Biologically Inspired Techniques in Many-Criteria Decision Making: International Conference on Biologically Inspired Techniques in Many-Criteria ... and Analytics in Intelligent Systems, 10) 9783030390327, 9783030390334, 3030390322

This book addresses many-criteria decision-making (MCDM), a process used to find a solution in an environment with sever

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Table of contents :
Preface
Contents
Biologically Inspired Techniques and Their Applications
Classification of Arrhythmia Using Artificial Neural Network with Grey Wolf Optimization
1 Introduction
2 Related Literature
3 Methodology
3.1 Grey Wolf Optimization (GWO)
4 Experimental Setup and Result
5 Conclusion
References
Multi-objective Biogeography-Based Optimization for Influence Maximization-Cost Minimization in Social Networks
1 Introduction
2 Backgrounds
2.1 Social Influence, Influence Maximization, and Influence Maximization-Cost Minimization Problem
2.2 Overview of Multi-objective Optimization
3 Related Works
4 Our Proposed Approach
4.1 Solution Encoding
4.2 Selection Strategy for Determining Serviceable Nodes, Population Initialization, and for Mutation
4.3 Skip Migration When a Mutation Occurs
4.4 Evolving Mutation Rate
4.5 Consolidated Algorithm
5 Experimental Setup and Result Analysis
6 Conclusion
References
Classification of Credit Dataset Using Improved Particle Swarm Optimization Tuned Radial Basis Function Neural Networks
1 Introduction
2 Literature Survey
3 Machine Learning Techniques Used for Credit Risk Analysis
3.1 Radial Basis Function Neural Networks
3.2 Canonical Particle Swarm Optimization Algorithm
3.3 Improved PSO Tuned RBFNN Algorithm
4 Experimental Works
4.1 Environment
4.2 Parameters Details
5 Result Analysis
6 Conclusions
References
Multi-Verse Optimization of Multilayer Perceptrons (MV-MLPs) for Efficient Modeling and Forecasting of Crude Oil Prices Data
1 Introduction
2 Related Work
3 MV-MLP
4 Experimental Results and Discussion
5 Concluding Remarks
References
Application of Machine Learning to Predict Diseases Based on Symptoms in Rural India
1 Introduction
2 Materials and Methods
2.1 Information Gain
2.2 Entropy
2.3 Algorithm
3 Results and Discussion
4 Summary/Conclusion
References
Classification of Real Time Noisy Fingerprint Images Using Flann
1 Introduction
2 Finger Print Classification
3 BBO-FLANN Hybrid Network
4 Result Analysis
5 Conclusion
References
Software Reliability Prediction with Ensemble Method and Virtual Data Point Incorporation
1 Introduction
2 Related Study
3 Methods and Methodologies
3.1 Ridge Regression and Bayesian Ridge Regression
3.2 Support Vector Regression (SVR)
3.3 K-Nearest Neighbors Regression (KNN)
3.4 Artificial Neural Network (ANN)
3.5 Radial Basis Function Network (RBFN)
3.6 Virtual Data Generation Methods
3.7 Liner Interpolation
4 Proposed Model
5 Experimental Study and Result Analysis
6 Conclusions
References
Hyperspectral Image Classification Using Stochastic Gradient Descent Based Support Vector Machine
1 Introduction
2 Related Work
3 Proposed Model and Techniques Used
4 Results and Discussion
4.1 Dataset Description
4.2 Experimental Setup
4.3 Result Analysis
5 Conclusion
References
A Survey on Ant Colony Optimization for Solving Some of the Selected NP-Hard Problem
1 Introduction
2 Computational Complexity of Algorithms and NP-Hard Problems
3 Basics of Ant Colony Optimization
3.1 Background of Ant Colony Optimization
3.2 Graph Representation of ACO Algorithm
3.3 ACO Algorithm
4 Ant Colony Optimization for NP-Hard Problems
4.1 Ant Colony Optimization for Traveling Salesman Problem
4.2 Ant Colony Optimization for Subset Selection Problem
4.3 Ant Colony Optimization for 0/1 Knapsack Problem
4.4 Ant Colony Optimization for Minimum Vertex Cover Problem
5 Discussions and Conclusions
References
Machine Learning Models for Stock Prediction Using Real-Time Streaming Data
1 Introduction
2 Machine Learning Techniques Adopted
2.1 Decision Tree
2.2 Polynomial Linear Regression
2.3 Support Vector Regression (SVR)
2.4 Random Forest Generation
3 Proposed Work and Analysis
4 Performance Measures
5 Result and Analysis
6 Conclusion and Future Work
References
Epidemiology of Breast Cancer (BC) and Its Early Identification via Evolving Machine Learning Classification Tools (MLCT)–A Study
1 Introduction
2 Cancer Incidence and Cancer Cases Vary by State
