Concrete strength prediction machine learning

Author: buoe

August undefined, 2024

WebJan 1, 2024 · Concrete is one of the most widely used materials in various civil engineering applications.Its global production rate is increasing to meet demand. Mechanical properties of concrete are among important parameters in designing and evaluating its performance. Over the past few decades, machine learning has been used to model real-world … WebNov 10, 2024 · Also, machine learning techniques like multi-linear regression (MLR) and extreme gradient boosting (XGB) algorithms were utilized for the compressive strength prediction of concrete (CSC). Results indicated that XGB for cylinder compressive strength was found to be 2.7% greater than cube compressive strength and MLR for …

Prediction of Ecofriendly Concrete Compressive Strength Using …

WebFeb 17, 2024 · Despite previous efforts to map the proportioning of a concrete to its strength, a robust knowledge-based model enabling accurate strength predictions is still lacking. As an alternative to physical or chemical-based models, data-driven machine learning methods offer a promising pathway to address this problem. WebJun 9, 2024 · In general, the compressive strength prediction was undertaken for several type of concrete i.e., ordinary concrete 8,10, high-performance concrete 25,27,28,29,30, ultra-high-performance concrete ... scrotal sac in hindi

Prediction of Compressive Strength of Concrete: Machine Learning ...

WebAug 4, 2024 · Concrete Strength Prediction Using Different Machine Learning Processes: Effect of Slag, Fly Ash and Superplasticizer ... The RF algorithm was utilized in combination with PCA and PSO for the concrete strength prediction. The specific conclusions are as follows: (1) The R, EVS, MAE and MSE values on the original dataset … WebJun 10, 2024 · The development in computational methods can be used to obtain a rational relation between the materials used and the compressive strength using machine learning techniques which reduces the ... WebOct 26, 2024 · Currently, one of the topical areas of application of machine learning methods in the construction industry is the prediction of the mechanical properties of various building materials. In the future, algorithms with elements of artificial intelligence … pc health cje

Concrete Compressive Strength Prediction using Machine …

Predicting the Compressive Strength and the Effective ... - Springer

WebConcrete Compressive Strength Data Set. Download: Data Folder, Data Set Description. Abstract: Concrete is the most important material in civil engineering. The concrete compressive strength is a highly nonlinear function of age and ingredients. Data Set … WebJan 10, 2024 · Up to date, several ML algorithms are used for concrete compressive strength prediction, among which the most preferred ones are artificial neural network (ANN) and support vector machine (SVM). To name a few, Siddique et al. [13] used … scrotal shieldWebJan 27, 2024 · Accurate prediction of the compressive strength of concrete is of great significance to construction quality and progress. In order to understand the current research status in the concrete compressive strength prediction field, a bibliometric analysis of the relevant literature published in this field in the last decade was conducted first. The 3135 … scrotal shingles

"WebJul 21, 2024 · This study aims to implement a hybrid ensemble surrogate machine learning technique in predicting the compressive strength (CS) of concrete, an important parameter used for durability design and ... " - Concrete strength prediction machine learning

Concrete strength prediction machine learning

Machine learning models for predicting the …

WebConcrete is a building material that is most widely used because of its excellent mechanical performance and durability. Compressive strength is an essential property of concrete, which changes with time under various factors. In this paper, the time variation law of the compressive strength of concrete was reviewed from three aspects: single, multiple … WebJul 21, 2024 · Among them, the use of artificial neural networks to predict the compressive strength of concrete is more studied. For example, Garg A, Aggarwal P, Aggarwal Y, et al. [20], using SVM and GPR to ...

Did you know?

WebA sensitivity and robustness analysis of GPR and ANN for high-performance concrete compressive strength prediction using a Monte Carlo simulation. Sustainability 2024, 12, 830. [Google Scholar ... D.-Y.; Gupta, R. Machine learning-based prediction for compressive and flexural strengths of steel fiber-reinforced concrete. Constr. Build. … WebApr 11, 2024 · Therefore, some scholars tried to use ML methods to predict the basic mechanical properties of concrete, Tran et al. [27] used six ML models to predict and analyze the compressive strength of recycled concrete, and results showed that cement content and water consumption were the main factors affecting the compressive …

WebApr 7, 2024 · Keywords: green construction projects; external support; cost prediction; machine learning. ... Beams of high-strength concrete (f(cc) up to 90 MPa) were tested in shear and bending. Various types ... WebConcrete Compressive Strength Data Set. Download: Data Folder, Data Set Description. Abstract: Concrete is the most important material in civil engineering. The concrete compressive strength is a highly nonlinear function of age and ingredients. Data Set Characteristics: Multivariate. Number of Instances: 1030. Area:

WebMar 4, 2024 · Compressive strength is an important mechanical property of high-strength concrete (HSC), but testing methods are usually uneconomical, time-consuming, and labor-intensive. To this end, in this paper, a long short-term memory (LSTM) model was proposed to predict the HSC compressive strength using 324 data sets with five input independent … WebMar 24, 2024 · The compressive strength of high-performance concrete has exceeded 200 MPa. 28-d average strength between 100 to 120 MPa of high-performance concrete has been widely used in engineering. Compressive strength is one of the important …

WebApr 17, 2024 · Predictable compressive strength of concrete is essential for concrete structure utilisation and is the main feature of its safety and durability. Recently, machine learning is gaining significant attention and future predictions for this technology are even more promising.

WebAug 4, 2024 · Blast furnace slag (BFS) and fly ash (FA), as mining-associated solid wastes with good pozzolanic effects, can be combined with superplasticizer to prepare concrete with less cement utilization. … pc health check 电脑健康状况检查工具WebApr 14, 2024 · The durability of two types of widely used glass fiber reinforced polymer (GFRP) bars, one without coating (G1) and one with slightly surface sand-coating (G2), were studied through accelerated aging. Concrete cylinders reinforced with GFRP bars were immersed in tap water in temperature-controlled tanks. The influence of different … pc health check 削除WebJun 26, 2024 · In this investigation, an approach using a feedforward neural network (FNN) machine learning algorithm was proposed to predict the compressive strength of later-age concrete. The proposed model was fully evaluated in terms of performance and prediction capability over statistical results of 1000 simulations under a random sampling effect. pc health check 無料WebThis study also aims to contribute to the knowledge of the application of computational models in the prediction of compressive strength of concrete, using machine learning and pre-processing methods such as … scrotal shaveWebDec 27, 2024 · In the current studies, the machine learning-based model has been widely used in slope stability prediction , floods , prediction of mechanical properties of materials [10–12] and building structures [13, 14]. In addition, many researchers have explored the application of machine learning in concrete prediction of compressive strengths. scrotal shrinkerWebCompressive and flexural strength are the crucial properties of a material. The strength of recycled aggregate concrete (RAC) is comparatively lower than that of natural aggregate concrete. Several factors, including the recycled aggregate replacement ratio, parent concrete strength, water–cement ratio, water absorption, density of the recycled … scrotal sebaceous glandsWebSep 6, 2024 · This paper aims to develop a novel prediction tool based on the machine learning framework to evaluate the compressive strength and effective porosity of pervious concrete material from its compositions. To address this difficult task, 14 data sources were collected from the literature to build a dataset of 164 samples. The dataset included … pc health check 起動