³, Qiuxiong Gou³, Liangyu Zhao^{1, *}
CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.1, pp. 109-130, 2020, DOI:10.32604/cmes.2020.08109
（This article belongs to this Special Issue: Nonlinear Computational and Control Methods in Aerospace Engineering)
Abstract Combining adaptive theory with an advanced second-order sliding mode control algorithm, a roll stabilization controller with aerodynamic disturbance and actuator failure consideration for spinning flight vehicles is proposed in this paper. The presented controller is summarized as an “observer-controller” system. More specifically, an adaptive second-order sliding mode observer is presented to select the proper design parameters and estimate the knowledge of aerodynamic disturbance and actuator failure, while the proposed roll stabilization control scheme can drive both roll angle and rotation rate smoothly converge to the desired value. Theoretical analysis and numerical simulation results demonstrate the effectiveness of the proposed controller. More
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