Home / Journals / CMES / Vol.131, No.3, 2022
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  • Open AccessOpen Access

    REVIEW

    Analysis of Multi-AGVs Management System and Key Issues: A Review

    Wenhao Lu1, Shuai Guo1,2, Tao Song1,*, Yuwen Li1
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1197-1227, 2022, DOI:10.32604/cmes.2022.019770
    Abstract Multiple Automatic Guided Vehicle (multi-AGVs) management systems provide an effective solution to ensuring stable operations of multi-AGVs in the same scenario, such as flexible manufacturing systems, warehouses, container terminals, etc. This type of systems need to balance the relationship among the resources of the system and solve the problems existing in the operation to make the system in line with the requirement of the administrator. The multi-AGVs management problem is a multi-objective, multi-constraint combinatorial optimization problem, which depends on the types of application scenarios. This article classifies and compares the research papers on multi-AGVs management in detail. Firstly, according to… More >

  • Open AccessOpen Access

    ARTICLE

    Assessment of the Solid Waste Disposal Method during COVID-19 Period Using the ELECTRE III Method in an Interval-Valued q-Rung Orthopair Fuzzy Approach

    Samayan Narayanamoorthy1, Arumugam Anuja1, J. V. Brainy1, Thangaraj Manirathinam1, Subramaniam Pragathi1, Thirumalai Nallasivan Parthasarathy1, Daekook Kang2,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1229-1261, 2022, DOI:10.32604/cmes.2022.019442
    Abstract As the quantity of garbage created every day rises, solid waste management has become the world’s most important issue. As a result, improper solid waste disposal and major sanitary issues develop, which are only detected after they have become dangerous. Due to the system’s lockdown during the COVID-19 pandemic, this scenario became much more uncertain. We are at the stage to develop and execute effective waste management procedures, as well as long-term policies and forward-thinking programmes that can work even in the most adverse of scenarios. We incorporate major solid waste (organic and inorganic solid wastes) approaches that actually perform… More >

  • Open AccessOpen Access

    ARTICLE

    Sentiment Analysis of Roman Urdu on E-Commerce Reviews Using Machine Learning

    Bilal Chandio1, Asadullah Shaikh2, Maheen Bakhtyar1, Mesfer Alrizq2, Junaid Baber1, Adel Sulaiman2,*, Adel Rajab2, Waheed Noor3
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1263-1287, 2022, DOI:10.32604/cmes.2022.019535
    Abstract Sentiment analysis task has widely been studied for various languages such as English and French. However, Roman Urdu sentiment analysis yet requires more attention from peer-researchers due to the lack of Off-the-Shelf Natural Language Processing (NLP) solutions. The primary objective of this study is to investigate the diverse machine learning methods for the sentiment analysis of Roman Urdu data which is very informal in nature and needs to be lexically normalized. To mitigate this challenge, we propose a fine-tuned Support Vector Machine (SVM) powered by Roman Urdu Stemmer. In our proposed scheme, the corpus data is initially cleaned to remove… More >

  • Open AccessOpen Access

    ARTICLE

    Nonlinear Response of Tunnel Portal under Earthquake Waves with Different Vibration Directions

    Hongyun Jiao1, Mi Zhao1, Jingqi Huang2,*, Xu Zhao1,3, Xiuli Du1
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1289-1314, 2022, DOI:10.32604/cmes.2022.018540
    Abstract Tunnel portal sections often suffer serious damage in strong earthquake events. Earthquake waves may propagate in different directions, producing various dynamic responses in the tunnel portal. Based on the Galongla tunnel, which is located in a seismic region of China, three-dimensional seismic analysis is conducted to investigate the dynamic response of a tunnel portal subjected to earthquake waves with different vibration directions. In order to simulate the mechanic behavior of slope rock effectively, an elastoplastic damage model is adopted and applied to ABAQUS software by a self-compiled user material (UMAT) subroutine. Moreover, the seismic wave input method for tunnel portal… More >

  • Open AccessOpen Access

    ARTICLE

    A Method Based on Knowledge Distillation for Fish School Stress State Recognition in Intensive Aquaculture

    Siyuan Mei1,2, Yingyi Chen1,2,*, Hanxiang Qin1,2, Huihui Yu3, Daoliang Li1,2, Boyang Sun1,2, Ling Yang1,2, Yeqi Liu1,2
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1315-1335, 2022, DOI:10.32604/cmes.2022.019378
    Abstract Fish behavior analysis for recognizing stress is very important for fish welfare and production management in aquaculture. Recent advances have been made in fish behavior analysis based on deep learning. However, most existing methods with top performance rely on considerable memory and computational resources, which is impractical in the real-world scenario. In order to overcome the limitations of these methods, a new method based on knowledge distillation is proposed to identify the stress states of fish schools. The knowledge distillation architecture transfers additional inter-class information via a mixed relative loss function, and it forces a lightweight network (GhostNet) to mimic… More >

