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EDITORIAL

Yudong Zhang^1,*, Huiling Chen²
CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1065-1067, 2023, DOI:10.32604/cmes.2023.029710 - 26 June 2023
（This article belongs to the Special Issue: Bio-inspired Optimization in Engineering and Sciences)
Abstract This article has no abstract. More >

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Loc Vu-Quoc^1,*, Alexander Humer²
CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1069-1343, 2023, DOI:10.32604/cmes.2023.028130 - 26 June 2023
Abstract Three recent breakthroughs due to AI in arts and science serve as motivation: An award winning digital image, protein folding, fast matrix multiplication. Many recent developments in artificial neural networks, particularly deep learning (DL), applied and relevant to computational mechanics (solid, fluids, finite-element technology) are reviewed in detail. Both hybrid and pure machine learning (ML) methods are discussed. Hybrid methods combine traditional PDE discretizations with ML methods either (1) to help model complex nonlinear constitutive relations, (2) to nonlinearly reduce the model order for efficient simulation (turbulence), or (3) to accelerate the simulation by predicting… More >

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Yanjun Yan, Kai Chen^*, Hang Geng, Wenqian Fan, Xinrui Zhou
CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1345-1379, 2023, DOI:10.32604/cmes.2023.027252 - 26 June 2023
Abstract With increasing global concerns about clean energy in smart grids, the detection of power quality disturbances (PQDs) caused by energy instability is becoming more and more prominent. It is well acknowledged that the PQD effects on power grid equipment are destructive and hazardous, which causes irreversible damage to underlying electrical/electronic equipment of the concerned intelligent grids. In order to ensure safe and reliable equipment implementation, appropriate PQD detection technologies must be adopted to avoid such adverse effects. This paper summarizes the newly proposed and traditional PQD detection techniques in order to give a quick start More >

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Jiaqi Wang¹, Pengfei Sun¹, Leilei Chen², Jianfeng Yang³, Zhenghe Liu¹, Haojie Lian^1,*
CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1381-1418, 2023, DOI:10.32604/cmes.2023.023693 - 26 June 2023
Abstract Geological hazard is an adverse geological condition that can cause loss of life and property. Accurate prediction and analysis of geological hazards is an important and challenging task. In the past decade, there has been a great expansion of geohazard detection data and advancement in data-driven simulation techniques. In particular, great efforts have been made in applying deep learning to predict geohazards. To understand the recent progress in this field, this paper provides an overview of the commonly used data sources and deep neural networks in the prediction of a variety of geological hazards. More >

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Zipu Yan^1,2, Honghua Dai^1,2,*, Qisi Wang^1,2, Satya N. Atluri³
CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1419-1459, 2023, DOI:10.32604/cmes.2023.028198 - 26 June 2023
Abstract The harmonic balance (HB) method is one of the most commonly used methods for solving periodic solutions of both weakly and strongly nonlinear dynamical systems. However, it is confined to low-order approximations due to complex symbolic operations. Many variants have been developed to improve the HB method, among which the time domain HB-like methods are regarded as crucial improvements because of their fast computation and simple derivation. So far, there are two problems remaining to be addressed. i) A dozen of different versions of HB-like methods, in frequency domain or time domain or in hybrid,… More >

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Zhiyuan Dai, Tian Li^*, Weihua Zhang, Jiye Zhang
CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1461-1489, 2023, DOI:10.32604/cmes.2023.028677 - 26 June 2023
Abstract The aerodynamic optimization design of high-speed trains (HSTs) is crucial for energy conservation, environmental preservation, operational safety, and speeding up. This study aims to review the current state and progress of the aerodynamic multi-objective optimization of HSTs. First, the study explores the impact of train nose shape parameters on aerodynamic performance. The parameterization methods involved in the aerodynamic multiobjective optimization of HSTs are summarized and classified as shape-based and disturbance-based parameterization methods. Meanwhile, the advantages and limitations of each parameterization method, as well as the applicable scope, are briefly discussed. In addition, the NSGA-II algorithm,… More >

