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Applications of Computational Intelligence
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Computational Intelligence (CI) is the theory, design, application, and development of biologically and linguistically motivated computational paradigms. Traditionally, the three main pillars of CI have been neural networks, fuzzy systems, and evolutionary computation. However, in time, many nature-inspired computing paradigms have evolved. Thus, CI is an evolving field, and, at present, in addition to the three main constituents, it encompasses computing paradigms such as ambient intelligence, artificial life, cultural learning, artificial endocrine networks, social reasoning, and artificial hormone networks. CI plays a major role in developing successful intelligent systems, including games and cognitive developmental systems. Over the last few years, there has been an explosion of research on deep learning, specifically deep convolutional neural networks, and deep learning has become the core method for artificial intelligence. In fact, some of the most successful AI systems today are based on CI. Therefore, this reprint focuses on the theoretical study of computational intelligence and its applications.
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Keywords
- active–frozen memory model
- AlphaZero
- artificial intelligence
- attention mechanism
- capsule network (CapsNet)
- circle chaotic map
- Computational intelligence
- Computer science
- Computing & information technology
- convolutional neural network
- convolutional neural network (CNN)
- convolutional neural networks
- crop disease leaf image segmentation (CDLIS)
- crop insect pest identification
- cross-modal learning network
- crystal structure algorithm
- CSI
- data-driven method
- deep learning
- dilated convolution
- disease screening
- Economics, finance, business & management
- Electroencephalogram
- engineering optimization problems
- evolutionary algorithm
- evolutionary multitasking
- evolutionary optimization
- few-shot learning
- gastrointestinal stromal tumor
- golden sine algorithm
- graph neural network
- hashing learning
- HCNNs
- Human perception
- hyperspectral image
- image classification
- image retrieval
- Industry & industrial studies
- Information technology industries
- joint integrated probabilistic data association
- knowledge distillation
- Kuroshio Extension Observatory
- large-scale multiobjective optimization
- Lévy flight
- lightweight multi-scale dilated U-Net (LWMSDU-Net)
- Media, information & communication industries
- medical image classification
- medical image segmentation
- multi-scale convolution-capsule network (MSCCN)
- multi-target tracking
- multipopulation optimization
- neuroevolution
- no-limit Texas hold’em
- NoGo games
- nonlinear adaptive weight
- object detection
- online update
- opponent exploitation
- particle swarm optimization
- people counting
- progressive deep learning
- propagation mechanism
- quality of experience
- random finite set
- reinforcement learning
- reliable evaluation strategy
- self-attention
- self-organizing map
- self-training
- semi-supervised learning
- sound speed profile
- sparse unmixing
- spatial attention
- transfer learning
- transformer
- tuna swarm optimization
- u-net
- visual tracking
- weakly supervised segmentation
Links
DOI: 10.3390/books978-3-0365-7039-6Editions