Shun Ma¹, Na Yu¹, Xiuna Wang², Shiyan Mei¹, Mingrui Zhao^2,*, Xiaoyu Han²

Energy Engineering, Vol.120, No.10, pp. 2369-2392, 2023, DOI:10.32604/ee.2023.028727

Abstract Using the improved prospect theory with the linear transformations of rewarding good and punishing bad (RGPBIT), a new investment ranking model for power grid construction projects (PGCPs) is proposed. Given the uncertainty of each index value under the market environment, fuzzy numbers are used to describe qualitative indicators and interval numbers are used to describe quantitative ones. Taking into account decision-maker’s subjective risk attitudes, a multi-criteria decision-making (MCDM) method based on improved prospect theory is proposed. First, the [−1, 1] RGPBIT operator is proposed to normalize the original data, to obtain the best and worst schemes of PGCPs. Furthermore, the… More >

Chunlei Jiao¹, Hongyan Hao², Ming Li^1,*, Rifucairen Fu¹, Yichun Liu³, Shunfu Lin³, Ronghui Liu³

Energy Engineering, Vol.120, No.10, pp. 2393-2416, 2023, DOI:10.32604/ee.2023.028574

Abstract In the context of the joint operation of China’s intra-provincial markets and inter-provincial trading, how to meet the load demand and energy consumption using inter-provincial renewable energy trading is a key problem. The combined operation of intra-provincial and inter-provincial markets provides a new way for provincial power companies to optimize and clear the intra-provincial power market, complete the intra-provincial consumption responsibility weight index, and consume renewable energy across provinces and regions. This paper combines power generation and consumption within the province, uses inter-provincial renewable energy trading to meet the load demand within the province and completes the index of intra-provincial… More >

Zhiguo Yong¹, Hongmei Kang¹, Falai Chen^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 739-760, 2024, DOI:10.32604/cmes.2023.027171

Abstract PHT-splines are defined as polynomial splines over hierarchical T-meshes with very efficient local refinement properties. The original PHT-spline basis functions constructed by the truncation mechanism have a decay phenomenon, resulting in numerical instability. The non-decay basis functions are constructed as the B-splines that are defined on the 2 × 2 tensor product meshes associated with basis vertices in Kang et al., but at the cost of losing the partition of unity. In the field of finite element analysis and topology optimization, forming the partition of unity is the default ingredient for constructing basis functions of approximate spaces. In this paper,… More > Graphic Abstract

ShiJie Luo¹, Feng Yang¹, Yingjun Wang^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.1, pp. 1-1, 2023, DOI:10.32604/icces.2023.09474

Abstract The isogeometric analysis Method (IGA) is an efficient and accurate engineering analysis method. However, in order to obtain accurate analysis results, the grid must be refined, and the increase of the number of refinements will lead to large-scale equations, which will increase the computational cost. Compared with the traditional equation solvers such as preconditioned conjugate gradient method (PCG), generalized minimal residual (GMRES), the advantage of multigrid method is that the convergence rate is independent of grid scale when solving large-scale equations. This paper presents an adaptive weighted Jacobi method to improve the convergence of geometric multigrid method to efficiently solve… More >

Lihong Guo^*, Jie Yang, Haitao Wu

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1929-1946, 2023, DOI:10.32604/cmc.2023.039170

Abstract Attribute-based encryption (ABE) is a technique used to encrypt data, it has the flexibility of access control, high security, and resistance to collusion attacks, and especially it is used in cloud security protection. However, a large number of bilinear mappings are used in ABE, and the calculation of bilinear pairing is time-consuming. So there is the problem of low efficiency. On the other hand, the decryption key is not uniquely associated with personal identification information, if the decryption key is maliciously sold, ABE is unable to achieve accountability for the user. In practical applications, shared message requires hierarchical sharing in… More >

Mingqiang Zhou^*, Mengjiao Li, Zhiyuan Qian, Kunpeng Li

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2443-2460, 2023, DOI:10.32604/cmc.2023.038675

Abstract Role-based network embedding aims to embed role-similar nodes into a similar embedding space, which is widely used in graph mining tasks such as role classification and detection. Roles are sets of nodes in graph networks with similar structural patterns and functions. However, the role-similar nodes may be far away or even disconnected from each other. Meanwhile, the neighborhood node features and noise also affect the result of the role-based network embedding, which are also challenges of current network embedding work. In this paper, we propose a Role-based network Embedding via Quantum walk with weighted Features fusion (REQF), which simultaneously considers… More >

Lilan Zou¹, Bo Liang¹, Xu Cheng², Shufa Li^1,*, Cong Lin^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2641-2659, 2023, DOI:10.32604/cmes.2023.028037

Abstract Target signal acquisition and detection based on sonar images is a challenging task due to the complex underwater environment. In order to solve the problem that some semantic information in sonar images is lost and model detection performance is degraded due to the complex imaging environment, we proposed a more effective and robust target detection framework based on deep learning, which can make full use of the acoustic shadow information in the forward-looking sonar images to assist underwater target detection. Firstly, the weighted box fusion method is adopted to generate a fusion box by weighted fusion of prediction boxes with… More > Graphic Abstract

Shahzad Noor Abbasi¹, Shahzaib Ashraf^1,*, M. Shazib Hameed¹, Sayed M. Eldin^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2795-2844, 2023, DOI:10.32604/cmes.2023.028963

Abstract The primary goal of this research is to determine the optimal agricultural field selection that would most effectively support manufacturing producers in manufacturing production while accounting for unpredictability and reliability in their decision-making. The PFS is known to address the levels of participation and non-participation. To begin, we introduce the novel concept of a PFZN, which is a hybrid structure of Pythagorean fuzzy sets and the ZN. The PFZN is graded in terms of membership and non-membership, as well as reliability, which provides a strong advice in real-world decision support concerns. The PFZN is a useful tool for dealing with… More >

Zhonghao Qian¹, Hanyi Ma¹, Jun Rao², Jun Hu¹, Lichengzi Yu^2,*, Caoyi Feng¹, Yunxu Qiu¹, Kemo Ding¹

Energy Engineering, Vol.120, No.9, pp. 2013-2027, 2023, DOI:10.32604/ee.2023.028859

Abstract The lack of reactive power in offshore wind farms will affect the voltage stability and power transmission quality of wind farms. To improve the voltage stability and reactive power economy of wind farms, the improved particle swarm optimization is used to optimize the reactive power planning in wind farms. First, the power flow of offshore wind farms is modeled, analyzed and calculated. To improve the global search ability and local optimization ability of particle swarm optimization, the improved particle swarm optimization adopts the adaptive inertia weight and asynchronous learning factor. Taking the minimum active power loss of the offshore wind… More >

Safdar Khan¹, Muhammad Attique Khan², Jamal Hussain Shah^1,*, Faheem Shehzad², Taerang Kim³, Jae-Hyuk Cha³

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2337-2360, 2023, DOI:10.32604/csse.2023.040410

Abstract Human Suspicious Activity Recognition (HSAR) is a critical and active research area in computer vision that relies on artificial intelligence reasoning. Significant advances have been made in this field recently due to important applications such as video surveillance. In video surveillance, humans are monitored through video cameras when doing suspicious activities such as kidnapping, fighting, snatching, and a few more. Although numerous techniques have been introduced in the literature for routine human actions (HAR), very few studies are available for HSAR. This study proposes a deep convolutional neural network (CNN) and optimal featuresbased framework for HSAR in video frames. The… More >