3 Risk Factor
4 Availability of Open Source Data for Research
5 ML Algorithm for Cancer Prediction
6 ANN for Cancer Research
7 Related Work
8 Conclusion and Recommendation
References
Ensemble Classification Approach for Cancer Prognosis and Prediction
1 Introduction
2 Materials and Methods
2.1 Dataset Pruning
2.2 Normalization (Min – Max Algorithm)
2.3 Feature Extraction (Double RBF Kernel Based Ranking of Feature)
2.4 KNN Classifier
2.5 MLP (Multi Linear Perceptron)
2.6 Decision Tree
3 Proposed Algorithm
4 Parameter Discussion
5 Experimental Evaluation
6 Dataset
6.1 Wisconsin Prognostic Breast Cancer (WPBC)
6.2 Five Bench Mark Cancer Dataset
7 Ranking of Classifier
8 Result Analysis and Comparison
8.1 Breast Cancer Prognosis
8.2 Cancer Prediction
9 Conclusion
References
Extractive Odia Text Summarization System: An OCR Based Approach
1 Introduction
2 Related Work
3 Experimental Setup
3.1 Data Preprocessing
3.2 Methodology
4 Result
5 Conclusion and Future Work
References
Predicting Sensitivity of Local News Articles from Odia Dailies
1 Introduction
2 Related Works
3 Methodology
3.1 Performance Evaluation Measure
4 Results Analysis
5 Conclusion
References
A Systematic Frame Work Using Machine Learning Approaches in Supply Chain Forecasting
1 Introduction
2 Related Works
3 Framework
4 Results
5 Conclusion
References
An Intelligent System on Computer-Aided Diagnosis for Parkinson’s Disease with MRI Using Machine Learning
1 Introduction
1.1 GBA
1.2 LRRK2
1.3 SNCA
2 Related Works
3 Architecture
4 Materials and Methods
4.1 Dataset
4.2 Data Pre-processing
5 Feature Classification
5.1 AdaBoost
5.2 Naïve Bayes
5.3 Random Forest
5.4 Logistic Regression
5.5 Decision Trees
5.6 Support Vector Machines
6 Implementation
7 Result
References
Multi-Criteria Decision Making Approaches
Operations on Picture Fuzzy Numbers and Their Application in Multi-criteria Group Decision Making Problems
1 Introduction
2 Preliminaries
2.1 Fuzzy Set
2.2 Intuitionistic Fuzzy Set
2.3 Picture Fuzzy Set
2.4 -cut of Picture Fuzzy Set
2.5 Triangular PFSs
3 Arithmetic Operations of Triangular PFSs and Their Examples
4 Numerical Examples
5 Ranking of Triangular PFSs Based on Value and Ambiguity
6 Multi-criteria Group Decision-Making Based on Arithmetic Operation Between Triangular PFSs
7 Hypothetical Case Study
7.1 Computational Procedure Is Discussed in Detail
8 Conclusion
References
Some Generalized Results on Multi-criteria Decision Making Model Using Fuzzy TOPSIS Technique
1 Introduction
2 Preliminaries
2.1 TOPSIS Method
2.2 Fuzzy TOPSIS Method
3 Proposed Methodology
4 Computational Illustration
5 Conclusion
References
Data Mining, Bioinformatics, and Cellular Communications
A Survey on FP-Tree Based Incremental Frequent Pattern Mining
1 Introduction
2 FP-tree Based Incremental FPM
2.1 Two-Pass FPM
2.2 Single-Pass FPM
3 Research Issues and Challenges
4 Conclusion
References
Improving Co-expressed Gene Pattern Finding Using Gene Ontology
1 Introduction
2 Combined Similarity (ComSim)
3 Proposed Technique PatGeneClus
4 Experimental Results
5 Conclusions
References
Survey of Methods Used for Differential Expression Analysis on RNA Seq Data
1 Introduction
2 Issues and Challenges
3 Normalisation of RNA-Seq Data
4 Differential Gene Expression
4.1 Mathematical Definition
5 Differential Gene Expression Analysis
5.1 Tools Used for Differential Gene Expression Analysis
5.2 Results of the Study on Differential Expression Packages
6 Clustering the Results
7 Conclusions
References
Adaptive Antenna Tilt for Cellular Coverage Optimization in Suburban Scenario
1 Introduction
2 Related Work
3 System Model
3.1 Radio Channel Modelling
3.2 Base Station Antenna Radiation Pattern Modelling
3.3 Application of Reinforcement Learning Algorithm to the Current Scenario
4 Results and Analysis
5 Conclusion
References
A Survey of the Different Itemset Representation for Candidate Generation
1 Introduction
2 Layout for Itemsets Representation
3 Data Structures for Itemset Representation
4 Experimental Analysis
5 Conclusion
References
Author Index

Biologically Inspired Techniques in Many-Criteria Decision Making: International Conference on Biologically Inspired Techniques in Many-Criteria ... and Analytics in Intelligent Systems, 10)
 9783030390327, 9783030390334, 3030390322

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