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Xiangjuan Jia¹, Jing Xu¹, Mengwei Han¹, Qing Zhang¹, Lu Zhang¹, Xiaofeng Chen^1,2,*
CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1491-1523, 2023, DOI:10.32604/cmes.2023.026357 - 26 June 2023
（This article belongs to the Special Issue: Emerging Trends on Blockchain: Architecture and Dapp Ecosystem)
Abstract As one of the most concerned digital technologies in recent years, blockchain and distributed ledger technology are an important driving force for a new round of technological development. It is currently in the process of accelerating its evolution and maturity, and has gradually integrated with other digital technologies. It has been applied in many industries, providing decentralized solutions for various industries, realizing innovative storage models, and building a new trust system. As blockchain technology is officially incorporated into China’s new information infrastructure category, the application fields of blockchain have expanded rapidly, gradually extending from the… More >

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Apurva Sonavane¹, Aditya Khamparia^2,*, Deepak Gupta³
CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1525-1550, 2023, DOI:10.32604/cmes.2023.028203 - 26 June 2023
（This article belongs to the Special Issue: Intelligent Biomedical Image Processing and Computer Vision)
Abstract IoT usage in healthcare is one of the fastest growing domains all over the world which applies to every age group. Internet of Medical Things (IoMT) bridges the gap between the medical and IoT field where medical devices communicate with each other through a wireless communication network. Advancement in IoMT makes human lives easy and better. This paper provides a comprehensive detailed literature survey to investigate different IoMT-driven applications, methodologies, and techniques to ensure the sustainability of IoMT-driven systems. The limitations of existing IoMT frameworks are also analyzed concerning their applicability in real-time driven systems More >

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ARTICLE

Hong Zhang^1,*, Jiaming Zhou¹, Qi Wang¹, Chengxi Zhu¹, Haijian Shao²
CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1551-1572, 2023, DOI:10.32604/cmes.2023.027035 - 26 June 2023
Abstract Metal flat surface in-line surface defect detection is notoriously difficult due to obstacles such as high surface reflectivity, pseudo-defect interference, and random elastic deformation. This study evaluates the approach for detecting scratches on a metal surface in order to address a problem in the detection process. This paper proposes an improved Gauss-Laplace (LoG) operator combined with a deep learning technique for metal surface scratch identification in order to solve the difficulties that it is challenging to reduce noise and that the edges are unclear when utilizing existing edge detection algorithms. In the process of scratch… More >

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ARTICLE

Yu-Ming Chu¹, Saima Rashid^2,*, Shazia Karim³, Anam Sultan²
CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1573-1611, 2023, DOI:10.32604/cmes.2023.027724 - 26 June 2023
Abstract The fractional-order Boussinesq equations (FBSQe) are investigated in this work to see if they can effectively improve the situation where the shallow water equation cannot directly handle the dispersion wave. The fuzzy forms of analytical FBSQe solutions are first derived using the Adomian decomposition method. It also occurs on the sea floor as opposed to at the functionality. A set of dynamical partial differential equations (PDEs) in this article exemplify an unconfined aquifer flow implication. This methodology can accurately simulate climatological intrinsic waves, so the ripples are spread across a large demographic zone. The Aboodh… More >

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Zaihe Cheng¹, Yuwen Tao², Xiaoqing Gu³, Yizhang Jiang², Pengjiang Qian^2,*
CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1613-1633, 2023, DOI:10.32604/cmes.2023.027708 - 26 June 2023
Abstract Through semi-supervised learning and knowledge inheritance, a novel Takagi-Sugeno-Kang (TSK) fuzzy system framework is proposed for epilepsy data classification in this study. The new method is based on the maximum mean discrepancy (MMD) method and TSK fuzzy system, as a basic model for the classification of epilepsy data. First, for medical data, the interpretability of TSK fuzzy systems can ensure that the prediction results are traceable and safe. Second, in view of the deviation in the data distribution between the real source domain and the target domain, MMD is used to measure the distance between… More >

