EE5654 Intelligent Systems

To understand the full range of state-of-the-art intelligent systems techniques.

To raise critical awareness of the issues affecting the performance of intelligent systems.

To develop the skills required to develop intelligent software using MATLAB/Simulink.

To gain hands-on experiences through learning, applying and implementing intelligent systems to a given problem.

Modelling (neural network, fuzzy systems, neuro-fuzzy systems)

Classifications (Support vector machine, Bay’s theorem, Fuzzy C mean) Optimisation

Evolutionary Computing: (Genetic Algorithm, Evolutionary Algorithm, Genetic Programming, Genetic Folding)

Swarm Optimisation: (Particle Swarm Optimisation, Bee algorithm, Ant colony, Bacterial foraging, Immune Systems, Firefly Algorithm)

Introduction to Intelligent Systems

What is an intelligent system?

Significance of intelligent systems in business  Characteristics of intelligent systems

The field of Artificial Intelligence (AI)

The Soft Computing paradigm

An Overview of Intelligent System Methodologies

Characteristics of intelligent systems

Possess one or more of these:

Capability to extract and stored knowledge  Human like reasoning process Learning from experience (or training) Dealing with imprecise expressions of facts Finding solutions through processes similar to natural evolution

Recent trend More sophisticated Interaction with the user through  natural language understanding speech recognition and synthesis image analysis

Most current intelligent systems are based on  rule based expert systems  one or more of the methodologies belonging to soft computing

The field of Artificial Intelligence (AI)

Primary goal:

Development of software aimed at enabling machines to solve problems through human-like reasoning

Attempts to build systems based on a model of knowledge representation and processing in the human mind

Encompasses study of the brain to understand its structure and functions

In existence as a discipline since 1956

Failed to live up to initial expectations due to inadequate understanding of intelligence, brain function complexity of problems to be solved

Expert systems – an AI success story of the 1980s Case Based Reasoning systems - partial success

The Soft Computing (SC) paradigm

Also known as Computational Intelligence

Unlike conventional computing, SC techniques  can be tolerant of imprecise, incomplete or corrupt input data solve problems without explicit solution steps learn the solution through repeated observation and adaptation can handle information expressed in vague linguistic terms arrive at an acceptable solution through evolution

Data mining (cont’d)

Note: This goes far beyond simple statistical analysis of numerical data, to classification and analysis of non-numerical data
 Such information might  reveal important underlying trends and associations in market behaviour, and help gain competitive advantage by improving marketing effectiveness
 Techniques such as artificial neural networks and decision trees have made it possible to perform data mining involving large volumes of data (from "data warehouses").

Growing interest in applying data mining in areas such direct target marketing campaigns, fraud detection, and development of models to aid in financial predictions, antiterrorism systems

The process of exploring and analysing data for discovering new and useful information

Huge volumes of mostly point-of-sale (POS) data are generated or captured electronically every day, eg,  data generated by bar code scanners customer call detail databases web log files in e-commerce etc.

Organizations are ending up with huge amounts of mostly day-to-day transaction data

Learning Outcomes

Demonstrate the ability to plan, develop, and manage a project from inception through to completion.

·Shown in the completion of the WRIT1 proposal including a working title, research rationale, aims and objectives of the research, indicative bibliography, and research timetable. Also shown in the completion of the WRIT2 research project in line with the proposal.

Extend their research skills required to complete academic work including; accessing print and online library resources, notetaking, and the use of Harvard referencing.

·Demonstrated by the ability to select appropriate sources, and to correctly reference relevant source materials from academic books, journal articles and online materials in order to present clear, supported evidence.

Communicate clearly and appropriately for academic and professional purposes

·Demonstrated through the structuring of the WRIT2 research project, and the use of academic language.

Analyse relevant sources and use them to create a structured argument / critical commentary regarding a research product

·Demonstrated through the summarising of material and present clear logical arguments using the supporting evidence presented.