{"id":394328,"date":"2024-10-20T04:13:31","date_gmt":"2024-10-20T04:13:31","guid":{"rendered":"https:\/\/pdfstandards.shop\/product\/uncategorized\/bsi-pd-iso-iec-tr-243722021\/"},"modified":"2024-10-26T07:53:45","modified_gmt":"2024-10-26T07:53:45","slug":"bsi-pd-iso-iec-tr-243722021","status":"publish","type":"product","link":"https:\/\/pdfstandards.shop\/product\/publishers\/bsi\/bsi-pd-iso-iec-tr-243722021\/","title":{"rendered":"BSI PD ISO\/IEC TR 24372:2021"},"content":{"rendered":"
PDF Pages<\/th>\n | PDF Title<\/th>\n<\/tr>\n | ||||||
---|---|---|---|---|---|---|---|
2<\/td>\n | undefined <\/td>\n<\/tr>\n | ||||||
7<\/td>\n | Foreword <\/td>\n<\/tr>\n | ||||||
8<\/td>\n | Introduction <\/td>\n<\/tr>\n | ||||||
9<\/td>\n | 1 Scope 2 Normative references 3 Terms and definitions <\/td>\n<\/tr>\n | ||||||
10<\/td>\n | 4 Abbreviated terms <\/td>\n<\/tr>\n | ||||||
11<\/td>\n | 5 General <\/td>\n<\/tr>\n | ||||||
13<\/td>\n | 6 Main characteristics of AI systems 6.1 General <\/td>\n<\/tr>\n | ||||||
14<\/td>\n | 6.2 Typical characteristics of AI systems 6.2.1 Adaptable 6.2.2 Constructive 6.2.3 Coordinated 6.2.4 Dynamic 6.2.5 Explainable 6.2.6 Discriminative or generative 6.2.7 Introspective <\/td>\n<\/tr>\n | ||||||
15<\/td>\n | 6.2.8 Trained or trainable 6.2.9 Accommodating various data 6.3 Computational characteristics of AI systems 6.3.1 Data-based or knowledge-based 6.3.2 Infrastructure-based <\/td>\n<\/tr>\n | ||||||
16<\/td>\n | 6.3.3 Algorithm-dependent <\/td>\n<\/tr>\n | ||||||
17<\/td>\n | 6.3.4 Multi-step or end-to-end learning-based 7 Types of AI computational approaches 7.1 General <\/td>\n<\/tr>\n | ||||||
18<\/td>\n | 7.2 Knowledge-driven approaches 7.3 Data-driven approaches <\/td>\n<\/tr>\n | ||||||
19<\/td>\n | 8 Selected algorithms and approaches used in AI systems 8.1 General 8.2 Knowledge engineering and representation 8.2.1 General <\/td>\n<\/tr>\n | ||||||
20<\/td>\n | 8.2.2 Ontology 8.2.3 Knowledge graph <\/td>\n<\/tr>\n | ||||||
22<\/td>\n | 8.2.4 Semantic web 8.3 Logic and reasoning 8.3.1 General <\/td>\n<\/tr>\n | ||||||
23<\/td>\n | 8.3.2 Inductive reasoning 8.3.3 Deductive inference <\/td>\n<\/tr>\n | ||||||
24<\/td>\n | 8.3.4 Hypothetical reasoning <\/td>\n<\/tr>\n | ||||||
25<\/td>\n | 8.3.5 Bayesian inference <\/td>\n<\/tr>\n | ||||||
26<\/td>\n | 8.4 Machine learning 8.4.1 General 8.4.2 Decision tree <\/td>\n<\/tr>\n | ||||||
27<\/td>\n | 8.4.3 Random forest <\/td>\n<\/tr>\n | ||||||
28<\/td>\n | 8.4.4 Linear regression <\/td>\n<\/tr>\n | ||||||
29<\/td>\n | 8.4.5 Logistic regression 8.4.6 K-nearest neighbour <\/td>\n<\/tr>\n | ||||||
30<\/td>\n | 8.4.7 Na\u00efve Bayes 8.4.8 Feedforward neural network <\/td>\n<\/tr>\n | ||||||
31<\/td>\n | 8.4.9 Recurrent neural network <\/td>\n<\/tr>\n | ||||||
32<\/td>\n | 8.4.10 Long short-term memory network <\/td>\n<\/tr>\n | ||||||
33<\/td>\n | 8.4.11 Convolutional neural network <\/td>\n<\/tr>\n | ||||||
34<\/td>\n | 8.4.12 Generative adversarial network <\/td>\n<\/tr>\n | ||||||
35<\/td>\n | 8.4.13 Transfer learning 8.4.14 Bidirectional encoder representations from transformers <\/td>\n<\/tr>\n | ||||||
36<\/td>\n | 8.4.15 XLNet <\/td>\n<\/tr>\n | ||||||
37<\/td>\n | 8.5 Metaheuristics 8.5.1 General 8.5.2 Genetic algorithms <\/td>\n<\/tr>\n | ||||||
39<\/td>\n | Bibliography <\/td>\n<\/tr>\n<\/table>\n","protected":false},"excerpt":{"rendered":" Information technology. Artificial intelligence (AI). Overview of computational approaches for AI systems<\/b><\/p>\n |