Advances in Artificial Intelligence
The present book contains all the articles accepted and published in the Special Issue “Advances in Artificial Intelligence: Models, Optimization, and Machine Learning, 2nd Edition” of the MDPI Mathematics journal. The content of this Special Issue encompasses a diverse array of topics related to ar...
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| Materialtyp: | Online |
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| Språk: | engelska |
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MDPI - Multidisciplinary Digital Publishing Institute
2025
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| Länkar: | ONIX_20250812T110751_9783725834730_32 |
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| _version_ | 1869529790419042304 |
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| collection | Directory of Open Access Books |
| description | The present book contains all the articles accepted and published in the Special Issue “Advances in Artificial Intelligence: Models, Optimization, and Machine Learning, 2nd Edition” of the MDPI Mathematics journal. The content of this Special Issue encompasses a diverse array of topics related to artificial intelligence, spanning both foundational theories and practical applications. It covers advancements in deep learning and machine learning techniques, including neural networks and reinforcement learning, as well as the growing field of federated learning. This issue also explores developments in natural language processing and multimodal data analysis, alongside optimization strategies inspired by evolutionary algorithms and probabilistic models, such as Gaussian processes. It also highlights research in feature selection and support vector machines, innovations in autonomous driving and trajectory prediction, and broader applications of artificial intelligence in decision-making and intelligent systems. We anticipate that the scientific findings presented in this volume will offer valuable references and inspiration to those eager to explore new frontiers in artificial intelligence, machine learning, and their extensive real-world applications. |
| format | Online |
| id | doab-20.500.12854ir-165276 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1652762025-08-12T09:16:39Z Advances in Artificial Intelligence Leon, Florin Hulea, Mircea Gavrilescu, Marius evolutionary algorithm biologically inspired optimization neural network optimization imperialist competitive algorithm regression model intelligent connected vehicle cooperative driving system V2X communication technology redundancy allocation hybrid structure binary systems Markov chains evolutionary algorithms RELIVE algorithm zero-one integer programming hateful memes deep learning multimodal data multi-task learning self-supervised principal component analysis manifold learning features extracting l2,p-norm neighborhood preserving embedding trajectory prediction autonomous driving neural network multimodal prediction group context road context machine learning Bayesian optimization Gaussian process overfitting support vector machine Harris hawks optimization scaling techniques parallel processing pre-trained language models parameter-efficient fine-tuning low-rank adaptation intrinsic rank training efficiency federated learning transfer learning adapter transformer traditional machine learning cancer detection colorectal cancer gastric cancer mathematical formulation preprocessing feature extraction feature selection multi-target regression graph learning crude oil scheduling efficient policy learning state-space compression reinforcement learning abstractive summarization text summarization natural language processing Gaussian process regression (GPR) time-series analysis differential evolution (DE) support vector regression (SVR) New York Commodity Exchange gold price forecasting graph neural network graph information joint training graph curvature thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science The present book contains all the articles accepted and published in the Special Issue “Advances in Artificial Intelligence: Models, Optimization, and Machine Learning, 2nd Edition” of the MDPI Mathematics journal. The content of this Special Issue encompasses a diverse array of topics related to artificial intelligence, spanning both foundational theories and practical applications. It covers advancements in deep learning and machine learning techniques, including neural networks and reinforcement learning, as well as the growing field of federated learning. This issue also explores developments in natural language processing and multimodal data analysis, alongside optimization strategies inspired by evolutionary algorithms and probabilistic models, such as Gaussian processes. It also highlights research in feature selection and support vector machines, innovations in autonomous driving and trajectory prediction, and broader applications of artificial intelligence in decision-making and intelligent systems. We anticipate that the scientific findings presented in this volume will offer valuable references and inspiration to those eager to explore new frontiers in artificial intelligence, machine learning, and their extensive real-world applications. 2025-08-12T09:16:36Z 2025-08-12T09:16:36Z 2025 book ONIX_20250812T110751_9783725834730_32 9783725834730 9783725834747 https://directory.doabooks.org/handle/20.500.12854/165276 eng image/jpeg Attribution 4.0 International https://mdpi.com/books https://mdpi.com/books/pdfview/book/10636 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-3474-7 10.3390/books978-3-7258-3474-7 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725834730 9783725834747 368 open access |