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ARTICLE

Hao Cui, Yanling Guo^*, Yaning Xiao, Yangwei Wang^*, Jian Li, Yapeng Zhang, Haoyu Zhang
CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1635-1675, 2023, DOI:10.32604/cmes.2023.026019 - 26 June 2023
（This article belongs to the Special Issue: Bio-inspired Computer Modelling: Theories and Applications in Engineering and Sciences)
Abstract Harris Hawks Optimization (HHO) is a novel meta-heuristic algorithm that imitates the predation characteristics of Harris Hawk and combines Lévy flight to solve complex multidimensional problems. Nevertheless, the basic HHO algorithm still has certain limitations, including the tendency to fall into the local optima and poor convergence accuracy. Coot Bird Optimization (CBO) is another new swarm-based optimization algorithm. CBO originates from the regular and irregular motion of a bird called Coot on the water’s surface. Although the framework of CBO is slightly complicated, it has outstanding exploration potential and excellent capability to avoid falling into… More >

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ARTICLE

Muhammad Tayyeb¹, Muhammad Umer¹, Khaled Alnowaiser², Saima Sadiq³, Ala’ Abdulmajid Eshmawi⁴, Rizwan Majeed⁵, Abdullah Mohamed⁶, Houbing Song⁷, Imran Ashraf^8,*
CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1677-1694, 2023, DOI:10.32604/cmes.2023.026535 - 26 June 2023
（This article belongs to the Special Issue: Bio-inspired Computer Modelling: Theories and Applications in Engineering and Sciences)
Abstract Cardiovascular problems have become the predominant cause of death worldwide and a rise in the number of patients has been observed lately. Currently, electrocardiogram (ECG) data is analyzed by medical experts to determine the cardiac abnormality, which is time-consuming. In addition, the diagnosis requires experienced medical experts and is error-prone. However, automated identification of cardiovascular disease using ECGs is a challenging problem and state-of-the-art performance has been attained by complex deep learning architectures. This study proposes a simple multilayer perceptron (MLP) model for heart disease prediction to reduce computational complexity. ECG dataset containing averaged signals More >

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Pavel Trojovský^*, Mohammad Dehghani
CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1695-1730, 2023, DOI:10.32604/cmes.2023.028314 - 26 June 2023
（This article belongs to the Special Issue: Computational Intelligent Systems for Solving Complex Engineering Problems: Principles and Applications)
Abstract This paper introduces a new metaheuristic algorithm called Migration Algorithm (MA), which is helpful in solving optimization problems. The fundamental inspiration of MA is the process of human migration, which aims to improve job, educational, economic, and living conditions, and so on. The mathematical modeling of the proposed MA is presented in two phases to empower the proposed approach in exploration and exploitation during the search process. In the exploration phase, the algorithm population is updated based on the simulation of choosing the migration destination among the available options. In the exploitation phase, the algorithm… More >

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Hang Deng, Jimin Ye^*, Wei Li^*, Dongmei Huang
CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1731-1747, 2023, DOI:10.32604/cmes.2023.028334 - 26 June 2023
（This article belongs to the Special Issue: Vibration Control and Utilization)
Abstract In this paper, the response properties of galloping energy harvesters under bounded random parameter excitation are studied theoretically. The first-order approximate solution of the galloping energy harvester is derived by applying the multi-scales method. The expression for the largest Lyapunov exponent that determines the trivial solution is derived, and the corresponding simulation diagrams, including the largest Lyapunov exponent diagrams and time domain diagrams, verify our results. Then the steady-state response moments of the nontrivial solution are studied using the moment method, and the analytical expressions for the first-order and second-order moments of the voltage amplitude… More >

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ARTICLE

Xinzong Wang¹, Xiaofang Kang^1,2,*, Qingguan Lei¹
CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1749-1771, 2023, DOI:10.32604/cmes.2023.027745 - 26 June 2023
（This article belongs to the Special Issue: Vibration Control and Utilization)
Abstract The chaotic motion behavior of the rectangular conductive thin plate that is simply supported on four sides by airflow and mechanical external excitation in a magnetic field is studied. According to Kirchhoff ’s thin plate theory, considering geometric nonlinearity and using the principle of virtual work, the nonlinear motion partial differential equation of the rectangular conductive thin plate is deduced. Using the separate variable method and Galerkin’s method, the system motion partial differential equation is converted into the general equation of the Duffing equation; the Hamilton system is introduced, and the Melnikov function is used More >

