Read the below passage and answer the questions. Artificial Neural Networks…
2024
Read the below passage and answer the questions.
Artificial Neural Networks (ANNs) are computational models inspired by the human brain's neural networks. They consist of inter-connected nodes, or neurons, organized into layers: an input layer, one or more hidden layers, and an output layer. Each connection between neurons has a weight that adjusts as learning progresses, allowing the network to adapt and improve its performance. ANNs are particularly effective in recognizing patterns, making them valuable for tasks such as image and speech recognition, Natural language processing, and predictive analytics. Learning in ANNs typically involves training algorithms like backpropagation, which minimize the error by adjusting the weights. As a subset of machine learning, ANNs have revolutionized the field of Artificial Intelligence by providing solutions to complex problems that traditional algorithms struggle with.
Artificial Neural Networks (ANNs) are inspired by:
- A.
Quantum mechanics
- B.
Human brain's neural network
- C.
Computer Hardware architecture
- D.
Genetic algorithm.
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Correct answer: B
Answer: Artificial Neural Networks are inspired by the human brain's neural network.
Explanation: The passage explicitly says that ANNs are "inspired by the human brain's neural networks." It describes key biological-inspired elements such as neurons (nodes), layers (input, hidden, output), and adjustable connection weights that change during learning.
Neurons and layers: ANNs use interconnected nodes organized into input, hidden, and output layers, mirroring biological neural organization.
Weights and learning: Connections have weights that adjust during training (for example, via backpropagation), analogous to changing synaptic strengths in biology.
Not other choices: Quantum mechanics, computer hardware architecture, and genetic algorithms are unrelated as the primary inspiration for ANNs.
Therefore, the correct choice is the human brain's neural network because the design and terminology of ANNs are explicitly modeled after biological neural systems.