東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁 到查詢結果 [ subject:"Artificial intelligence- Industrial applications." ]

切換: 標籤 | MARC模式 | ISBD

Machine learning algorithms for indu...

Das, Santosh Kumar.

FindBook

Google Book

Amazon

博客來

Machine learning algorithms for industrial applications

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Machine learning algorithms for industrial applications/ edited by Santosh Kumar Das .. [et al.].
其他作者:	Das, Santosh Kumar.
出版者:	Cham :Springer International Publishing : : 2021.,
面頁冊數:	xvii, 315 p. :ill., digital ;24 cm.
內容註:	Part I: Natural Language Processing -- A Hybrid Feature Selection Approach Based on LSI for Classification of Urdu Text -- Automated Document Categorization Model -- Automated Categorization & Mining Tweets for Disaster Management -- Sentiment Analysis in Airline Data: Customer Rating Based Recommendation Prediction using WEKA -- Part II: Computer Vision -- Image Inpainting for Irregular Holes using Extreme Learning Machine -- OCR using Computer Vision and Machine Learning -- Few Shot Learning for Medical Imaging -- Hyperspectral Remote Sensing Image Classification using Active Learning -- A Smart Document Converter: Conversion of Handwritten Text Document to Computerized Text Document -- GRNN Based An Intelligent Technique for Image Inpainting -- Part III: Data Analysis and Prediction -- Content-Based Airline Recommendation Prediction using Machine Learning Techniques -- Meta-heuristic Based Approach for Slope Stability Analysis to Design an Optimal Soil Slope -- An Application of Operational Analytics: for Predicting Sales Revenue of Restaurant -- Application of Machine Learning Algorithm for Anomaly Detection for Industrial Pumps -- Part IV: Decision Making System -- Fast Accessing Non-volatile, High Performance-High Density, Optimized Array for Machine Learning Processor -- Long Term Evolution for Secured Smart Railway Communications using Internet of Things -- Application of the Flower Pollination Algorithm to Locate Critical Failure Surface for Slope Stability Analysis.
Contained By:	Springer Nature eBook
標題:	Machine learning. -
電子資源:	https://doi.org/10.1007/978-3-030-50641-4
ISBN:	9783030506414

Machine learning algorithms for industrial applications
Machine learning algorithms for industrial applications[electronic resource] /edited by Santosh Kumar Das .. [et al.]. - Cham :Springer International Publishing :2021. - xvii, 315 p. :ill., digital ;24 cm. - Studies in computational intelligence,v.9071860-949X ;. - Studies in computational intelligence ;v.907..

Part I: Natural Language Processing -- A Hybrid Feature Selection Approach Based on LSI for Classification of Urdu Text -- Automated Document Categorization Model -- Automated Categorization & Mining Tweets for Disaster Management -- Sentiment Analysis in Airline Data: Customer Rating Based Recommendation Prediction using WEKA -- Part II: Computer Vision -- Image Inpainting for Irregular Holes using Extreme Learning Machine -- OCR using Computer Vision and Machine Learning -- Few Shot Learning for Medical Imaging -- Hyperspectral Remote Sensing Image Classification using Active Learning -- A Smart Document Converter: Conversion of Handwritten Text Document to Computerized Text Document -- GRNN Based An Intelligent Technique for Image Inpainting -- Part III: Data Analysis and Prediction -- Content-Based Airline Recommendation Prediction using Machine Learning Techniques -- Meta-heuristic Based Approach for Slope Stability Analysis to Design an Optimal Soil Slope -- An Application of Operational Analytics: for Predicting Sales Revenue of Restaurant -- Application of Machine Learning Algorithm for Anomaly Detection for Industrial Pumps -- Part IV: Decision Making System -- Fast Accessing Non-volatile, High Performance-High Density, Optimized Array for Machine Learning Processor -- Long Term Evolution for Secured Smart Railway Communications using Internet of Things -- Application of the Flower Pollination Algorithm to Locate Critical Failure Surface for Slope Stability Analysis.

