Advances in Intelligent Data Analysis and Its Applications
This Special Issue sheds light on the escalating significance of intelligent data analysis and its applications in the era of burgeoning big data. It has emerged as a pivotal driver for progress across diverse domains, necessitating in-depth research and practical applications within this framework....
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| 格式: | Online |
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| 語言: | 英语 |
| 出版: |
MDPI - Multidisciplinary Digital Publishing Institute
2024
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| 主題: | |
| 在線閱讀: | ONIX_20240514_9783039286157_50 |
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| _version_ | 1869525548040978432 |
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| collection | Directory of Open Access Books |
| description | This Special Issue sheds light on the escalating significance of intelligent data analysis and its applications in the era of burgeoning big data. It has emerged as a pivotal driver for progress across diverse domains, necessitating in-depth research and practical applications within this framework. This multifaceted endeavor facilitates the revelation of latent value within extensive datasets and provides robust support for innovation and progress across various industries. Consequently, the imperative nature of discussing and exploring the latest research developments in intelligent data analysis and its practical applications becomes apparent, representing a vital initiative to keenly discern and proactively address trends in the big data era. This compilation is dedicated to comprehensively exploring recent research advancements in intelligent data analysis, elucidating their specific manifestations in practical applications. Encompassing diverse and profound topics, including intelligent data mining algorithms and their applications, the integration of machine learning in intelligent data analysis, models for natural language processing, intelligent granular computing models, cognitive computing, and hybrid models, the overarching goal is to provide profound insights into the academic development of intelligent data analysis. This, in turn, extends innovative guidance for academic research and industrial applications, thereby nurturing the continuous advancement and evolution of intelligent data analysis technologies. |
| format | Online |
| id | doab-20.500.12854ir-137448 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1374482024-05-14T13:07:23Z Advances in Intelligent Data Analysis and Its Applications Zhang, Chao Li, Wentao Zhang, Huiyan Zhan, Tao intuitionistic fuzzy concept rough set multi-granularity relative macro-knowledge distance multigranulation rough sets optimistic approximation pessimistic approximation cost-sensitive decision-making applications context awareness attention network dynamic user preferences next POI recommendation IoT unmanned aerial vehicle anomaly detection ALFA CNN orphan genes (OGs) hybrid features machine learning angiosperm delay prediction model lightweight neural network lightweight attention mechanism semi-supervised classification co-training method instance selection granular computing information granulation variable structure of interacting multiple-model symmetric model set optimization method proportional reduction optimization method expected model optimization method multi-granulation rough set hesitant trapezoidal fuzzy set air quality evaluation dependency structure graph convolution network question answering data mining network clustering protein complex detection power-law distribution topological characteristics data enhancement few-shot data smart home generative adversarial networks intrusion detection bilingual short text with emoji emotional fusion emotional fluctuation emotional computation knowledge graph embedding chunked learning network data-driven approach picks wear state recognition wavelet packet decomposition Bayesian-LSTM absolute positioning accuracy deep belief network differential evolution algorithm industrial robot off-line error compensation sequential recommendation local fluctuation global stability Stochastic Shared Embeddings AUV underwater navigation dataset inertial navigation DVL ultrasound imaging plane-wave beamforming coherence factor adaptive spatio-temporally smoothed delay multiply and sum beamforming data augmentation deep learning data quality big data multi-head attention BiLSTM energy consumption IoT-based power control systems optimization using sensor data predictive control pharmaceutical technology process modeling exploratory data analysis multiscale neighbors attentional mechanism collaborative embedding recommendation computer science artificial intelligence burnout clinical reasoning imbalanced datasets stratified sampling prediction classification accuracy wrapper classes target detection YOLOV5s attention mechanism lightweighting healthcare imputation algorithms incomplete data neighborhood similarity frequency synthesizer direct frequency synthesizer indirect frequency synthesizer railway track circuit n/a thema EDItEUR::U Computing and Information Technology::UY