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230811 ||| eng |
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|a books978-3-0365-7483-7
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|a 9783036574837
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|a 9783036574820
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|a Wu, Yue
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| 245 |
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|a Recent Advances in Machine Learning and Computational Intelligence
|h Elektronische Ressource
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| 260 |
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|a Basel
|b MDPI - Multidisciplinary Digital Publishing Institute
|c 2023
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| 300 |
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|a 1 electronic resource (216 p.)
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| 653 |
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|a machine learning
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| 653 |
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|a naive Bayesian classifier
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| 653 |
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|a subsection proximal policy optimization
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| 653 |
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|a mixed-attribute classification
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| 653 |
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|a autonomous driving
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| 653 |
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|a n/a
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| 653 |
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|a attribute transformation
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| 653 |
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|a deep learning
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| 653 |
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|a vectorization
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| 653 |
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|a differential evolution strategy
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| 653 |
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|a attribute independence assumption
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| 653 |
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|a tactics for high performance
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| 653 |
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|a weighted importance sampling
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| 653 |
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|a jump point search algorithm
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| 653 |
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|a mask R-CNN
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| 653 |
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|a TORCS
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| 653 |
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|a cross-validation
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| 653 |
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|a RJA-star algorithm
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| 653 |
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|a facial skin problem
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| 653 |
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|a beta function
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| 653 |
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|a left ventricle segmentation
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| 653 |
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|a evolutionary algorithm
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| 653 |
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|a reinforcement learning
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| 653 |
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|a model predictive control
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| 653 |
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|a Information technology industries / bicssc
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| 653 |
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|a vehicle-following
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| 653 |
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|a magnetic resonance imaging
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| 653 |
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|a sentiment analysis
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| 653 |
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|a optimization algorithm
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| 653 |
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|a path planning
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| 653 |
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|a credit scoring
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| 653 |
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|a feature importance
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| 653 |
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|a Computer science / bicssc
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| 653 |
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|a UNet 3+
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| 653 |
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|a global search optimization
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| 653 |
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|a super resolution
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| 653 |
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|a parameter adaptive
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| 653 |
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|a Bayesian network
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| 653 |
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|a quadruped robot
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| 653 |
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|a crow search algorithm
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| 653 |
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|a Generative Adversarial Network (GAN)
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| 653 |
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|a weighted mean of vectors
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| 653 |
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|a encoder-decoder
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| 653 |
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|a transformer
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| 653 |
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|a search accuracy
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| 653 |
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|a dynamic multi-objective optimization problems
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| 653 |
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|a R5DOS intersection matrix
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| 653 |
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|a conditional probability
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| 653 |
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|a many-objective optimization problems
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| 700 |
1 |
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|a Zhang, Xinglong
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| 700 |
1 |
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|a Jia, Pengfei
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| 700 |
1 |
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|a Wu, Yue
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b DOAB
|a Directory of Open Access Books
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| 500 |
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|a Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/
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| 024 |
8 |
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|a 10.3390/books978-3-0365-7483-7
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| 856 |
4 |
2 |
|u https://directory.doabooks.org/handle/20.500.12854/100825
|z DOAB: description of the publication
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| 856 |
4 |
0 |
|u https://www.mdpi.com/books/pdfview/book/7288
|7 0
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 000
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| 082 |
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|a 576
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| 082 |
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|a 600
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|a Machine learning and computational intelligence have been applied to various areas and witnessed many successes. The research in this publication explorse many intelligent algorithms which are characterized by computational adaptability, robustness, and high performance. These algorithms facilitate intelligent behavior in complex and dynamic environments and the development of technology that enables machines to think, behave, or act in a more humanesque fashion. This reprint aims to present and discuss the most recent innovations, trends, concerns, challenges, solutions, and application fields in the areas of machine learning and computational intelligence.
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