Lecture02 人工神经网络用于石油工程

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What are ANN Used for?

Hale Waihona Puke Brain modeling Models of human development – help children with developmental problems Simulations of adult performance – aid our understanding of how the brain works Neuropsychological models – suggest remedial actions for brain damaged patients Real world applications Financial modeling – predicting stocks, shares, currency exchange rates Time series prediction – climate, weather, airline marketing tactician Computer games – intelligent agents, backgammon, first person shooters Control systems – autonomous adaptable robots, microwave controllers Pattern recognition – speech recognition, hand-writing recognition, sonar signals Data analysis – data compression, data mining Noise reduction – function approximation, ECG noise reduction Bioinformatics – protein secondary structure, DNA sequencing Petroleum Engineering -------------------- WVU -----------------------



From a practical point of view, an ANN is just a parallel computational system consisting of many simple processing elements connected together in a specific way in order to perform a particular task.
Artificial Neural Networks and Reservoir Engineering Applications
Dr. Guojian Cheng
Department of Petroleum Engineering, West Virginia University School of Computer Science, Xi’an Shiyou University gucheng@, gjcheng.xsyu@

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What are ANN Used for?

Brain modeling: The scientific goal of building models of how real brains work

This can potentially help us understand the nature of human intelligence, formulate better teaching strategies, or better remedial actions for brain damaged patients.
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Lecture Topics
1. 2. 3. 4. 5.
6.
7.
An Overview of Computational Intelligence Applications for Petroleum Reservoir Engineering Artificial Neural Networks and Reservoir Engineering Applications Support Vector Machines and Reservoir Engineering Applications Fuzzy System and Reservoir Engineering Applications Evolutionary Computation and Reservoir Engineering Applications Swarm Intelligence and Reservoir Engineering Applications Hybrid Intelligence System and Reservoir Engineering Applications
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Perceptron Computing

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Perceptron Computing

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What are ANN?

Neural Networks (NNs) are networks of neurons, as found in real our brains. Artificial Neurons are crude approximations of the biological neurons. They may be physical devices, or purely mathematical constructs. Artificial Neural Networks (ANNs) are networks of Artificial Neurons. They may be physical devices, or simulated on conventional computers.

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Biological Neurons vs. Artificial Neurons

Biological Neurons encode their outputs or activations as a series of brief electrical pulses (i.e. spikes or action potentials). Dendrites are the receptive zones that receive activation from other neurons. Cell body (soma) of the neuron’s processes the incoming activations and converts them into output activations. Axons are transmission lines that send activation to other neurons. Synapses allow weighted transmission of signals (using neurotransmitters) between axons and dendrites to build up large neural networks.
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Activation functions of a neuron
Step function
Y
Sign function Sigmoid function Linear function
Y Y Y
+1
0 -1 X
+1
0 -1 X
1
0 -1 X
1
0 -1 X
1, if X 0 sign 1, if X 0 sigmoid step Y Y Y 0, if X 0 1, if X 0
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Why Study ANN ?

They are extremely powerful computational devices (Turing equivalent, universal computers) Massive parallelism makes them very efficient They can learn and generalize from training data They are particularly fault tolerant – this is equivalent to the “graceful degradation” found in biological systems
Main References: 1. Michael Negnevitsky, “Artificial Intelligence: A Guide to Intelligent Systems (2nd Edition)", Addison Wesley,2004,ISBN: 0321204662 2. Arthur K. Kordon, "Applying Computational Intelligence: How to Create Value", Springer,2009, ISBN: 3540699104 3. / 4. / 5. /

Artificial System Building: The engineering goal of building efficient systems for real world applications

This may make machines more powerful, relieve humans of tedious tasks, and may even improve upon human performance.