BSI PD ISO/IEC TR 24372:2021:2022 Edition

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Information technology. Artificial intelligence (AI). Overview of computational approaches for AI systems

Published By	Publication Date	Number of Pages
BSI	2022	42

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PDF Catalog

PDF Pages	PDF Title
2	undefined
7	Foreword
8	Introduction
9	1 Scope 2 Normative references 3 Terms and definitions
10	4 Abbreviated terms
11	5 General
13	6 Main characteristics of AI systems 6.1 General
14	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
15	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
16	6.3.3 Algorithm-dependent
17	6.3.4 Multi-step or end-to-end learning-based 7 Types of AI computational approaches 7.1 General
18	7.2 Knowledge-driven approaches 7.3 Data-driven approaches
19	8 Selected algorithms and approaches used in AI systems 8.1 General 8.2 Knowledge engineering and representation 8.2.1 General
20	8.2.2 Ontology 8.2.3 Knowledge graph
22	8.2.4 Semantic web 8.3 Logic and reasoning 8.3.1 General
23	8.3.2 Inductive reasoning 8.3.3 Deductive inference
24	8.3.4 Hypothetical reasoning
25	8.3.5 Bayesian inference
26	8.4 Machine learning 8.4.1 General 8.4.2 Decision tree
27	8.4.3 Random forest
28	8.4.4 Linear regression
29	8.4.5 Logistic regression 8.4.6 K-nearest neighbour
30	8.4.7 Naïve Bayes 8.4.8 Feedforward neural network
31	8.4.9 Recurrent neural network
32	8.4.10 Long short-term memory network
33	8.4.11 Convolutional neural network
34	8.4.12 Generative adversarial network
35	8.4.13 Transfer learning 8.4.14 Bidirectional encoder representations from transformers
36	8.4.15 XLNet
37	8.5 Metaheuristics 8.5.1 General 8.5.2 Genetic algorithms
39	Bibliography