4.7 Article

Reduction of computational error by optimizing SVR kernel coefficients to simulate concrete compressive strength through the use of a human learning optimization algorithm

Related references

Note: Only part of the references are listed.
Article Computer Science, Interdisciplinary Applications

A new hybrid grey wolf optimizer-feature weighted-multiple kernel-support vector regression technique to predict TBM performance

Haiqing Yang et al.

Summary: A new hybrid intelligence technique was introduced to predict the performance of the full-face tunnel boring machine (TBM). By measuring and considering the important parameters, a predictive model was established and evaluated. The results showed that the model had high accuracy in predicting the TBM performance.

ENGINEERING WITH COMPUTERS (2022)

Article Engineering, Geological

Statistical variations and new correlation models to predict the mechanical behaviour of the cement mortar modified with silica fume

Kawan Ghafor et al.

Summary: This study comprehensively investigates the effect of silica fume content, curing time and water to cement ratio on the mechanical properties of cement mortar. The results show that the effect of silica fume content on increasing compressive strength is minimal.

GEOMECHANICS AND GEOENGINEERING-AN INTERNATIONAL JOURNAL (2022)

Article Computer Science, Interdisciplinary Applications

Investigating the effective parameters on the risk levels of rockburst phenomena by developing a hybrid heuristic algorithm

Jian Zhou et al.

Summary: This paper integrates the firefly algorithm and artificial neural network to accurately predict the risk of rockburst in deep mines and tunnels. The hybrid model successfully determines different hazard levels under various conditions and offers new solutions for classification based on success rates.

ENGINEERING WITH COMPUTERS (2021)

Article Construction & Building Technology

Soft computing techniques: Systematic multiscale models to predict the compressive strength of HVFA concrete based on mix proportions and curing times

Ahmed Mohammed et al.

Summary: This study aims to evaluate and model the hardness of concrete mixtures with high-volume fly ash (HVFA) to meet environmental design standards, and establish systematic multiscale models to predict the compressive strength of HVFA concrete mixes, using various technical approaches for analysis and modeling.

JOURNAL OF BUILDING ENGINEERING (2021)

Article Construction & Building Technology

Anti-rutting performance of the damping asphalt mixtures (DAMs) made with a high content of asphalt rubber (AR)

Jiandong Huang et al.

Summary: The research evaluates the mechanical properties and rutting resistance of two DAMs designed based on OG aggregate structure. The results show that DAMs have high damping characteristics and exhibit better rutting resistance in HWT samples compared to traditional mixtures.

CONSTRUCTION AND BUILDING MATERIALS (2021)

Article Engineering, Civil

A novel approach for classification of soils based on laboratory tests using Adaboost, Tree and ANN modeling

Binh Thai Pham et al.

Summary: This research presents new models for classifying soil types based on Adaboost classifiers, which can increase accuracy and reduce project costs.

TRANSPORTATION GEOTECHNICS (2021)

Article Geosciences, Multidisciplinary

Predicting TBM penetration rate in hard rock condition: A comparative study among six XGB-based metaheuristic techniques

Jian Zhou et al.

Summary: This study aimed to develop hybrid models to predict TBM performance, with PSO-XGB technique identified as the best predictive model. Sensitivity analysis revealed that UCS, BTS, and TFC have the greatest impact on TBM performance.

GEOSCIENCE FRONTIERS (2021)

Article Engineering, Civil

Estimation of the TBM advance rate under hard rock conditions using XGBoost and Bayesian optimization

Jian Zhou et al.

Summary: In this study, a hybrid model of XGBoost with BO was used to improve the accuracy of predicting TBM AR under hard rock conditions. By collecting data from an actual tunnel project in Malaysia, the proposed BO-XGBoost model demonstrated high accuracy in predicting TBM AR. The study also showed that machine parameters have the greatest impact on TBM AR compared to rock mass and material properties.

UNDERGROUND SPACE (2021)

Article Computer Science, Interdisciplinary Applications

A new methodology for optimization and prediction of rate of penetration during drilling operations

Yanru Zhao et al.

ENGINEERING WITH COMPUTERS (2020)

Article Computer Science, Interdisciplinary Applications

A Monte Carlo simulation approach for effective assessment of flyrock based on intelligent system of neural network

Jian Zhou et al.

ENGINEERING WITH COMPUTERS (2020)

Article Engineering, Geological

Effect of Water Content on Argillization of Mudstone During the Tunnelling process

Bolong Liu et al.

ROCK MECHANICS AND ROCK ENGINEERING (2020)

Article Green & Sustainable Science & Technology

Influencing factors analysis and forecasting of residential energy-related CO2 emissions utilizing optimized support vector machine

Lei Wen et al.

JOURNAL OF CLEANER PRODUCTION (2020)

Article Computer Science, Interdisciplinary Applications

The use of new intelligent techniques in designing retaining walls

Mohammadreza Koopialipoor et al.

ENGINEERING WITH COMPUTERS (2020)

Article Engineering, Environmental

Forecasting of TBM advance rate in hard rock condition based on artificial neural network and genetic programming techniques

Jian Zhou et al.

BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT (2020)

Article Multidisciplinary Sciences

Re-epithelialization and immune cell behaviour in an ex vivo human skin model

Ana Rakita et al.

