Machine Learning Algorithms for Industrial Applications
Published on 18. July 2020
XVII, 315 pages
978-3-030-50641-4 (ISBN)
Description
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.
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.
More details
Series
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Product notice
Reflowable
Illustrations
XVII, 315 p. 164 illus., 117 illus. in color.
File size
14,26 MB
ISBN-13
978-3-030-50641-4 (9783030506414)
DOI
10.1007/978-3-030-50641-4
Schweitzer Classification
Other editions
Additional editions
Santosh Kumar Das | Shom Prasad Das | Nilanjan Dey
Machine Learning Algorithms for Industrial Applications
Book
07/2020
Springer
€160.49
Shipment within 7-9 days
Persons
Content
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.
