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level: machine learning

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level questions: machine learning

QuestionAnswer
What is included as part of preventative maitenance?-predetermined maintenance (follows factory schedule) -condition-based maintenance (occurs when a situation of condition indicates maintenance is needed)
What is included as part of preventative maitenance?-predetermined maintenance (follows factory schedule) -condition-based maintenance (occurs when a situation of condition indicates maintenance is needed)
What is included as part of preventative maitenance?-predetermined maintenance (follows factory schedule) -condition-based maintenance (occurs when a situation of condition indicates maintenance is needed)
What is included as part of preventative maitenance?-predetermined maintenance (follows factory schedule) -condition-based maintenance (occurs when a situation of condition indicates maintenance is needed)
What is included as part of preventative maitenance?-predetermined maintenance (follows factory schedule) -condition-based maintenance (occurs when a situation of condition indicates maintenance is needed)
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What is included as part of preventative maitenance?-predetermined maintenance (follows factory schedule) -condition-based maintenance (occurs when a situation of condition indicates maintenance is needed)
What is artificial intelligence (AI)?Artificial intelligence (AI) is a popular branch of computer science that concerns with building “intelligent” smart machines capable of performing intelligent tasks.
What is machine learning?Field of study that gives computer the ability to learn without being explicitly programmed.
What is deep learning?A subfield of machine learning that is concerned with algorithms inspired by the brain’s structure, such as artificial neural network.
What are some applications of machine learning?-Deep learning applications. -Predictive analytics. -Translation. -Information extraction.
What are the ways in which machines can learn?Supervised learning and unsupervised learning.
What is supervised learning?An approach to creating artificial intelligence (AI) based on labelled training data consisting of input objects and a desired output value. After trained by using labelled data, it can be used to predict the outcomes based on the unlabelled data (only inputs are known).
How can supervised learning be achieved for simple engineering problems?Regression.
How can supervised learning be achieved for complex engineering problems?By combining different regressions together, namely artificial neural networks (ANN).
What are the approaches of supervised learning using ANN?-ANN using activation function -Fuzzy neural network (FNN) using membership function
What are artificial neural networks (ANN)?Series of algorithms that mimic the operations of a human brain to recognise relationships between vast amounts of data.
What is a fuzzy set defined by?Its unclear boundaries.
When is fuzzy set theory used?When the activation function has a very steep change, fuzzy set theory is needed for problems relating to imprecise judgements.
How is the element in fuzzy set theory presented?? = {?, pf(?)} where: -x is the element value, -pf(x) is membership value showing the degree of probability of x belonging to A (e.g., a high cost category)
What are support-vector machines (SVMs) in machine learning?Supervised learning models with associated learning algorithms that analyse data for classification and regression analysis.
What is the process of supervised training using Support Vector Machine (SVM)?Labelled data for training -> determine hyperplane (&unlabelled data) -> trained support vector machine -> risk level prediction
How is the best decision boundary (hyperplane) determined?The boundary line with the maximum margin with a high fault tolerance.
What are the vectors that sit on the hyperplane called?support vectors
What do recurrent neural networks (RNN) do?Recognise sequential characteristics of data and use patterns to predict the next likely scenario. Neural networks which has memory.
How are recurrent neural networks (RNN) sequential?The outputs of hidden layer of RNN are stored in the memory and considered as inputs as well.
What is the process in which sequential data is input into a recurrent neural network (RNN) after training?• The process of inputting sequential data into an RNN after training involves pre-processing the data into a suitable format that can be fed into the network. • As RNNs are designed to capture temporal dependencies in sequential data, they may not be able to capture any meaningful temporal dependencies with a single data point.
What are the limitations of recurrent neural networks (RNN)?Can not maintain information in memory over a long period. Therefore, it is not suitable to predict data consequences over a long period of time.
What are the advantages of long short-term memory (LSTM) networks compared to recurrent neural networks (RNN)?• Retain information for longer periods, making them more effective in modelling long-term dependencies. • Better control of the flow of information using the gating mechanism (input gate, forget gate and output gate). • Better performance on sequence-to-sequence tasks. • More effectively filter out irrelevant information and noise in a sequence due to their gating mechanism.
How does the gating mechanism of LSTM work?Information in LSTMs can be stored, written, or read via gates that open and close. These gates store the memory in the analogue format, implementing element-wise multiplication by sigmoid ranges between 0-1.
Why is preventative maintenance of infrastructure projects important?Ensure the proper functioning and longevity of infrastructure.
What can LTSM be used for?Predict and identify potential maintenance issues before they become critical.
How can LSTM networks be implemented as part of preventative maitenance?• Step 1 - Data collection (e.g., historical inspection data) • Step 2 - Data preprocessing (e.g., handle missing values, and normalize the data) • Step 3 - Design an LSTM network (e.g., input layers, LSTM layers, and output layers) • Step 4 – Training the model (e.g., Split the preprocessed data into training and validation sets) • Step 5 - Model evaluation (e.g., Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) ) • Step 6 - Predictive maintenance (e.g., schedule maintenance based on residual life prediction) • Step 7 - Continuous improvement (e.g., continuously collect new data for training)
What is included as part of preventative maitenance?-predetermined maintenance (follows factory schedule) -condition-based maintenance (occurs when a situation of condition indicates maintenance is needed)