Biologically Inspired Techniques in Many-Criteria Decision Making

International Conference on Biologically Inspired Techniques in Many-Criteria Decision Making (BITMDM-2019)

AvSatchidananda Dehuri,Bhabani Shankar Prasad Mishra

Inbunden, Engelska, 2020

Del 10 i serien Learning and Analytics in Intelligent Systems

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Beskrivning

This book addresses many-criteria decision-making (MCDM), a process used to find a solution in an environment with several criteria. Accordingly, many current research efforts are focused on the implementation of biologically inspired algorithms (BIAs), which are well suited to solving uni-objective problems.

Produktinformation

Utgivningsdatum:2020-01-22
Mått:155 x 235 x 21 mm
Vikt:582 g
Format:Inbunden
Språk:Engelska
Serie:Learning and Analytics in Intelligent Systems
Antal sidor:258
Upplaga:20001
Förlag:Springer Nature Switzerland AG
ISBN:9783030390327

Utforska kategorier

Databaser inom Data och IT
Artificiell intelligens inom Data och IT

Innehållsförteckning

Chapter 1: Classification of Arrhythmia Using Artificial Neural Network with Grey Wolf Optimization.- Chapter 2: Multi-objective Biogeography-Based Optimization for Influence Maximization-Cost Minimization in Social Networks.- Chapter 3: Classification of Credit Dataset Using Improved Particle Swarm Optimization Tuned Radial Basis Function Neural Networks.- Chapter 4: Multi-verse Optimization of Multilayer Perceptrons (MV-MLPs) for Efficient Modeling and Forecasting of Crude Oil Prices Data.- Chapter 5: Application of machine learning to predict diseases based on symptoms in rural India.- Chapter 6: Classıfıcatıon of Real Tıme Noısy Fıngerprınt Images Usıng FLANN.- Chapter 7: Software Reliability Prediction with Ensemble Method and Virtual Data Point Incorporation.- Chapter 8: Hyperspectral Image Classification using Stochastic Gradient Descent based Support Vector Machine.- Chapter 9: A Survey on Ant Colony Optimization for Solving Some of the Selected NP-Hard Problem.- Chapter 10: Machine Learning Models for Stock Prediction using Real-Time Streaming Data.- Chapter 11: Epidemiology of Breast Cancer (BC) and its Early Identification via Evolving Machine Learning Classification Tools (MLCT)–A Study.- Chapter 12: Ensemble Classification Approach for Cancer Prognosis and Prediction.- Chapter 13: Extractive Odia Text Summarization System: An OCR based Approach.- Chapter 14: Predicting sensitivity of local news articles from Odia dailies.- Chapter 15: A systematic frame work using machine learning approaches in supply chain forecasting.- Chapter 16: An Intelligent system on computer-aided diagnosis for Parkinson’s disease with MRI using Machine Learning.- Chapter 17: Operations on Picture Fuzzy Numbers and their Application in Multi-Criteria Group Decision Making Problems.- Chapter 18: Some Generalized Results on Multi-Criteria Decision Making Model using Fuzzy TOPSIS Technique.- Chapter 19: A Survey on FP-Tree Based Incremental Frequent Pattern Mining.- Chapter 20: Improving Co-expressed Gene Pattern Finding Using Gene Ontology.- Chapter 21: Survey of Methods Used for Differential Expression Analysis on RNA Seq Data.- Chapter 22: Adaptive Antenna Tilt for Cellular Coverage Optimization in Suburban Scenario.- Chapter 23: A survey of the different itemset representation for candidate.