B.E. Electronics(Instrumentation Control):Artificial Intelligence Techniques and Applications

Thapar University
In Patiala

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Important information

  • 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
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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

Electromagnetic Fields
Human Values, Ethics and IPR
Semiconductor Devices
Measurement Science and Techniques
Circuit Theory
Digital Electronic Circuits
Electrical Machines


Second year: Semester II

Fluid Mechanics
Computer System Architecture
Optimization Techniques
Analog Electronic Circuits
Numerical and Statistical Methods
Electrical and Electronic Measurements
Environmental Studies


Third year: Semester I

Elements and Analysis of Instrumentation System
Analytical Instrumentation
Signals and Systems
Power Electronics
Microprocessors
Biomedical instrumentation
Summer Training

Third year: Semester II

Data Acquisition Systems
Industrial Measurements
Process Dynamics and Control
Control Systems
Total Quality Management


Fourth year: Semester I

Advance Process Control
Virtual Instrumentation
Instrumentation System Design
Engineering Economics
Microelectronics and ICs

Fourth year: Semester II

Project Semester
Project
Industrial Training(6 weeks)


Artificial Intelligence Techniques and Application

Overview of Artificial Intelligence: The concept and importance of AI, fields related to AI human intelligence vs machine intelligence

Knowledge and general Concepts: General concept of knowledge, Acquisition, Knowledge Representation and organization: Prepositional and Predicate Logic, Theorem Proving, Structured Knowledge representation using Semantic Networks, Frames, Scripts,, Conceptual Graphs, Conceptual Dependencies, Knowledge Manipulation: Search space control, Uninformed search, Depth first search, Breadth first search, Depth first search with iterative deepening, Heuristic Search :Minimax Search procedure

Expert Systems: Expert systems: advantages, disadvantages, Expert system architecture, functions of various parts, Mechanism and role of inference engine, Types of Expert system, Tuning of expert systems, Role of Expert systems in instrumentation and process control

Overview of AI languages

Artificial Neural Networks: History of neural networks, Structure and function of a single neuron, biological neurons, artificial neuron models, Types of activation functions, Neural network architectures: Fully connected, layered, acyclic, feed forward, Neural learning : correlation, competitive, evaluation of networks; Supervised learning: Back propagation algorithm, Unsupervised learning, winner-take all networks, adaptive resonance theory, Application areas of neural networks : classification, clustering, pattern associations, function approximation, forecasting.

Fuzzy Logic: Fuzziness vs probability, Crisp logic vs fuzzy logic, Fuzzy sets and systems, operations on sets, fuzzy relations, membership functions, fuzzy rule generation, de fuzzification, Applications of Fuzzy Logic in process Control and motion control

Genetic Algorithms: introduction and concept, coding, reproduction, cross-over and mutation Scaling, fitness, applications.


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