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Machine Learning Algorithms for Industrial Applications de Santosh Kumar Das

Machine Learning Algorithms for Industrial Applications: Studies in Computational Intelligence, cartea 907

Editat de Santosh Kumar Das, Shom Prasad Das, Nilanjan Dey, Aboul-Ella Hassanien
en Limba Engleză Paperback – 20 iul 2021
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.   

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Specificații

ISBN-13: 9783030506438
ISBN-10: 3030506436
Ilustrații: XVII, 315 p. 164 illus., 117 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.47 kg
Ediția:1st ed. 2021
Editura: Springer International Publishing
Colecția Springer
Seria Studies in Computational Intelligence

Locul publicării:Cham, Switzerland

Cuprins

​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.

Textul de pe ultima copertă

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.

Caracteristici

Discusses recently developed, innovative machine learning algorithms for applications in industry Presents the state of the art in machine learning algorithms for a global industrial scenario Written by respected experts in the field