| spellingShingle | evolutionary algorithm biologically inspired optimization neural network optimization imperialist competitive algorithm regression model intelligent connected vehicle cooperative driving system V2X communication technology redundancy allocation hybrid structure binary systems Markov chains evolutionary algorithms RELIVE algorithm zero-one integer programming hateful memes deep learning multimodal data multi-task learning self-supervised principal component analysis manifold learning features extracting l2,p-norm neighborhood preserving embedding trajectory prediction autonomous driving neural network multimodal prediction group context road context machine learning Bayesian optimization Gaussian process overfitting support vector machine Harris hawks optimization scaling techniques parallel processing pre-trained language models parameter-efficient fine-tuning low-rank adaptation intrinsic rank training efficiency federated learning transfer learning adapter transformer traditional machine learning cancer detection colorectal cancer gastric cancer mathematical formulation preprocessing feature extraction feature selection multi-target regression graph learning crude oil scheduling efficient policy learning state-space compression reinforcement learning abstractive summarization text summarization natural language processing Gaussian process regression (GPR) time-series analysis differential evolution (DE) support vector regression (SVR) New York Commodity Exchange gold price forecasting graph neural network graph information joint training graph curvature thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science Advances in Artificial Intelligence |
| title | Advances in Artificial Intelligence |
| title_full | Advances in Artificial Intelligence |
| title_fullStr | Advances in Artificial Intelligence |
| title_full_unstemmed | Advances in Artificial Intelligence |
| title_short | Advances in Artificial Intelligence |
| title_sort | advances in artificial intelligence |
| topic | evolutionary algorithm biologically inspired optimization neural network optimization imperialist competitive algorithm regression model intelligent connected vehicle cooperative driving system V2X communication technology redundancy allocation hybrid structure binary systems Markov chains evolutionary algorithms RELIVE algorithm zero-one integer programming hateful memes deep learning multimodal data multi-task learning self-supervised principal component analysis manifold learning features extracting l2,p-norm neighborhood preserving embedding trajectory prediction autonomous driving neural network multimodal prediction group context road context machine learning Bayesian optimization Gaussian process overfitting support vector machine Harris hawks optimization scaling techniques parallel processing pre-trained language models parameter-efficient fine-tuning low-rank adaptation intrinsic rank training efficiency federated learning transfer learning adapter transformer traditional machine learning cancer detection colorectal cancer gastric cancer mathematical formulation preprocessing feature extraction feature selection multi-target regression graph learning crude oil scheduling efficient policy learning state-space compression reinforcement learning abstractive summarization text summarization natural language processing Gaussian process regression (GPR) time-series analysis differential evolution (DE) support vector regression (SVR) New York Commodity Exchange gold price forecasting graph neural network graph information joint training graph curvature thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science |
| topic_facet | evolutionary algorithm biologically inspired optimization neural network optimization imperialist competitive algorithm regression model intelligent connected vehicle cooperative driving system V2X communication technology redundancy allocation hybrid structure binary systems Markov chains evolutionary algorithms RELIVE algorithm zero-one integer programming hateful memes deep learning multimodal data multi-task learning self-supervised principal component analysis manifold learning features extracting l2,p-norm neighborhood preserving embedding trajectory prediction autonomous driving neural network multimodal prediction group context road context machine learning Bayesian optimization Gaussian process overfitting support vector machine Harris hawks optimization scaling techniques parallel processing pre-trained language models parameter-efficient fine-tuning low-rank adaptation intrinsic rank training efficiency federated learning transfer learning adapter transformer traditional machine learning cancer detection colorectal cancer gastric cancer mathematical formulation preprocessing feature extraction feature selection multi-target regression graph learning crude oil scheduling efficient policy learning state-space compression reinforcement learning abstractive summarization text summarization natural language processing Gaussian process regression (GPR) time-series analysis differential evolution (DE) support vector regression (SVR) New York Commodity Exchange gold price forecasting graph neural network graph information joint training graph curvature thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science |
| url | ONIX_20250812T110751_9783725834730_32 |