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Qingyue Zhao¹, Qiaoyu Gu², Zhijun Gao^3,*, Shipian Shao¹, Xinyuan Zhang¹
CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1773-1788, 2023, DOI:10.32604/cmes.2023.027500 - 26 June 2023
（This article belongs to the Special Issue: Advanced Intelligent Decision and Intelligent Control with Applications in Smart City)
Abstract Building indoor dangerous behavior recognition is a specific application in the field of abnormal human recognition. A human dangerous behavior recognition method based on LSTM-GCN with attention mechanism (GLA) model was proposed aiming at the problem that the existing human skeleton-based action recognition methods cannot fully extract the temporal and spatial features. The network connects GCN and LSTM network in series, and inputs the skeleton sequence extracted by GCN that contains spatial information into the LSTM layer for time sequence feature extraction, which fully excavates the temporal and spatial features of the skeleton sequence. Finally, More >

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Xiaoli Jing, Xianpeng Wang^*, Xiang Lan, Ting Su
CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1789-1804, 2023, DOI:10.32604/cmes.2023.028477 - 26 June 2023
（This article belongs to the Special Issue: AI-Driven Intelligent Sensor Networks: Key Enabling Theories, Architectures, Modeling, and Techniques)
Abstract At present, the traditional channel estimation algorithms have the disadvantages of over-reliance on initial conditions and high complexity. The bacterial foraging optimization (BFO)-based algorithm has been applied in wireless communication and signal processing because of its simple operation and strong self-organization ability. But the BFO-based algorithm is easy to fall into local optimum. Therefore, this paper proposes the quantum bacterial foraging optimization (QBFO)-binary orthogonal matching pursuit (BOMP) channel estimation algorithm to the problem of local optimization. Firstly, the binary matrix is constructed according to whether atoms are selected or not. And the support set of… More >

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Hui Wei, Leibing Yan^*
CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1805-1824, 2023, DOI:10.32604/cmes.2023.028072 - 26 June 2023
（This article belongs to the Special Issue: Recent Advances in Backscatter and Intelligent Reflecting Surface Communications for 6G-enabled Internet of Things Networks)
Abstract This paper focuses on the secrecy efficiency maximization in intelligent reflecting surface (IRS) assisted unmanned aerial vehicle (UAV) communication. With the popularization of UAV technology, more and more communication scenarios need UAV support. We consider using IRS to improve the secrecy efficiency. Specifically, IRS and UAV trajectories work together to counter potential eavesdroppers, while balancing the secrecy rate and energy consumption. The original problem is difficult to solve due to the coupling of optimization variables. We first introduce secrecy efficiency as an auxiliary variable and propose relaxation optimization problem, and then prove the equivalence between More >

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Qingsong Fan, Qijie Rao, Haisong Huang^*
CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1825-1848, 2023, DOI:10.32604/cmes.2023.028369 - 26 June 2023
（This article belongs to the Special Issue: Computing Methods for Industrial Artificial Intelligence)
Abstract In present-day industrial settings, where robot arms perform tasks in an unstructured environment, there may exist numerous objects of various shapes scattered in random positions, making it challenging for a robot arm to precisely attain the ideal pose to grasp the object. To solve this problem, a multistage robotic arm flexible grasp detection method based on deep learning is proposed. This method first improves the Faster RCNN target detection model, which significantly improves the detection ability of the model for multiscale grasped objects in unstructured scenes. Then, a Squeeze-and-Excitation module is introduced to design a… More >

