Recent Advances in Machine Learning and Computational Intelligence
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...
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Format: | Electronic Book Chapter |
Language: | English |
Published: |
Basel
MDPI - Multidisciplinary Digital Publishing Institute
2023
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Online Access: | DOAB: download the publication DOAB: description of the publication |
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072 | 7 | |a KNTX |2 bicssc | |
072 | 7 | |a UY |2 bicssc | |
100 | 1 | |a Wu, Yue |4 edt | |
700 | 1 | |a Zhang, Xinglong |4 edt | |
700 | 1 | |a Jia, Pengfei |4 edt | |
700 | 1 | |a Wu, Yue |4 oth | |
700 | 1 | |a Zhang, Xinglong |4 oth | |
700 | 1 | |a Jia, Pengfei |4 oth | |
245 | 1 | 0 | |a Recent Advances in Machine Learning and Computational Intelligence |
260 | |a Basel |b MDPI - Multidisciplinary Digital Publishing Institute |c 2023 | ||
300 | |a 1 electronic resource (216 p.) | ||
336 | |a text |b txt |2 rdacontent | ||
337 | |a computer |b c |2 rdamedia | ||
338 | |a online resource |b cr |2 rdacarrier | ||
506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
520 | |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. | ||
540 | |a Creative Commons |f https://creativecommons.org/licenses/by/4.0/ |2 cc |4 https://creativecommons.org/licenses/by/4.0/ | ||
546 | |a English | ||
650 | 7 | |a Information technology industries |2 bicssc | |
650 | 7 | |a Computer science |2 bicssc | |
653 | |a left ventricle segmentation | ||
653 | |a UNet 3+ | ||
653 | |a encoder-decoder | ||
653 | |a transformer | ||
653 | |a magnetic resonance imaging | ||
653 | |a beta function | ||
653 | |a crow search algorithm | ||
653 | |a dynamic multi-objective optimization problems | ||
653 | |a evolutionary algorithm | ||
653 | |a many-objective optimization problems | ||
653 | |a naive Bayesian classifier | ||
653 | |a attribute independence assumption | ||
653 | |a mixed-attribute classification | ||
653 | |a conditional probability | ||
653 | |a Bayesian network | ||
653 | |a attribute transformation | ||
653 | |a subsection proximal policy optimization | ||
653 | |a weighted importance sampling | ||
653 | |a TORCS | ||
653 | |a vehicle-following | ||
653 | |a autonomous driving | ||
653 | |a credit scoring | ||
653 | |a machine learning | ||
653 | |a deep learning | ||
653 | |a model predictive control | ||
653 | |a reinforcement learning | ||
653 | |a parameter adaptive | ||
653 | |a quadruped robot | ||
653 | |a facial skin problem | ||
653 | |a mask R-CNN | ||
653 | |a super resolution | ||
653 | |a Generative Adversarial Network (GAN) | ||
653 | |a tactics for high performance | ||
653 | |a R5DOS intersection matrix | ||
653 | |a RJA-star algorithm | ||
653 | |a jump point search algorithm | ||
653 | |a path planning | ||
653 | |a sentiment analysis | ||
653 | |a cross-validation | ||
653 | |a vectorization | ||
653 | |a feature importance | ||
653 | |a differential evolution strategy | ||
653 | |a global search optimization | ||
653 | |a optimization algorithm | ||
653 | |a search accuracy | ||
653 | |a weighted mean of vectors | ||
653 | |a n/a | ||
856 | 4 | 0 | |a www.oapen.org |u https://mdpi.com/books/pdfview/book/7288 |7 0 |z DOAB: download the publication |
856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/100825 |7 0 |z DOAB: description of the publication |