Introduction
Lecture
1
Intro to ALS
These lecture notes accompany the book on ALS
They can be used with the book and the software
for courses on ALS and related subjects of:
Machine learning (ML);
System engineering (specifically, system
identification), SI;
Data mining, DM;
Statistical Analysis, SA;
Pattern Recognition including clustering,
classification, PR;
Fuzzy logic and fuzzy systems, including
neuro
-
fuzzy systems, FL;
ALS by P Angelov (c) 2013 Wiley LN1 Intro
2
Outline of the ALS course
20
-
30h lectures
20 h practical session using the EST
software
Lectures cover:
Introduction to ALS (1h)
Probability theory
-
basics (2h)
Machine Learning & Pattern recognition (2h)
Fuzzy Systems Theory
–
basics (2h)
Evolving System Structure (2h)
Parameters Learning (1h)
Autonomous Predictors/Estimators/Filters/
Inferential Sensors (1h)…
ALS by P Angelov (c) 2013 Wiley LN1 Intro
3
Outline of the ALS course …
…
AL Classifiers (1h)
AL Controllers (1h)
Collaborative ALS (1h)
AL Sensors
in (
Petro
-
) Chemical
industry
(1h)
ALS in Mobile Robotics (1h)
Autonomous Novelty Detection (1h)
Modelling Evolving user behaviour with ALS (1h)
Review (1h)
Tutorial (1h)
ALS by P Angelov (c) 2013 Wiley LN1 Intro
4
Outline of Lecture1
Introduction to ALS
Autonomous Systems (AS)
The role of Machine Learning (ML) in AS
System Identification
–
A World Model
System structure identification
Parameter identification
Novelty detection, outliers, structure identification
Online
vs
Offline
Adaptive and Evolving
Evolving
vs
Evolutionary
Supervised
vs
unsupervised learning
ALS by P Angelov (c) 2013 Wiley LN1 Intro
5
Introduction to ALS
ALS interacts with a number of well
established areas of research ( a non
exhaustive list is shown below):
ML
SI
DM
SA
PR
FL
ALS
ALS by P Angelov (c) 2013 Wiley LN1 Intro
6
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