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Machine Learning in Electrical Engineering Quiz

Total questions: 11

Worksheet time: 6mins

Name
Class
Date
1.

What is Machine Learning (ML)?

a)

A subset of AI that enables systems to automatically learn patterns from data and make predictions/decisions.

b)

A programming language used for electrical engineering applications.

c)

A hardware component used in electrical systems.

d)

A method to manually write explicit rules for systems.

2.

What is Machine Learning (ML)?

a)

A subset of AI that enables systems to automatically learn patterns from data and make predictions/decisions.

b)

A programming language used for electrical engineering applications.

c)

A hardware component used in electrical systems.

d)

A method to manually write explicit rules for systems.

3.

How does Machine Learning help in fault detection and condition monitoring in electrical engineering?

a)

By detecting anomalies in motors, transformers, and power lines, and using predictive maintenance with vibration/temperature data.

b)

By manually inspecting motors and transformers for faults.

c)

By replacing motors and transformers with AI systems.

d)

By eliminating the need for condition monitoring.

4.

What is the goal of supervised learning in machine learning?

a)

Predict a label/output from input data

b)

Find patterns in unlabeled data

c)

Learn from interaction based on rewards

d)

Forecast solar power generation

5.

What is the goal of unsupervised learning in machine learning?

a)

Predict a label/output from input data

b)

Find patterns, groups, or structure in unlabeled data

c)

Learn from interaction based on rewards

d)

Perform PID tuning using ML

6.

Which machine learning technique is used for clustering power quality events?

a)

Supervised learning

b)

Unsupervised learning

c)

Reinforcement learning

d)

PID tuning

7.

Which of the following is an application of machine learning in electrical vehicle (EV) systems?

a)

Classify disturbances in power quality analysis

b)

Charging station demand forecasting

c)

Predict motor temperature

d)

Adaptive control using reinforcement learning

8.

What term refers to the issue of a model performing well on training data but poorly on testing data?

a)

Accuracy

b)

Overfitting

c)

Precision

d)

Recall

9.

What does K-Means clustering aim to do?

a)

Build dendrograms

b)

Group data into k clusters

c)

Predict next day load

d)

Remove noise from data

10.

Which of the following is an output of solar power prediction using regression techniques?

a)

Fault type classification

b)

Solar power generation

c)

High consumption users

d)

Image-based signal analysis

11.

What is the duration of the "Supervised Learning + Algorithms" segment?

a)

10 minutes

b)

15 minutes

c)

25 minutes

d)

20 minutes