This book explores several problems and their solutions regarding data analysis and prediction for industrial applications. Machine learning is a prominent topic in modern industries: its influence can be felt in many aspects of everyday life, as the world rapidly embraces big data and data analytics. Accordingly, there is a pressing need for novel and innovative algorithms to help us find effective solutions in industrial application areas such as media, healthcare, travel, finance, and retail. In all of these areas, data is the crucial parameter, and the main key to unlocking the value of industry. The book presents a range of intelligent algorithms that can be used to filter useful information in the above-mentioned application areas and efficiently solve particular problems. Its main objective is to raise awareness for this important field among students, researchers, and industrial practitioners.

ISBN: 9783030506414

Standard No.: 10.1007/978-3-030-50641-4doiSubjects--Topical Terms:

533906
Machine learning.

LC Class. No.: Q325.5 / .M33 2021

Dewey Class. No.: 006.31

Machine learning algorithms for industrial applications
LDR:03505nmm a2200337 a 4500 001 2235600
003 DE-He213
005 20200718191239.0
006 m d
007 cr nn 008maaau
008 211111s2021 sz s 0 eng d
020 $a 9783030506414 $q (electronic bk.)
020 $a 9783030506407 $q (paper)
024 7 $a 10.1007/978-3-030-50641-4 $2 doi
035 $a 978-3-030-50641-4
040 $a GP $c GP
041 0 $a eng
050 4 $a Q325.5 $b .M33 2021
072 7 $a UYQ $2 bicssc
072 7 $a TEC009000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.31 $2 23
090 $a Q325.5 $b .M149 2021
245 0 0 $a Machine learning algorithms for industrial applications $h [electronic resource] / $c edited by Santosh Kumar Das .. [et al.].
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a xvii, 315 p. : $b ill., digital ; $c 24 cm.
490 1 $a Studies in computational intelligence, $x 1860-949X ; $v v.907
505 0 $a Part I: Natural Language Processing -- A Hybrid Feature Selection Approach Based on LSI for Classification of Urdu Text -- Automated Document Categorization Model -- Automated Categorization & Mining Tweets for Disaster Management -- Sentiment Analysis in Airline Data: Customer Rating Based Recommendation Prediction using WEKA -- Part II: Computer Vision -- Image Inpainting for Irregular Holes using Extreme Learning Machine -- OCR using Computer Vision and Machine Learning -- Few Shot Learning for Medical Imaging -- Hyperspectral Remote Sensing Image Classification using Active Learning -- A Smart Document Converter: Conversion of Handwritten Text Document to Computerized Text Document -- GRNN Based An Intelligent Technique for Image Inpainting -- Part III: Data Analysis and Prediction -- Content-Based Airline Recommendation Prediction using Machine Learning Techniques -- Meta-heuristic Based Approach for Slope Stability Analysis to Design an Optimal Soil Slope -- An Application of Operational Analytics: for Predicting Sales Revenue of Restaurant -- Application of Machine Learning Algorithm for Anomaly Detection for Industrial Pumps -- Part IV: Decision Making System -- Fast Accessing Non-volatile, High Performance-High Density, Optimized Array for Machine Learning Processor -- Long Term Evolution for Secured Smart Railway Communications using Internet of Things -- Application of the Flower Pollination Algorithm to Locate Critical Failure Surface for Slope Stability Analysis.
520 $a This book explores several problems and their solutions regarding data analysis and prediction for industrial applications. Machine learning is a prominent topic in modern industries: its influence can be felt in many aspects of everyday life, as the world rapidly embraces big data and data analytics. Accordingly, there is a pressing need for novel and innovative algorithms to help us find effective solutions in industrial application areas such as media, healthcare, travel, finance, and retail. In all of these areas, data is the crucial parameter, and the main key to unlocking the value of industry. The book presents a range of intelligent algorithms that can be used to filter useful information in the above-mentioned application areas and efficiently solve particular problems. Its main objective is to raise awareness for this important field among students, researchers, and industrial practitioners.
650 0 $a Machine learning. $3 533906
650 0 $a Artificial intelligence $x Industrial applications. $3 653318
650 1 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Artificial Intelligence. $3 769149
700 1 $a Das, Santosh Kumar. $3 3443808
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Studies in computational intelligence ; $v v.907. $3 3486231
856 4 0 $u https://doi.org/10.1007/978-3-030-50641-4
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)