Computer science This Special Issue sheds light on the escalating significance of intelligent data analysis and its applications in the era of burgeoning big data. It has emerged as a pivotal driver for progress across diverse domains, necessitating in-depth research and practical applications within this framework. This multifaceted endeavor facilitates the revelation of latent value within extensive datasets and provides robust support for innovation and progress across various industries. Consequently, the imperative nature of discussing and exploring the latest research developments in intelligent data analysis and its practical applications becomes apparent, representing a vital initiative to keenly discern and proactively address trends in the big data era. This compilation is dedicated to comprehensively exploring recent research advancements in intelligent data analysis, elucidating their specific manifestations in practical applications. Encompassing diverse and profound topics, including intelligent data mining algorithms and their applications, the integration of machine learning in intelligent data analysis, models for natural language processing, intelligent granular computing models, cognitive computing, and hybrid models, the overarching goal is to provide profound insights into the academic development of intelligent data analysis. This, in turn, extends innovative guidance for academic research and industrial applications, thereby nurturing the continuous advancement and evolution of intelligent data analysis technologies. 2024-05-14T13:07:18Z 2024-05-14T13:07:18Z 2024 book ONIX_20240514_9783039286157_50 9783039286157 9783039286164 https://directory.doabooks.org/handle/20.500.12854/137448 eng application/octet-stream Attribution-NonCommercial-NoDerivatives 4.0 International https://mdpi.com/books/pdfview/book/8602 https://mdpi.com/books/pdfview/book/8602 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-03928-616-4 10.3390/books978-3-03928-616-4 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783039286157 9783039286164 542 open access |
| spellingShingle | intuitionistic fuzzy concept rough set multi-granularity relative macro-knowledge distance multigranulation rough sets optimistic approximation pessimistic approximation cost-sensitive decision-making applications context awareness attention network dynamic user preferences next POI recommendation IoT unmanned aerial vehicle anomaly detection ALFA CNN orphan genes (OGs) hybrid features machine learning angiosperm delay prediction model lightweight neural network lightweight attention mechanism semi-supervised classification co-training method instance selection granular computing information granulation variable structure of interacting multiple-model symmetric model set optimization method proportional reduction optimization method expected model optimization method multi-granulation rough set hesitant trapezoidal fuzzy set air quality evaluation dependency structure graph convolution network question answering data mining network clustering protein complex detection power-law distribution topological characteristics data enhancement few-shot data smart home generative adversarial networks intrusion detection bilingual short text with emoji emotional fusion emotional fluctuation emotional computation knowledge graph embedding chunked learning network data-driven approach picks wear state recognition wavelet packet decomposition Bayesian-LSTM absolute positioning accuracy deep belief network differential evolution algorithm industrial robot off-line error compensation sequential recommendation local fluctuation global stability Stochastic Shared Embeddings AUV underwater navigation dataset inertial navigation DVL ultrasound imaging plane-wave beamforming coherence factor adaptive spatio-temporally smoothed delay multiply and sum beamforming data augmentation deep learning data quality big data multi-head attention BiLSTM energy consumption IoT-based power control systems optimization using sensor data predictive control pharmaceutical technology process modeling exploratory data analysis multiscale neighbors attentional mechanism collaborative embedding recommendation computer science artificial intelligence burnout clinical reasoning imbalanced datasets stratified sampling prediction classification accuracy wrapper classes target detection YOLOV5s attention mechanism lightweighting healthcare imputation algorithms incomplete data neighborhood similarity frequency synthesizer direct frequency synthesizer indirect frequency synthesizer railway track circuit n/a thema EDItEUR::U Computing and Information Technology::UY Computer science Advances in Intelligent Data Analysis and Its Applications |
| title | Advances in Intelligent Data Analysis and Its Applications |
| title_full | Advances in Intelligent Data Analysis and Its Applications |
| title_fullStr | Advances in Intelligent Data Analysis and Its Applications |
| title_full_unstemmed | Advances in Intelligent Data Analysis and Its Applications |
| title_short | Advances in Intelligent Data Analysis and Its Applications |
| title_sort | advances in intelligent data analysis and its applications |
