Peng Zhang¹, Dongsheng Shi^1,*, Ping Han^1,2, Wenchao Jiang^1,3

Journal of Renewable Materials, Vol.11, No.2, pp. 669-688, 2023, DOI:10.32604/jrm.2022.022192

Abstract The destruction of concrete building materials in severely cold regions of the north is more severely affected by freeze-thaw cycles, and the relationship between the mechanical properties and pore structure of concrete with fine aggregate from municipal solid waste (MSW) incineration bottom ash after freeze-thaw cycles is analyzed under the degree of freeze-thaw hazard variation. In this paper, the gray correlation method is used to calculate the correlation between the relative dynamic elastic modulus, compressive strength, and microscopic porosity parameters to speculate on the most important factors affecting their changes. The GM (1,1) model was established based on the compressive… More >

Gang Yu^1,4,5, Jian Tang^2,*, Jian Zhang³, Zhonghui Wang⁶

Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 273-290, 2021, DOI:10.32604/iasc.2021.016981

Abstract Kernel learning based on structure risk minimum can be employed to build a soft measuring model for analyzing small samples. However, it is difficult to select learning parameters, such as kernel parameter (KP) and regularization parameter (RP). In this paper, a soft measuring method is investigated to select learning parameters, which is based on adaptive multi-layer selective ensemble (AMLSEN) and least-square support vector machine (LSSVM). First, candidate kernels and RPs with K and R numbers are preset based on prior knowledge, and candidate sub-sub-models with K*R numbers are constructed through utilizing LSSVM. Second, the candidate sub-sub-models with same KPs and… More >