Open Access
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 Access
ARTICLE
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 Access
ARTICLE
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 Access
ARTICLE
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 Access
ARTICLE
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 Access
ARTICLE
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 Access
ARTICLE
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 Access
ARTICLE
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 Access
ARTICLE
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 Access
ARTICLE
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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