| topic | intuitionistic fuzzy concept rough set multi-granularity relative macro-knowledge distance multigranulation rough sets optimistic approximation pessimistic approximation cost-sensitive decision-making applications context awareness attention network dynamic user preferences next POI recommendation IoT unmanned aerial vehicle anomaly detection ALFA CNN orphan genes (OGs) hybrid features machine learning angiosperm delay prediction model lightweight neural network lightweight attention mechanism semi-supervised classification co-training method instance selection granular computing information granulation variable structure of interacting multiple-model symmetric model set optimization method proportional reduction optimization method expected model optimization method multi-granulation rough set hesitant trapezoidal fuzzy set air quality evaluation dependency structure graph convolution network question answering data mining network clustering protein complex detection power-law distribution topological characteristics data enhancement few-shot data smart home generative adversarial networks intrusion detection bilingual short text with emoji emotional fusion emotional fluctuation emotional computation knowledge graph embedding chunked learning network data-driven approach picks wear state recognition wavelet packet decomposition Bayesian-LSTM absolute positioning accuracy deep belief network differential evolution algorithm industrial robot off-line error compensation sequential recommendation local fluctuation global stability Stochastic Shared Embeddings AUV underwater navigation dataset inertial navigation DVL ultrasound imaging plane-wave beamforming coherence factor adaptive spatio-temporally smoothed delay multiply and sum beamforming data augmentation deep learning data quality big data multi-head attention BiLSTM energy consumption IoT-based power control systems optimization using sensor data predictive control pharmaceutical technology process modeling exploratory data analysis multiscale neighbors attentional mechanism collaborative embedding recommendation computer science artificial intelligence burnout clinical reasoning imbalanced datasets stratified sampling prediction classification accuracy wrapper classes target detection YOLOV5s attention mechanism lightweighting healthcare imputation algorithms incomplete data neighborhood similarity frequency synthesizer direct frequency synthesizer indirect frequency synthesizer railway track circuit n/a thema EDItEUR::U Computing and Information Technology::UY Computer science |
| topic_facet | intuitionistic fuzzy concept rough set multi-granularity relative macro-knowledge distance multigranulation rough sets optimistic approximation pessimistic approximation cost-sensitive decision-making applications context awareness attention network dynamic user preferences next POI recommendation IoT unmanned aerial vehicle anomaly detection ALFA CNN orphan genes (OGs) hybrid features machine learning angiosperm delay prediction model lightweight neural network lightweight attention mechanism semi-supervised classification co-training method instance selection granular computing information granulation variable structure of interacting multiple-model symmetric model set optimization method proportional reduction optimization method expected model optimization method multi-granulation rough set hesitant trapezoidal fuzzy set air quality evaluation dependency structure graph convolution network question answering data mining network clustering protein complex detection power-law distribution topological characteristics data enhancement few-shot data smart home generative adversarial networks intrusion detection bilingual short text with emoji emotional fusion emotional fluctuation emotional computation knowledge graph embedding chunked learning network data-driven approach picks wear state recognition wavelet packet decomposition Bayesian-LSTM absolute positioning accuracy deep belief network differential evolution algorithm industrial robot off-line error compensation sequential recommendation local fluctuation global stability Stochastic Shared Embeddings AUV underwater navigation dataset inertial navigation DVL ultrasound imaging plane-wave beamforming coherence factor adaptive spatio-temporally smoothed delay multiply and sum beamforming data augmentation deep learning data quality big data multi-head attention BiLSTM energy consumption IoT-based power control systems optimization using sensor data predictive control pharmaceutical technology process modeling exploratory data analysis multiscale neighbors attentional mechanism collaborative embedding recommendation computer science artificial intelligence burnout clinical reasoning imbalanced datasets stratified sampling prediction classification accuracy wrapper classes target detection YOLOV5s attention mechanism lightweighting healthcare imputation algorithms incomplete data neighborhood similarity frequency synthesizer direct frequency synthesizer indirect frequency synthesizer railway track circuit n/a thema EDItEUR::U Computing and Information Technology::UY Computer science |
| url | ONIX_20240514_9783039286157_50 |