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Cuiyu Wang, Xinyu Li, Yiping Gao^*
CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1849-1870, 2023, DOI:10.32604/cmes.2023.028098 - 26 June 2023
（This article belongs to the Special Issue: Computing Methods for Industrial Artificial Intelligence)
Abstract Job shop scheduling (JS) is an important technology for modern manufacturing. Flexible job shop scheduling (FJS) is critical in JS, and it has been widely employed in many industries, including aerospace and energy. FJS enables any machine from a certain set to handle an operation, and this is an NP-hard problem. Furthermore, due to the requirements in real-world cases, multi-objective FJS is increasingly widespread, thus increasing the challenge of solving the FJS problems. As a result, it is necessary to develop a novel method to address this challenge. To achieve this goal, a novel collaborative More >

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Sihan Wang, Xinyu Li, Qihao Liu^*
CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1871-1890, 2023, DOI:10.32604/cmes.2023.028339 - 26 June 2023
（This article belongs to the Special Issue: Computing Methods for Industrial Artificial Intelligence)
Abstract The job shop scheduling problem (JSSP) is a classical combinatorial optimization problem that exists widely in diverse scenarios of manufacturing systems. It is a well-known NP-hard problem, when the number of jobs increases, the difficulty of solving the problem exponentially increases. Therefore, a major challenge is to increase the solving efficiency of current algorithms. Modifying the neighborhood structure of the solutions can effectively improve the local search ability and efficiency. In this paper, a genetic Tabu search algorithm with neighborhood clipping (GTS_NC) is proposed for solving JSSP. A neighborhood solution clipping method is developed and… More >

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Mohammed M. Ali Al-Shamiri^1,2, Ghous Ali^3,*, Muhammad Zain Ul Abidin³, Arooj Adeel³
CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1891-1936, 2023, DOI:10.32604/cmes.2023.027844 - 26 June 2023
（This article belongs to the Special Issue: Decision making Modeling, Methods and Applications of Advanced Fuzzy Theory in Engineering and Science)
Abstract Spherical fuzzy soft expert set (SFSES) theory blends the perks of spherical fuzzy sets and group decision-making into a unified approach. It allows solutions to highly complicated uncertainties and ambiguities under the unbiased supervision and group decision-making of multiple experts. However, SFSES theory has some deficiencies such as the inability to interpret and portray the bipolarity of decision-parameters. This work highlights and overcomes these limitations by introducing the novel spherical fuzzy bipolar soft expert sets (SFBSESs) as a powerful hybridization of spherical fuzzy set theory with bipolar soft expert sets (BSESs). Followed by the development More >

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Maha Noorwali¹, Mohammed Shehu Shagari^2,*
CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1937-1956, 2023, DOI:10.32604/cmes.2023.028239 - 26 June 2023
（This article belongs to the Special Issue: Computational Aspects of Nonlinear Operator and Fixed Point Theory with Applications)
Abstract The real world is filled with uncertainty, vagueness, and imprecision. The concepts we meet in everyday life are vague rather than precise. In real-world situations, if a model requires that conclusions drawn from it have some bearings on reality, then two major problems immediately arise, viz. real situations are not usually crisp and deterministic; complete descriptions of real systems often require more comprehensive data than human beings could recognize simultaneously, process and understand. Conventional mathematical tools which require all inferences to be exact, are not always efficient to handle imprecisions in a wide variety of… More >

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Jinlan Xu^*, Shuxin Xiao, Gang Xu, Renshu Gu
CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1957-1973, 2023, DOI:10.32604/cmes.2023.028665 - 26 June 2023
（This article belongs to the Special Issue: Integration of Geometric Modeling and Numerical Simulation)
Abstract In this paper, we propose a parameterization transfer algorithm for planar domains bounded by B-spline curves, where the shapes of the planar domains are similar. The domain geometries are considered to be similar if their simplified skeletons have the same structures. One domain we call source domain, and it is parameterized using multi-patch B-spline surfaces. The resulting parameterization is C1 continuous in the regular region and G1 continuous around singular points regardless of whether the parameterization of the source domain is C1/G1 continuous or not. In this algorithm, boundary control points of the source domain… More >

