Fig. 1.
Artificial intelligence methods used with BIM in publications according to the Scopus database (own research)
| No | AI techniques in BIM – main groups | Subdivision of method groups | AI methods used in combination with BIM | Total number of publications | Number of Construction Management (CM) publications |
|---|---|---|---|---|---|
| 1 | Knowledge based Reasoning | – | Rule based Reasoning | 60 | 15 |
| 2 | – | Case based Reasoning | 79 | 32 | |
| 3 | Metaheuristics | Evolutionary Algorithm | Genetic Algorithm | 221 | 58 |
| 4 | Swarm Intelligence | Particle Swarm Optimization | 45 | 11 | |
| 5 | Ant Colony Optimization | 28 | 6 | ||
| 6 | Firefly Algorithm | 4 | 2 | ||
| 7 | Simulated Annealing | 24 | 2 | ||
| 8 | Symbiotic Organisms Search | 3 | 0 | ||
| 9 | Machine Learning | Supervised Learning | Artificial Neural Network | 135 | 33 |
| 10 | Convolutional Neural Network | 120 | 16 | ||
| 11 | Recurrent Neural Network | 16 | 2 | ||
| 12 | Unsupervised Learning | K Nearest Neighbor | 16 | 2 | |
| 13 | Support Vector Machine | 46 | 10 | ||
| 14 | Decision Tree | 50 | 9 | ||
| 15 | K Means Clustering | 17 | 5 | ||
| 16 | Hierarchical Clustering | 14 | 1 | ||
| 17 | Network Clustering | 39 | 18 | ||
| 18 | Frequent Pattern Mining | 3 | 2 | ||
| 19 | Sequential Pattern Mining | 3 | 1 | ||
| 20 | Hybrid AI | Computer Vision | Image Processing | 301 | 45 |
| 21 | Feature Extraction | 129 | 17 | ||
| 22 | Registration | 227 | 43 | ||
| 23 | Natural Language Processing | Lexical Analysis | 0 | 0 | |
| 24 | Syntactic Analysis | 7 | 1 | ||
| 25 | Semantic Analysis | 353 | 80 | ||
| 26 | AI Robotics | Data Collection Robot | 17 | 5 | |
| 27 | Manufacture Robot | 10 | 1 |
Relationships between authors and the most frequently occurring keywords for the analysed publications in the field of construction – top 10 methods (own research)
| AI methods used in combination with BIM | Total number of authors | Clusters | Links | Total link strength | Keywords (min. 5 occurrences) |
|---|---|---|---|---|---|
| SEA – Semantic Analysis | 1052 | 224 | 2059 | 2170 | 166 |
| IP – Image Processing | 898 | 223 | 1708 | 1807 | 135 |
| R – Registration | 784 | 147 | 2494 | 2615 | 99 |
| GA – Genetic Algorithm | 633 | 164 | 1113 | 1171 | 97 |
| FE – Feature Extraction | 396 | 105 | 741 | 785 | 57 |
| CNN – Convolutional Neural Network | 374 | 90 | 703 | 742 | 51 |
| CBR – Case based Reasoning | 227 | 64 | 355 | 379 | 30 |
| RBR – Rule based Reasoning | 183 | 52 | 271 | 288 | 28 |
| DT – Decision Tree | 149 | 37 | 276 | 281 | 17 |
| PSO – Particle Swarm Optimization | 144 | 35 | 262 | 278 | 17 |
Relationships between authors and the most frequently occurring keywords for the analysed publications in the field of construction (own research)
| Abbreviation | Total number of authors | Clusters | Links | Total link strength | Kewords (min. 5 occurrences) |
|---|---|---|---|---|---|
| RBR – Rule based Reasoning | 47 | 13 | 69 | 75 | 4 |
| CBR – Case based Reasoning | 82 | 26 | 111 | 119 | 14 |
| GA – Genetic Algorithm | 126 | 42 | 163 | 169 | 22 |
| PSO – Particle Swarm Optimization | 37 | 11 | 59 | – | 3 |
| ANN – Artificial Neural Network | 36 | 7 | 83 | – | 0 |
| CNN – Convolutional Neural Network | 54 | 13 | 101 | – | 5 |
| IP – Image Processing | 119 | 33 | 187 | 194 | 23 |
| FE – Feature Extraction | 48 | 15 | 75 | 76 | 6 |
| R – Registration | 111 | 25 | 227 | 236 | 14 |
| SEA – Semantic Analysis | 259 | 66 | 493 | 509 | 30 |