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Olga Grjasnowa liest aus "JULI, AUGUST, SEPTEMBER
04.02.2025 um 19:30 Uhr
Applied Intelligent Decision Making in Machine Learning
von Himansu Das, Jitendra Kumar Rout, Suresh Chandra Moharana
Verlag: Taylor & Francis Ltd (Sales)
Reihe: Computational Intelligence in Engineering Problem Solving
Taschenbuch
ISBN: 978-0-367-50493-9
Erschienen am 15.05.2022
Sprache: Englisch
Format: 234 mm [H] x 156 mm [B] x 14 mm [T]
Gewicht: 372 Gramm
Umfang: 252 Seiten

Preis: 86,00 €
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Klappentext
Biografische Anmerkung
Inhaltsverzeichnis

The objective of this edited book is to share outcomes on various research domains to develop efficient, adaptive and intelligent models to handle the challenges related to decision making in various aspects. It incorporates the advances of machine intelligent techniques in decision making process and its applications.



Himansu Das is working as an Assistant Professor in the School of Computer Engineering, Kalinga Institute of Industrial Technology (KIIT) Deemed to be University, Bhubaneswar, India.

Jitendra Kumar Rout is an Assistant Professor in School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, India.

Suresh Chandra Moharana is an Assistant Professor in School of Computer Engineering at KIIT Deemed to be University.

Nilanjan Dey is an Assistant Professor in Department of Information Technology at Techno India College of Technology (under Techno India Group), Kolkata, India.



1. Data Stream Mining for Big Data.

2. Decoding Common Machine Learning Methods: Agricultural Application Case Studies Using Open Source Software.

3. A Multi-Stage Hybrid Model for Odia Compound Character Recognition.

4. Development of Hybrid Computational Approaches for Landslide Susceptibility Mapping Using Remotely Sensed Data in East Sikkim, India.

5. Domain-Specific Journal Recommendation Using Feed Forward Neural Network.

6. Forecasting Air Quality in India through an Ensemble Clustering Technique.

7. Intelligence-Based Health Biomarker Identification System Using Microarray Analysis.

8. Extraction of Medical Entities Using Matrix-Based Pattern-Matching Method.

9. Supporting Environmental Decision Making: Application of Machine Learning Techniques to Australia's Emissions.

10. Prediction Analysis of Exchange Rate Forecasting Using Deep Learning-Based Neural Network Models.

11. Optimal Selection of Features Using Deep Learning-Based Optimization Algorithm for Classification.

12. An Enhanced Image Dehazing Procedure Using CLAHE and Guided Filter.


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