[HTML][HTML] State-of-the-art review of soft computing applications in underground excavations
Soft computing techniques are becoming even more popular and particularly amenable to
model the complex behaviors of most geotechnical engineering systems since they have …
model the complex behaviors of most geotechnical engineering systems since they have …
Artificial intelligence based models for stream-flow forecasting: 2000–2015
Summary The use of Artificial Intelligence (AI) has increased since the middle of the 20th
century as seen in its application in a wide range of engineering and science problems. The …
century as seen in its application in a wide range of engineering and science problems. The …
Predictive modeling of swell-strength of expansive soils using artificial intelligence approaches: ANN, ANFIS and GEP
This study presents the development of new empirical prediction models to evaluate swell
pressure and unconfined compression strength of expansive soils (P s UCS-ES) using three …
pressure and unconfined compression strength of expansive soils (P s UCS-ES) using three …
Estimation of strength, rheological parameters, and impact of raw constituents of alkali-activated mortar using machine learning and SHapely Additive exPlanations …
One-part alkali-activated material (AAM) is a new eco-friendly developed low-carbon binder
that utilizes alkaline activators in solid form. This study deals with the experimental synthesis …
that utilizes alkaline activators in solid form. This study deals with the experimental synthesis …
[HTML][HTML] Machine learning interpretable-prediction models to evaluate the slump and strength of fly ash-based geopolymer
This study used three artificial intelligence-based algorithms–adaptive neuro-fuzzy inference
system (ANFIS), artificial neural networks (ANNs), and gene expression programming (GEP) …
system (ANFIS), artificial neural networks (ANNs), and gene expression programming (GEP) …
Stream-flow forecasting using extreme learning machines: a case study in a semi-arid region in Iraq
Monthly stream-flow forecasting can yield important information for hydrological applications
including sustainable design of rural and urban water management systems, optimization of …
including sustainable design of rural and urban water management systems, optimization of …
[HTML][HTML] DeepGR4J: A deep learning hybridization approach for conceptual rainfall-runoff modelling
Despite the considerable success of deep learning methods in modelling physical
processes, they suffer from a variety of issues such as overfitting and lack of interpretability …
processes, they suffer from a variety of issues such as overfitting and lack of interpretability …
[HTML][HTML] A data-driven approach to predict the compressive strength of alkali-activated materials and correlation of influencing parameters using SHapley Additive …
This research used gene expression programming (GEP) and multi expression
programming (MEP) to determine the compressive strength (CS) of alkali-activated material …
programming (MEP) to determine the compressive strength (CS) of alkali-activated material …
Modeling slump of ready mix concrete using genetic algorithms assisted training of Artificial Neural Networks
The paper explores the usefulness of hybridizing two distinct nature inspired computational
intelligence techniques viz., Artificial Neural Networks (ANN) and Genetic Algorithms (GA) …
intelligence techniques viz., Artificial Neural Networks (ANN) and Genetic Algorithms (GA) …
Genetic programming in water resources engineering: A state-of-the-art review
The state-of-the-art genetic programming (GP) method is an evolutionary algorithm for
automatic generation of computer programs. In recent decades, GP has been frequently …
automatic generation of computer programs. In recent decades, GP has been frequently …