UID:
almahu_9949315747802882
Format:
XIV, 735 p. 312 illus., 210 illus. in color.
,
online resource.
Edition:
1st ed. 2022.
ISBN:
9789811687396
Series Statement:
Smart Innovation, Systems and Technologies, 271
Content:
This book includes best-selected, high-quality research papers presented at Second International Conference on Biologically Inspired Techniques in Many Criteria Decision Making (BITMDM 2021) organized by Department of Information & Communication Technology, Fakir Mohan University, Balasore, Odisha, India, during December 20-21, 2021. This proceeding presents the recent advances in techniques which are biologically inspired and their usage in the field of many criteria decision making. The topics covered are biologically inspired algorithms, nature-inspired algorithms, multi-criteria optimization, multi-criteria decision making, data mining, big-data analysis, cloud computing, IOT, machine learning and soft computing, smart technologies, crypt-analysis, cognitive informatics, computational intelligence, artificial intelligence and machine learning, data management exploration and mining, computational intelligence, and signal and image processing.
Note:
Cloud-based Smart Grids: Opportunities and Challenges -- A Resource Aware Load Balancing Strategy for Real-Time, Cross-Vertical IoT Applications -- An Elitist Artificial - electric - field - algorithm - based Artificial Neural Network for Financial Time Series Forecasting -- COVID - 19 Severıty Predıctıons: An Analysis Usıng Correlatıon Measures -- Antenna Array Optimization For Side Lobe Level: A Brief Review -- Accuracy Analysis for Predicting Heart Attacks Based on Various Machine Learning Algorithms -- Link Recommendation for Social Influence Maximization -- Performance Analysis of State-of-the art Classifiers and Stack Ensemble Model for Liver Disease Diagnosis -- CryptedWe: An end-to-encryption with fake news detection messaging system -- Enabling Data Security in Electronic Voting System using Blockchain -- Prediction of Used Car Prices Using Machine Learning -- Complexity Classification of Object-oriented Projects Based on Class Model Information Using Quasi-opposition Rao Algorithm Based Neural Networks -- Mood Based Movie Recommendation System.
In:
Springer Nature eBook
Additional Edition:
Printed edition: ISBN 9789811687389
Additional Edition:
Printed edition: ISBN 9789811687402
Additional Edition:
Printed edition: ISBN 9789811687419
Language:
English
DOI:
10.1007/978-981-16-8739-6
URL:
https://doi.org/10.1007/978-981-16-8739-6
URL:
Volltext
(URL des Erstveröffentlichers)
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