Study of an SSA-BP Neural Network-Based Strength Prediction Model for Slag–Cement-Stabilized Soil

• Published in: Materials Vol. 18; no. 15; p. 3520
• Main Authors: Zhang, Bei, Tao, Xingyu, Zhang, Han, Yu, Jun
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 27.07.2025; MDPI
• Subjects: Algorithms; Back propagation; Back propagation networks; Cement hydration; Composite materials; Compressive strength; Design engineering; Expected values; Industrial wastes; Mechanical properties; Moisture content; Neural networks; Neurons; Optimization; Prediction models; Sandy soils; Search algorithms; Slag; Soil properties; Soil strength; sparrow search algorithm; prediction model; prediction of compressive strength; cement-stabilized soil; SSA-BP neural network

As an industrial waste, slag powder can be processed and incorporated into cement-based materials as an additive, significantly improving the engineering properties of cement–soil. The strength of slag–cement-stabilized soil is subject to nonlinear interactions among multiple factors, including ceme...