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Innovative trends in computational i...

Tomar, Ravi.

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Innovative trends in computational intelligence

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Innovative trends in computational intelligence/ edited by Ravi Tomar ... [et al.].
其他作者:	Tomar, Ravi.
出版者:	Cham :Springer International Publishing : : 2022.,
面頁冊數:	xvii, 288 p. :ill., digital ;24 cm.
內容註:	Part I. Innovative Trends in Computational Intelligence -- Chapter 1. Data Mining in Healthcare and Prediction Model Using Data-Mining Technique on Covid-19 -- Chapter 2. Computational Intelligence in Intelligent Transportation Systems: An Overview -- Chapter 3. Insights to Computational Intelligence Techniques for Computer Vision -- Chapter 4. A two-stage multi-feature selection method to predict healthcare data using neural network -- Chapter 5. Computational Approaches for Detection and Classiﬁcation of Crop Diseases -- Chapter 6. Three-Layer Multimodal Biometric Fusion Using SIFT and SURF Descriptors for Improved Accuracy of Authentication of Human Identity -- Chapter 7. Applying Computation Intelligence for Improved Computer Vision Capabilities -- Chapter 8. ECG Feature Extraction -- Chapter 9. Computational Intelligence in Web Min -- Chapter 10. A Review on Cognitive Computational Neuroscience: Overview, Models and Applications -- Chapter 11. Artificial Neural Network: Models, Applications and Challenges -- Chapter 12. Proportional and Multi-Stimulations Haptic Device for Active Upper Limbs Prosthetics Control.
Contained By:	Springer Nature eBook
標題:	Computational intelligence. -
電子資源:	https://doi.org/10.1007/978-3-030-78284-9
ISBN:	9783030782849

Innovative trends in computational intelligence
Innovative trends in computational intelligence[electronic resource] /edited by Ravi Tomar ... [et al.]. - Cham :Springer International Publishing :2022. - xvii, 288 p. :ill., digital ;24 cm. - Eai/springer innovations in communication and computing,2522-8609. - Eai/springer innovations in communication and computing..

Part I. Innovative Trends in Computational Intelligence -- Chapter 1. Data Mining in Healthcare and Prediction Model Using Data-Mining Technique on Covid-19 -- Chapter 2. Computational Intelligence in Intelligent Transportation Systems: An Overview -- Chapter 3. Insights to Computational Intelligence Techniques for Computer Vision -- Chapter 4. A two-stage multi-feature selection method to predict healthcare data using neural network -- Chapter 5. Computational Approaches for Detection and Classiﬁcation of Crop Diseases -- Chapter 6. Three-Layer Multimodal Biometric Fusion Using SIFT and SURF Descriptors for Improved Accuracy of Authentication of Human Identity -- Chapter 7. Applying Computation Intelligence for Improved Computer Vision Capabilities -- Chapter 8. ECG Feature Extraction -- Chapter 9. Computational Intelligence in Web Min -- Chapter 10. A Review on Cognitive Computational Neuroscience: Overview, Models and Applications -- Chapter 11. Artificial Neural Network: Models, Applications and Challenges -- Chapter 12. Proportional and Multi-Stimulations Haptic Device for Active Upper Limbs Prosthetics Control.

This book addresses the key problems that computational intelligence aims to solve, including (i) the involved computational process might be too complex for mathematical reasoning; (ii) it might contain some uncertainties during the process, or (iii) by nature, the computational process is a randomly determined one (heuristic) The contributors make use of methods that are close to the human's way of reasoning, that is, available information might be inexact or incomplete, yet it would be able to produce controlled actions in an adaptive way. Approaches presented in the book include swarm intelligence, artificial immune systems, image processing, data mining, natural language processing, text mining, and other solutions involving artificial intelligence methodologies. Addresses key computational issues that can be solved by computational intelligence; Introduces various application domains by which computational intelligence is the preferred solution; Includes approaches such as swam intelligence, data mining, and artificial intelligence.

ISBN: 9783030782849

Standard No.: 10.1007/978-3-030-78284-9doiSubjects--Topical Terms:

595739
Computational intelligence.

LC Class. No.: Q342 / .I56 2022

Dewey Class. No.: 006.3

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505 0 $a Part I. Innovative Trends in Computational Intelligence -- Chapter 1. Data Mining in Healthcare and Prediction Model Using Data-Mining Technique on Covid-19 -- Chapter 2. Computational Intelligence in Intelligent Transportation Systems: An Overview -- Chapter 3. Insights to Computational Intelligence Techniques for Computer Vision -- Chapter 4. A two-stage multi-feature selection method to predict healthcare data using neural network -- Chapter 5. Computational Approaches for Detection and Classiﬁcation of Crop Diseases -- Chapter 6. Three-Layer Multimodal Biometric Fusion Using SIFT and SURF Descriptors for Improved Accuracy of Authentication of Human Identity -- Chapter 7. Applying Computation Intelligence for Improved Computer Vision Capabilities -- Chapter 8. ECG Feature Extraction -- Chapter 9. Computational Intelligence in Web Min -- Chapter 10. A Review on Cognitive Computational Neuroscience: Overview, Models and Applications -- Chapter 11. Artificial Neural Network: Models, Applications and Challenges -- Chapter 12. Proportional and Multi-Stimulations Haptic Device for Active Upper Limbs Prosthetics Control.
520 $a This book addresses the key problems that computational intelligence aims to solve, including (i) the involved computational process might be too complex for mathematical reasoning; (ii) it might contain some uncertainties during the process, or (iii) by nature, the computational process is a randomly determined one (heuristic) The contributors make use of methods that are close to the human's way of reasoning, that is, available information might be inexact or incomplete, yet it would be able to produce controlled actions in an adaptive way. Approaches presented in the book include swarm intelligence, artificial immune systems, image processing, data mining, natural language processing, text mining, and other solutions involving artificial intelligence methodologies. Addresses key computational issues that can be solved by computational intelligence; Introduces various application domains by which computational intelligence is the preferred solution; Includes approaches such as swam intelligence, data mining, and artificial intelligence.
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