  • Open AccessOpen Access

    ARTICLE

    Detecting and Repairing Data-Flow Errors in WFD-net Systems

    Fang Zhao1, Dongming Xiang2,*, Guanjun Liu1, Changjun Jiang1, Honghao Zhu3
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1337-1363, 2022, DOI:10.32604/cmes.2022.018872
    Abstract Workflow system has become a standard solution for managing a complex business process. How to guarantee its correctness is a key requirement. Many methods only focus on the control-flow verification, while they neglect the modeling and checking of data-flows. Although some studies are presented to repair the data-flow errors, they do not consider the effect of delete operations or weak circulation relations on the repairing results. What's more, repairing some data-flow errors may bring in new errors. In order to solve these problems, we use workflow net with data (WFD-net) systems to model and analyze a workflow system. Based on… More >

  • Open AccessOpen Access

    ARTICLE

    User Role Discovery and Optimization Method Based on K-means++ and Reinforcement Learning in Mobile Applications

    Yuanbang Li*, Wengang Zhou, Chi Xu, Yuchun Shi
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1365-1386, 2022, DOI:10.32604/cmes.2022.019656
    Abstract With the widespread use of mobile phones, users can share their location and activity anytime, anywhere, as a form of check-in data. These data reflect user features. Long-term stability and a set of user-shared features can be abstracted as user roles. This role is closely related to the users’ social background, occupation, and living habits. This study makes four main contributions to the literature. First, user feature models from different views for each user are constructed from the analysis of the check-in data. Second, the K-means algorithm is used to discover user roles from user features. Third, a reinforcement learning… More >

  • Open AccessOpen Access

    ARTICLE

    Efficient Data Augmentation Techniques for Improved Classification in Limited Data Set of Oral Squamous Cell Carcinoma

    Wael Alosaimi1,*, M. Irfan Uddin2
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1387-1401, 2022, DOI:10.32604/cmes.2022.018433
    Abstract Deep Learning (DL) techniques as a subfield of data science are getting overwhelming attention mainly because of their ability to understand the underlying pattern of data in making classifications. These techniques require a considerable amount of data to efficiently train the DL models. Generally, when the data size is larger, the DL models perform better. However, it is not possible to have a considerable amount of data in different domains such as healthcare. In healthcare, it is impossible to have a substantial amount of data to solve medical problems using Artificial Intelligence, mainly due to ethical issues and the privacy… More >

  • Open AccessOpen Access

    ARTICLE

    A Numerical Modelling Method of Fractured Reservoirs with Embedded Meshes and Topological Fracture Projection Configurations

    Xiang Rao1,2,*, Yina Liu1,2
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1403-1429, 2022, DOI:10.32604/cmes.2022.018879
    Abstract Projection-based embedded discrete fracture model (pEDFM) is an effective numerical model to handle the flow in fractured reservoirs, with high efficiency and strong generalization of flow models. However, this paper points out that pEDFM fails to handle flow barriers in most cases, and identifies the physical projection configuration of fractures is a key step in pEDFM. This paper presents and proves the equivalence theorem, which explains the geometric nature of physical projection configurations of fractures, that is, the projection configuration of a fracture being physical is equivalent to it being topologically homeomorphic to the fracture, by analyzing the essence of… More >

  • Open AccessOpen Access

    ARTICLE

    Novel Time Series Bagging Based Hybrid Models for Predicting Historical Water Levels in the Mekong Delta Region, Vietnam

    Nguyen Thanh Hoan1, Nguyen Van Dung1, Ho Le Thu1, Hoa Thuy Quynh1, Nadhir Al-Ansari2,*, Tran Van Phong3, Phan Trong Trinh3, Dam Duc Nguyen4, Hiep Van Le4, Hanh Bich Thi Nguyen4, Mahdis Amiri5, Indra Prakash6, Binh Thai Pham4,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1431-1449, 2022, DOI:10.32604/cmes.2022.018699
    (This article belongs to this Special Issue: Soft Computing Techniques in Materials Science and Engineering)
    Abstract Water level predictions in the river, lake and delta play an important role in flood management. Every year Mekong River delta of Vietnam is experiencing flood due to heavy monsoon rains and high tides. Land subsidence may also aggravate flooding problems in this area. Therefore, accurate predictions of water levels in this region are very important to forewarn the people and authorities for taking timely adequate remedial measures to prevent losses of life and property. There are so many methods available to predict the water levels based on historical data but nowadays Machine Learning (ML) methods are considered the best… More >

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