SCIENTIFIC REPORTS (2020)

Article Chemistry, Multidisciplinary

Seepage Analysis in Short Embankments Using Developing a Metaheuristic Method Based on Governing Equations

Dongchun Tang et al.

APPLIED SCIENCES-BASEL (2020)

Article Construction & Building Technology

Mapping and holistic design of natural hydraulic lime mortars

Maria Apostolopoulou et al.

CEMENT AND CONCRETE RESEARCH (2020)

Article Chemistry, Multidisciplinary

Effect of Modifiers on the Rutting, Moisture-Induced Damage, and Workability Properties of Hot Mix Asphalt Mixtures

Jiandong Huang et al.

APPLIED SCIENCES-BASEL (2020)

Article Construction & Building Technology

Predicting the Permeability of Pervious Concrete Based on the Beetle Antennae Search Algorithm and Random Forest Model

Jiandong Huang et al.

ADVANCES IN CIVIL ENGINEERING (2020)

Article Materials Science, Multidisciplinary

ANN, M5P-tree and nonlinear regression approaches with statistical evaluations to predict the compressive strength of cement-based mortar modified with fly ash

Ahmed Mohammed et al.

JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T (2020)

Article Computer Science, Interdisciplinary Applications

A combination of artificial bee colony and neural network for approximating the safety factor of retaining walls

Ebrahim Noroozi Ghaleini et al.

ENGINEERING WITH COMPUTERS (2019)

Article Computer Science, Artificial Intelligence

Applying various hybrid intelligent systems to evaluate and predict slope stability under static and dynamic conditions

Mohammadreza Koopialipoor et al.

SOFT COMPUTING (2019)

Article Environmental Sciences

Developing a new intelligent technique to predict overbreak in tunnels using an artificial bee colony-based ANN

Mohammadreza Koopialipoor et al.

ENVIRONMENTAL EARTH SCIENCES (2019)

Article Engineering, Civil

Prediction of Scour Depth below River Pipeline using Support Vector Machine

Abbas Parsaie et al.

KSCE JOURNAL OF CIVIL ENGINEERING (2019)

Article Engineering, Environmental

Application of deep neural networks in predicting the penetration rate of tunnel boring machines

Mohammadreza Koopialipoor et al.

BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT (2019)

Article Computer Science, Artificial Intelligence

Artificial bee colony-based neural network for the prediction of the fundamental period of infilled frame structures

Panagiotis G. Asteris et al.

NEURAL COMPUTING & APPLICATIONS (2019)

Article Engineering, Environmental

Model tree approach for predicting uniaxial compressive strength and Young's modulus of carbonate rocks

Ebrahim Ghasemi et al.

BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT (2018)

Article Engineering, Geological

Model test on the entrainment phenomenon and energy conversion mechanism of flow-like landslides

H. Q. Yang et al.

ENGINEERING GEOLOGY (2018)

Article Engineering, Geological

Investigation on the Cracking Character of Jointed Rock Mass Beneath TBM Disc Cutter

Haiqing Yang et al.

ROCK MECHANICS AND ROCK ENGINEERING (2018)

Article Construction & Building Technology

Effects of joints on the cutting behavior of disc cutter running on the jointed rock mass

H. Q. Yang et al.

TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY (2018)

Article Computer Science, Artificial Intelligence

A human learning optimization algorithm and its application to multi-dimensional knapsack problems

Ling Wang et al.

APPLIED SOFT COMPUTING (2015)

Article Engineering, Geological

Analysis of the excavation damaged zone around a tunnel accounting for geostress and unloading

H. Q. Yang et al.

INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES (2014)

Article Geosciences, Multidisciplinary

Study of the influence of geotechnical parameters on the TBM performance in Tehran-Shomal highway project using ANN and SPSS

S. R. Torabi et al.

ARABIAN JOURNAL OF GEOSCIENCES (2013)

Article Computer Science, Artificial Intelligence

Evaluation of effect of blast design parameters on flyrock using artificial neural networks

M. Monjezi et al.

NEURAL COMPUTING & APPLICATIONS (2013)

Article Computer Science, Artificial Intelligence

Backbreak prediction in the Chadormalu iron mine using artificial neural network

M. Monjezi et al.

NEURAL COMPUTING & APPLICATIONS (2013)

Article Geosciences, Multidisciplinary

Prediction of flyrock and backbreak in open pit blasting operation: a neuro-genetic approach

M. Monjezi et al.

ARABIAN JOURNAL OF GEOSCIENCES (2012)

Article Engineering, Geological

Optimization of Open pit Blast Parameters using Genetic Algorithm

M. Monjezi et al.

INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES (2011)

Article Construction & Building Technology

Influence of silica fume on the tensile strength of concrete

S Bhanja et al.

CEMENT AND CONCRETE RESEARCH (2005)

Article Construction & Building Technology

Effect of supplementary cementitious materials on the compressive strength and durability of short-term cured concrete

H Toutanji et al.

CEMENT AND CONCRETE RESEARCH (2004)

Article Construction & Building Technology

Effect of silica fume on mechanical properties of high-strength concrete

M Mazloom et al.

CEMENT & CONCRETE COMPOSITES (2004)

Article Engineering, Civil

Predicting the shear strength of reinforced concrete beams using artificial neural networks

MY Mansour et al.

ENGINEERING STRUCTURES (2004)