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What is Neural Network (NN)

Chapter 6
Handbook of Research on Human-Computer Interfaces and New Modes of Interactivity
In this chapter, it is a layered graph where each layer contains a set of nodes, the nodes of which are fully connected to those in the next layer, the first layer representing inputs and the last representing outputs or decisions. The graph encodes the statistical relationships between the inputs and outputs via machine-learning to generate outputs given only inputs.
Published in Chapter:
Explanations in Artificial Intelligence Decision Making: A User Acceptance Perspective
Norman G. Vinson (National Research Council, Canada), Heather Molyneaux (National Research Council, Canada), and Joel D. Martin (National Research Council, Canada)
Copyright: © 2019 |Pages: 22
DOI: 10.4018/978-1-5225-9069-9.ch006
Abstract
The opacity of AI systems' decision making has led to calls to modify these systems so they can provide explanations for their decisions. This chapter contains a discussion of what these explanations should address and what their nature should be to meet the concerns that have been raised and to prove satisfactory to users. More specifically, the chapter briefly reviews the typical forms of AI decision-making that are currently used to make real-world decisions affecting people's lives. Based on concerns about AI decision making expressed in the literature and the media, the chapter follows with principles that the systems should respect and corresponding requirements for explanations to respect those principles. A mapping between those explanation requirements and the types of explanations generated by AI decision making systems reveals the strengths and shortcomings of the explanations generated by those systems.
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Chapter 208
Shortening Automated Negotiation Threads via Neural Nets
A network modelled after the neurons in a biological nervous system with multiple synapses and layers. It is designed as an interconnected system of processing elements organized in a layered parallel architecture. These elements are called neurons and have a limited number of inputs and outputs. NNs can be trained to find nonlinear relationships in data, enabling specific input sets to lead to given target outputs.
Published in Chapter: Shortening Automated Negotiation Threads via Neural Nets; From: Encyclopedia of Artificial Intelligence
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Chapter 6
A Neuro-Fuzzy Partner Selection System for Business Social Networks
Also known as Artificial Neural Network (ANN), is a non-linear statistical data modeling tool. It processes information using a connectionist approach to computation. In most cases a NN is an adaptive system that changes its structure based on external or internal information that flows through the network during the learning phase. Modern neural networks are usually used to model complex relationships between inputs and outputs or to find patterns in data.
Published in Chapter: A Neuro-Fuzzy Partner Selection System for Business Social Networks; From: Handbook of Research on Business Social Networking: Organizational, Managerial, and Technological Dimensions
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Chapter 223
A Survey on Neural Networks in Automated Negotiations
A network modelled after the neurons in a biological nervous system with multiple synapses and layers. It is designed as an interconnected system of processing elements organized in a layered parallel architecture. These elements are called neurons and have a limited number of inputs and outputs. NNs can be trained to find nonlinear relationships in data, enabling specific input sets to lead to given target outputs.
Published in Chapter: A Survey on Neural Networks in Automated Negotiations; From: Encyclopedia of Artificial Intelligence
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Chapter 2
Swarm-Based Nature-Inspired Metaheuristics for Neural Network Optimization
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Chapter 10
Aspect-Based Sentiment Analysis of Online Product Reviews
Neural network is combination of neuron. Neural network is used for both classification and prediction. Neural network contain three layers for computation first is input layer second is hidden layer and last is output layer.
Published in Chapter: Aspect-Based Sentiment Analysis of Online Product Reviews; From: Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence
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