Zixuan Wu¹, Ye Wang^1,*, Lifeng Shen², Feng Hu¹, Hong Yu^1,*

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4111-4127, 2024, DOI:10.32604/cmc.2024.054581 - 12 September 2024

Abstract Hierarchical Text Classification (HTC) aims to match text to hierarchical labels. Existing methods overlook two critical issues: first, some texts cannot be fully matched to leaf node labels and need to be classified to the correct parent node instead of treating leaf nodes as the final classification target. Second, error propagation occurs when a misclassification at a parent node propagates down the hierarchy, ultimately leading to inaccurate predictions at the leaf nodes. To address these limitations, we propose an uncertainty-guided HTC depth-aware model called DepthMatch. Specifically, we design an early stopping strategy with uncertainty to More >

Juan Li¹, Tingting Xu^1,*, Yi Gu², Chuang Liu¹, Guiping Zhou², Guoliang Bian¹

Energy Engineering, Vol.121, No.10, pp. 2777-2795, 2024, DOI:10.32604/ee.2024.052331 - 11 September 2024

Abstract In fossil energy pollution is serious and the “double carbon” goal is being promoted, as a symbol of fresh energy in the electrical system, solar and wind power have an increasing installed capacity, only conventional units obviously can not solve the new energy as the main body of the scheduling problem. To enhance the system scheduling ability, based on the participation of thermal power units, incorporate the high energy-carrying load of electro-melting magnesium into the regulation object, and consider the effects on the wind unpredictability of the power. Firstly, the operating characteristics of high energy… More >

Debiao Meng^1,*, Abílio Manuel Pinho de Jesus², Zeng Meng³

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 1-5, 2024, DOI:10.32604/cmes.2024.056319 - 20 August 2024

Abstract This article has no abstract. More >

Kenian Wang^1,2,*, Yuan Hong^1,2, Chunxiao Li²

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1123-1142, 2024, DOI:10.32604/cmc.2024.052088 - 18 July 2024

Abstract With the exponential increase in information security risks, ensuring the safety of aircraft heavily relies on the accurate performance of risk assessment. However, experts possess a limited understanding of fundamental security elements, such as assets, threats, and vulnerabilities, due to the confidentiality of airborne networks, resulting in cognitive uncertainty. Therefore, the Pythagorean fuzzy Analytic Hierarchy Process (AHP) Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is proposed to address the expert cognitive uncertainty during information security risk assessment for airborne networks. First, Pythagorean fuzzy AHP is employed to construct an index system… More >

Phi-Hung Nguyen^*

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1655-1675, 2024, DOI:10.32604/cmc.2024.050713 - 18 July 2024

Abstract This study aims to establish an expert consensus and enhance the efficacy of decision-making processes by integrating Spherical Fuzzy Sets (SFSs) and Z-Numbers (SFZs). A novel group expert consensus technique, the PHI model, is developed to address the inherent limitations of both SFSs and the traditional Delphi technique, particularly in uncertain, complex scenarios. In such contexts, the accuracy of expert knowledge and the confidence in their judgments are pivotal considerations. This study provides the fundamental operational principles and aggregation operators associated with SFSs and Z-numbers, encompassing weighted geometric and arithmetic operators alongside fully developed operators… More >

Shuai Li¹, Xiaodong Zhao^1,2,*, Jinghu Zhou¹, Xiyue Wang¹

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2587-2611, 2024, DOI:10.32604/cmes.2024.052203 - 08 July 2024

Abstract Accurate quantification of the uncertainty in the mechanical characteristics of dielectric solids is crucial for advancing their application in high-precision technological domains, necessitating the development of robust computational methods. This paper introduces a Conditional Generation Adversarial Network Isogeometric Analysis (CGAN-IGA) to assess the uncertainty of dielectric solids’ mechanical characteristics. IGA is utilized for the precise computation of electric potentials in dielectric, piezoelectric, and flexoelectric materials, leveraging its advantage of integrating seamlessly with Computer-Aided Design (CAD) models to maintain exact geometrical fidelity. The CGAN method is highly efficient in generating models for piezoelectric and flexoelectric materials, More >

M. Navya Pratyusha, Ranjan Kumar^*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2957-2976, 2024, DOI:10.32604/cmes.2024.051581 - 08 July 2024

Abstract In the real world, one of the most common problems in project management is the unpredictability of resources and timelines. An efficient way to resolve uncertainty problems and overcome such obstacles is through an extended fuzzy approach, often known as neutrosophic logic. Our rigorous proposed model has led to the creation of an advanced technique for computing the triangular single-valued neutrosophic number. This innovative approach evaluates the inherent uncertainty in project durations of the planning phase, which enhances the potential significance of the decision-making process in the project. Our proposed method, for the first time… More >

Guanfu Wang¹, Yudie Sun¹, Jinling Li^2,3,*, Yu Jiang¹, Chunhui Li¹, Huanan Yu^2,3, He Wang^2,3, Shiqiang Li^2,3

Energy Engineering, Vol.121, No.6, pp. 1671-1695, 2024, DOI:10.32604/ee.2024.047794 - 21 May 2024

Abstract Traditional optimal scheduling methods are limited to accurate physical models and parameter settings, which are difficult to adapt to the uncertainty of source and load, and there are problems such as the inability to make dynamic decisions continuously. This paper proposed a dynamic economic scheduling method for distribution networks based on deep reinforcement learning. Firstly, the economic scheduling model of the new energy distribution network is established considering the action characteristics of micro-gas turbines, and the dynamic scheduling model based on deep reinforcement learning is constructed for the new energy distribution network system with a More >

Yuping Bian^*, Xiu Wan, Xiaoyu Zhou

Energy Engineering, Vol.121, No.6, pp. 1637-1656, 2024, DOI:10.32604/ee.2024.047678 - 21 May 2024

Abstract To address uncertainty as well as transient stability constraints simultaneously in the preventive control of wind farm systems, a novel three-stage optimization strategy is established in this paper. In the first stage, the probabilistic multi-objective particle swarm optimization based on the point estimate method is employed to cope with the stochastic factors. The transient security region of the system is accurately ensured by the interior point method in the second stage. Finally, the verification of the final optimal objectives and satisfied constraints are enforced in the last stage. Furthermore, the proposed strategy is a general More >

Ruijin Huo^1,2,3, Qingxiang Pei^1,2,3, Xiaohui Yuan^1,*, Yanming Xu³

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 2053-2077, 2024, DOI:10.32604/cmes.2024.049185 - 20 May 2024

Abstract In this paper, a generalized th-order perturbation method based on the isogeometric boundary element method is proposed for the uncertainty analysis of broadband structural acoustic scattering problems. The Burton-Miller method is employed to solve the problem of non-unique solutions that may be encountered in the external acoustic field, and the th-order discretization formulation of the boundary integral equation is derived. In addition, the computation of loop subdivision surfaces and the subdivision rules are introduced. In order to confirm the effectiveness of the algorithm, the computed results are contrasted and analyzed with the results under Monte More >