Novel Hybrid Intelligence Techniques in Engineering

The focus of this reprint is the development of novel intelligence techniques for solving various problems in engineering. These techniques, due to their ability to create complex relationships between dependent and independent variables, can be implemented in a faster and more reliable way. Such te...

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Bibliographic Details
Other Authors: Armaghani, Danial Jahed (Editor), Zhang, Yixia (Editor), Samui, Pijush (Editor), Elshafie, Ahmed Hussein Kamel Ahmed (Editor), Azizi, Aydin (Editor)
Format: Electronic Book Chapter
Language:English
Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2023
Subjects:
SCC
Online Access:DOAB: download the publication
DOAB: description of the publication
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520 |a The focus of this reprint is the development of novel intelligence techniques for solving various problems in engineering. These techniques, due to their ability to create complex relationships between dependent and independent variables, can be implemented in a faster and more reliable way. Such techniques utilise algorithms/approaches such as artificial neural networks, fuzzy logic, evolutionary theory, learning theory, and probabilistic theory, making them a suitable and useful fit for real-life complex problems. This reprint introduces the process of selecting, applying, and developing such techniques in different engineering designs and applications. In addition, the validation process of intelligence systems as an alternative is discussed in this reprint. Overall, this reprint forms an excellent introduction to these systems for engineers who are not familiar with them. 
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653 |a confinement of concrete 
653 |a CFST composite column 
653 |a artificial intelligence 
653 |a gene-expression programming 
653 |a hybrid techniques 
653 |a finite element method (FEM) 
653 |a imbalanced data 
653 |a travel mode choice data 
653 |a hybrid support vector machine-based model 
653 |a rock excavation 
653 |a soft computing 
653 |a cutter life index 
653 |a rock strength 
653 |a brittleness 
653 |a classification 
653 |a slope stability 
653 |a tree-based models 
653 |a random forest 
653 |a AdaBoost 
653 |a decision tree 
653 |a 3D bridge model 
653 |a IFC-based bridge model 
653 |a engineering document 
653 |a document fragment 
653 |a integrated operation 
653 |a granular model 
653 |a incremental granular model 
653 |a interval-based fuzzy c-means clustering 
653 |a coverage 
653 |a specificity 
653 |a performance index 
653 |a piezocone 
653 |a soil classification 
653 |a fuzzy C-means clustering 
653 |a neuro-fuzzy 
653 |a scratch-resistant 
653 |a hydrophobic 
653 |a GPTES 
653 |a transparent 
653 |a sol-gel 
653 |a blasting 
653 |a ground vibration 
653 |a PPV prediction 
653 |a whale optimization algorithm 
653 |a salp swarm optimizer 
653 |a spread foundation 
653 |a retaining structures 
653 |a economic design 
653 |a rock brittleness 
653 |a linear genetic programming 
653 |a bagged regression tree 
653 |a lazy machine learning method 
653 |a SCC 
653 |a compressive strength 
653 |a fly ash 
653 |a statistical analysis 
653 |a modeling 
653 |a blockchain technology 
653 |a intelligent technology 
653 |a internet of vehicles 
653 |a malicious nodes 
653 |a identification algorithm 
653 |a inverse analysis 
653 |a hydraulic conductivities 
653 |a Gray Wolf Optimizer 
653 |a thermal conductivity 
653 |a geothermal systems 
653 |a gene expression programming (GEP) 
653 |a non-linear multivariable regression (NLMR) 
653 |a P-wave 
653 |a porosity 
653 |a backpropagation neural network 
653 |a blast-induced ground vibration 
653 |a Gaussian process regression 
653 |a green campus 
653 |a shared free-floating electric scooter 
653 |a usage frequency prediction 
653 |a battery electric 
653 |a battery pack 
653 |a energy performance 
653 |a simulation 
653 |a second life batteries 
653 |a off-grid PV system 
653 |a residential building 
653 |a EV charging station 
653 |a optimization 
653 |a metaheuristic algorithms 
653 |a streamflow forecasting 
653 |a concrete 
653 |a water-reducer contents 
653 |a workability 
653 |a slump retention 
653 |a conceptual framework 
653 |a crowd-machine hybrid interaction 
653 |a design implications 
653 |a hybrid intelligence 
653 |a survey 
653 |a taxonomy 
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856 4 0 |a www.oapen.org  |u https://directory.doabooks.org/handle/20.500.12854/99998  |7 0  |z DOAB: description of the publication