Changkye Lee¹, Sundararajan Natarajan², Seong-Hoon Kee³, Jurng-Jae Yee^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1615-1634, 2022, DOI:10.32604/cmes.2022.020377

Abstract The aim of this work is to employ a modified cell-based smoothed finite element method (S-FEM) for topology optimization with the domain discretized with arbitrary polygons. In the present work, the linear polynomial basis function is used as the weight function instead of the constant weight function used in the standard S-FEM. This improves the accuracy and yields an optimal convergence rate. The gradients are smoothed over each smoothing domain, then used to compute the stiffness matrix. Within the proposed scheme, an optimum topology procedure is conducted over the smoothing domains. Structural materials are distributed over each smoothing domain and… More >

Shaohua Gu^1,2, Jiabao Wang³, Liang Xue^3,*, Bin Tu³, Mingjin Yang³, Yuetian Liu³

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1579-1599, 2022, DOI:10.32604/cmes.2022.019435

Abstract Production performance prediction of tight gas reservoirs is crucial to the estimation of ultimate recovery, which has an important impact on gas field development planning and economic evaluation. Owing to the model’s simplicity, the decline curve analysis method has been widely used to predict production performance. The advancement of deep-learning methods provides an intelligent way of analyzing production performance in tight gas reservoirs. In this paper, a sequence learning method to improve the accuracy and efficiency of tight gas production forecasting is proposed. The sequence learning methods used in production performance analysis herein include the recurrent neural network (RNN), long… More >

Weiwei Cai^1,2, Yaping Song¹, Huan Duan¹, Zhenwei Xia¹, Zhanguo Wei^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1539-1555, 2022, DOI:10.32604/cmes.2022.019785

Abstract In the smart logistics industry, unmanned forklifts that intelligently identify logistics pallets can improve work efficiency in warehousing and transportation and are better than traditional manual forklifts driven by humans. Therefore, they play a critical role in smart warehousing, and semantics segmentation is an effective method to realize the intelligent identification of logistics pallets. However, most current recognition algorithms are ineffective due to the diverse types of pallets, their complex shapes, frequent blockades in production environments, and changing lighting conditions. This paper proposes a novel multi-feature fusion-guided multiscale bidirectional attention (MFMBA) neural network for logistics pallet segmentation. To better predict… More >

Aniket N. Sharma¹, Shilpa R. Dongre¹, Rajesh Gupta¹, Prerna Pandey¹, Neeraj Dhanraj Bokde^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1515-1537, 2022, DOI:10.32604/cmes.2022.018867

Abstract Water distribution network (WDN) leakage management has received increased attention in recent years. One of the most successful leakage-control strategies is to divide the network into District Metered Areas (DMAs). As a multi-staged technique, the generation of DMAs is a difficult task in design and implementation (i.e., clustering, sectorization, and performance evaluation). Previous studies on DMAs implementation did not consider the potential use of existing valves in achieving the objective. In this work, a methodology is proposed for detecting clusters and reducing the cost of additional valves and DMA sectorization by considering existing valves as much as possible. The procedure… More >

Hye Kyung Kim^1,*, Dae Sik Lee²

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1479-1495, 2022, DOI:10.32604/cmes.2022.017616

Abstract Degenerate versions of special polynomials and numbers applied to social problems, physics, and applied mathematics have been studied variously in recent years. Moreover, the (s-)Lah numbers have many other interesting applications in analysis and combinatorics. In this paper, we divide two parts. We first introduce new types of both degenerate incomplete and complete s-Bell polynomials respectively and investigate some properties of them respectively. Second, we introduce the degenerate versions of complete and incomplete Lah-Bell polynomials as multivariate forms for a new type of degenerate s-extended Lah-Bell polynomials and numbers respectively. We investigate relations between these polynomials and degenerate incomplete and… More >

Bilal Khan^1,*, Zhi-Guo Liu¹, Nazar Khan², Aftab Hussain³, Nasir Khan⁴, Muhammad Tahir²

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1465-1477, 2022, DOI:10.32604/cmes.2022.016940

Abstract By using the basic (or q)-Calculus many subclasses of analytic and univalent functions have been generalized and studied from different viewpoints and perspectives. In this paper, we aim to define certain new subclasses of an analytic function. We then give necessary and sufficient conditions for each of the defined function classes. We also study necessary and sufficient conditions for a function whose coefficients are probabilities of q-Poisson distribution. To validate our results, some known consequences are also given in the form of Remarks and Corollaries. More >

Xiang Rao^1,2,*, Yina Liu^1,2

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 >

Bilal Chandio¹, Asadullah Shaikh², Maheen Bakhtyar¹, Mesfer Alrizq², Junaid Baber¹, Adel Sulaiman^2,*, 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 >

Jing Cheng¹, Yang Xie², Jie Zhang^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1831-1855, 2022, DOI:10.32604/cmes.2022.020178

Abstract For a city, analyzing its advantages, disadvantages and the level of economic development in a country is important, especially for the cities in China developing at flying speed. The corresponding literatures for the cities in China have not considered the indicators of economy and industry in detail. In this paper, based on multiple indicators of economy and industry, the urban hierarchical structure of 285 cities above the prefecture level in China is investigated. The indicators from the economy, industry, infrastructure, medical care, population, education, culture, and employment levels are selected to establish a new indicator system for analyzing urban hierarchical… More >

Li Lei¹, Zihao Wang^2,*, Yong Wu³

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.3, pp. 1815-1830, 2022, DOI:10.32604/cmes.2022.019855

Abstract It is essential to fully understand master the traffic characteristics of the self-stabilizing control effect and road characteristics to ensure the regular operation of transportation. Traffic flow on curved roads and slopes is irregular and more complicated than that on the straight road. However, most of the research only considers the effect of self-stabilizing in the straight road. This study attempts to bridge this deficiency from the following three aspects. First, we review the potential influencing factors of traffic flow stability, which are related to the vehicle's steady velocity, history velocity, and the turn radius of the road and the… More >