B.E. Electrical Engineering:Data Mining and Pattern Recognition

Thapar University
In Patiala

Price on request
You can also call the Study Centre
17523... More

Important information

Typology Bachelor
Start Patiala
Duration 4 Years
  • Bachelor
  • Patiala
  • Duration:
    4 Years
Description

Important information
Venues

Where and when

Starts Location
On request
Patiala
Thapar University P.O Box 32, 147004, Punjab, India
See map
Starts On request
Location
Patiala
Thapar University P.O Box 32, 147004, Punjab, India
See map

Course programme

First Year: Semester I

Mathematics I
Engineering graphics
Computer Programming
Physics
Solid Mechanics
Communication Skills

First Year: Semester-II

Mathematics II
Manufacturing Process
Chemistry
Electrical and Electronic Science
Thermodynamics
Organizational Behavior


Second Year- Semester - I

Semiconductor Devices
Measurement Science and Techniques
Digital Electronic Circuits
Circuit Theory
Electromechanical Energy conversion
Electromagnetic Fields
Human Values, Ethics and IPR

Second Year- Semester – II

Numerical and Statistical Methods
Fluid Mechanics
Power Generation and Economics
Analog Electronic Circuits
Electrical and Electronic Measurements
Transmission and Distribution of Power
Environmental Studies

Third Year- Semester – I

Power Electronics
Asynchronous Machines
Switch gear and Protection
Microprocessors
Optimization Techniques
Engineering Economics
Summer Training (6 Weeks after 2nd year during summer vacation)


Third Year- Semester – II

Total Quality Management
Control Systems
Synchronous Machines
Power System Analysis
Flexible AC Transmission Systems


Fourth Year- Semester – I

High Voltage Engineering
Operation and Control of Power Systems
Electric Drives
Intelligent Algorithms in Power Systems


Fourth Year- Semester – II

Project Semester
Project
Industrial Training

Data Mining and Pattern Recognition

Data Mining: What is data mining, on what kind of data, Data Mining Functionalities

Data Warehouse: Difference Between operational database systems and data warehouses, A multidimensional data model, Data Warehouse architecture, data warehouse architecture, Data Warehouse implementation

Data preprocessing: Data cleaning, data integration & transformation, data reduction

Data Mining Query Language

Characterization & Comparison, Generalization, Mining association rules in large databases, constraint based association Mining

Classification & prediction Classification by decision Tree Induction, Bayesian classification, classification by Back propagation

Cluster analysis Partitioning Methods, Hierarchical methods, and Density & Grid based methods

Mining complex types of data, applications & trends in data mining, Social impacts of data mining

Pattern recognition: its importance & applications, applications in Bioinformatics, recognizing important bioinformatic sequences, other applications of pattern discovery

Laboratory Work: Implementation of various data mining techniques like classification, clustering, generalization, cleaning etc.

Achievements for this centre


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