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Bingcai Wei, Di Wang, Zhuang Wang, Liye Zhang^*
CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1975-1988, 2023, DOI:10.32604/cmes.2023.027727 - 26 June 2023
（This article belongs to the Special Issue: Federated Learning Algorithms, Approaches, and Systems for Internet of Things)
Abstract With the increasing popularity of artificial intelligence applications, machine learning is also playing an increasingly important role in the Internet of Things (IoT) and the Internet of Vehicles (IoV). As an essential part of the IoV, smart transportation relies heavily on information obtained from images. However, inclement weather, such as snowy weather, negatively impacts the process and can hinder the regular operation of imaging equipment and the acquisition of conventional image information. Not only that, but the snow also makes intelligent transportation systems make the wrong judgment of road conditions and the entire system of… More >

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Di Wang, Bingcai Wei, Liye Zhang^*
CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1989-2000, 2023, DOI:10.32604/cmes.2023.028529 - 26 June 2023
（This article belongs to the Special Issue: Federated Learning Algorithms, Approaches, and Systems for Internet of Things)
Abstract Extracting useful details from images is essential for the Internet of Things project. However, in real life, various external environments,such as badweather conditions,will cause the occlusion of key target information and image distortion, resulting in difficulties and obstacles to the extraction of key information, affecting the judgment of the real situation in the process of the Internet of Things, and causing system decision-making errors and accidents. In this paper, we mainly solve the problem of rain on the image occlusion, remove the rain grain in the image, and get a clear image without rain. Therefore,… More >

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Peng Geng¹, Ji Lu¹, Ying Zhang^2,*, Simin Ma¹, Zhanzhong Tang², Jianhua Liu³
CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 2001-2023, 2023, DOI:10.32604/cmes.2023.027127 - 26 June 2023
（This article belongs to the Special Issue: Computer Modeling of Artificial Intelligence and Medical Imaging)
Abstract In medical image segmentation task, convolutional neural networks (CNNs) are difficult to capture long-range dependencies, but transformers can model the long-range dependencies effectively. However, transformers have a flexible structure and seldom assume the structural bias of input data, so it is difficult for transformers to learn positional encoding of the medical images when using fewer images for training. To solve these problems, a dual branch structure is proposed. In one branch, Mix-Feed-Forward Network (Mix-FFN) and axial attention are adopted to capture long-range dependencies and keep the translation invariance of the model. Mix-FFN whose depth-wise convolutions… More >

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Huabin Wang¹, Ruichao Mo², Yuping Chen³, Weiwei Lin^2,4,*, Minxian Xu⁵, Bo Liu^3,*
CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 2025-2047, 2023, DOI:10.32604/cmes.2023.026910 - 26 June 2023
（This article belongs to the Special Issue: Advances in Edge Intelligence for Internet of Things)
Abstract Nowadays, the rapid development of edge computing has driven an increasing number of deep learning applications deployed at the edge of the network, such as pedestrian and vehicle detection, to provide efficient intelligent services to mobile users. However, as the accuracy requirements continue to increase, the components of deep learning models for pedestrian and vehicle detection, such as YOLOv4, become more sophisticated and the computing resources required for model training are increasing dramatically, which in turn leads to significant challenges in achieving effective deployment on resource-constrained edge devices while ensuring the high accuracy performance. For… More >

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Yuyan Luo^1,2, Xiaoxu Zhang^1,*, Tao Tong¹, Yong Qin^3,*, Zheng Yang¹
CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 2049-2076, 2023, DOI:10.32604/cmes.2023.025413 - 26 June 2023
（This article belongs to the Special Issue: Linguistic Approaches for Multiple Criteria Decision Making and Applications)
Abstract Graduate education is the main way to train high-level innovative talents, the basic layout to cope with the global talent competition, and the important cornerstone for implementing the innovation-driven development strategy and building an innovation-driven country. Therefore, graduate education is of great remarkably to the development of national education. As an important manifestation of graduate education, the quality of a graduate thesis should receive more attention. It is conducive to promoting the quality of graduates by supervising and examining the quality of the graduate thesis. For this purpose, this work is based on text mining,… More >

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