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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Format: | Electronic Book Chapter |
Language: | English |
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Basel
MDPI - Multidisciplinary Digital Publishing Institute
2023
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Online Access: | DOAB: download the publication DOAB: description of the publication |
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100 | 1 | |a Armaghani, Danial Jahed |4 edt | |
700 | 1 | |a Zhang, Yixia |4 edt | |
700 | 1 | |a Samui, Pijush |4 edt | |
700 | 1 | |a Elshafie, Ahmed Hussein Kamel Ahmed |4 edt | |
700 | 1 | |a Azizi, Aydin |4 edt | |
700 | 1 | |a Armaghani, Danial Jahed |4 oth | |
700 | 1 | |a Zhang, Yixia |4 oth | |
700 | 1 | |a Samui, Pijush |4 oth | |
700 | 1 | |a Elshafie, Ahmed Hussein Kamel Ahmed |4 oth | |
700 | 1 | |a Azizi, Aydin |4 oth | |
245 | 1 | 0 | |a Novel Hybrid Intelligence Techniques in Engineering |
260 | |a Basel |b MDPI - Multidisciplinary Digital Publishing Institute |c 2023 | ||
300 | |a 1 electronic resource (456 p.) | ||
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506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
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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546 | |a English | ||
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653 | |a confinement of concrete | ||
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653 | |a travel mode choice data | ||
653 | |a hybrid support vector machine-based model | ||
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653 | |a soft computing | ||
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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 | ||
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653 | |a incremental granular model | ||
653 | |a interval-based fuzzy c-means clustering | ||
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653 | |a performance index | ||
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653 | |a linear genetic programming | ||
653 | |a bagged regression tree | ||
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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 | ||
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653 | |a usage frequency prediction | ||
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653 | |a taxonomy | ||
856 | 4 | 0 | |a www.oapen.org |u https://mdpi.com/books/pdfview/book/7091 |7 0 |z DOAB: download the publication |
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 |