Soft Computing for Problem Solving: Proceedings of SocProS 2020, Volume 2 (Advances in Intelligent Systems and Computing, 1393)

Preface
Contents
About the Editors
A Deep Semi-supervised Approach for Multi-label Land-Cover Classification Under Scarcity of Labelled Images
	1 Introduction
	2 Proposed Methodology
		2.1 Selection of the Most-Confident Images from the Training Set
		2.2 Segmentation and Generation of Class Templates
		2.3 One-Versus-All Training
		2.4 Assignment of Multiple Class Labels to the Test Image
	3 Experimental Results
		3.1 Description of the Datasets
		3.2 Details of the Implementation
		3.3 Analysis of the Results
	4 Conclusion
	References
Role of Individual Samples in Modified Possibilistic c-Means Classifier for Handling Heterogeneity Within Mustard Crop
	1 Introduction
	2 Vegetation Indices and Heterogeneity
	3 Mathematical Concepts of Algorithm
		3.1 Pseudo Code of MPCM Algorithm
	4 Study Area and Dataset Used
		4.1 Study Area
		4.2 Study Area
	5 Methodology
	6 Results and Discussion
	7 Conclusion
	References
Specially Structured Flow Shop Scheduling Models with Processing Times as Trapezoidal Fuzzy Numbers to Optimize Waiting Time of Jobs
	1 Introduction
	2 Preliminaries
		2.1 Fuzzy Number
		2.2 Trapezoidal Fuzzy Number
		2.3 Yager’s Ranking Method
		2.4 Waiting Time of Jobs
		2.5 Total Waiting Time of Jobs
	3 Format of Framework
		3.1 Notation
		3.2 Postulates
		3.3 Problem Description
		3.4 Significance
	4 Theorems and Results
	5 Algorithm
	6 Numerical Illustration
	7 Computational Analysis
	8 Conclusion
	References
Potential Fishing Zone Characterization in the Indian Ocean by Machine Learning Approach
	1 Introduction
	2 Study Area and Data
	3 Detection of Potential Fishing Zone
	4 Methodology and Results
		4.1 Decision Tree
		4.2 Naïve Bayes Method
		4.3 Hybrid Decision Tree Model
	5 Fish Catch Algorithm
	6 Conclusions
	References
A Novel Method to Optimize Interval Length for Intuitionistic Fuzzy Time Series
	1 Introduction
	2 Preliminaries
	3 IFTS Forecasting Method of Kumar and Gangwar
	4 Proposed Model Based on Optimization of MSE and Its Implementation
	5 Results and Discussion
	References
Low-Altitude Unmanned Aerial Vehicle for Real-Time Greenhouse Plant Disease Monitoring Using Convolutional Neural Network
	1 Introduction
	2 Design and Challenges
		2.1 UAV and Data Acquisition
		2.2 Data Preparation
		2.3 Infected Segmentation Training
		2.4 MQTT Communication
		2.5 Inference Implementation
		2.6 Inference Map Generation
		2.7 Upload to Cloud Service
	3 Experiments and Results
		3.1 Performance Evaluation
	4 Conclusion and Future Work
	References
Design and Development of an IoT-Based Smart Medication Device
	1 Introduction
	2 Literature Surveys
	3 Proposed Model
	4 Experimental Setup
	5 System Features and Specifications
	6 Results
	7 Applications
	8 Conclusion
	References
Effects of SARS-COV-2 on Blood
	1 Introduction
		1.1 Why Viruses and Diseases Are Different?
	2 SARS-CoV-2 Description
		2.1 SARS-CoV-2 Symptoms
		2.2 Succeeding Stage
		2.3 Severe Stage
		2.4 SARS-CoV-2 Transmission
		2.5 SARS-CoV-2 Infection on Blood
	3 Methodology
		3.1 Blood
		3.2 Classification of Blood
	4 COVID-19 Effect on Blood Cells
	5 Conclusion
	References
Covid-19: Machine Learning Algorithms to Predict Mortality Rate for Advance Testing and Treatment
	1 Introduction
		1.1 Linear Regression
		1.2 Multivariate Linear Regression
	2 Related Works
	3 Experiment and Dataset
		3.1 Experimental Setup
		3.2 Implementation
	4 Result
	5 Conclusion
	References
Personality Prediction Using EEG Signals and Machine Learning Algorithms
	1 Introduction
	2 Related Works
	3 Methodology
		3.1 Dataset
		3.2 Feature Extraction Technique
		3.3 Classification Algorithms
	4 Experimental Results
	5 Conclusion
	References
A Comparative Study of Various Apriori and FP-Growth Tree-Based Incremental Mining Methods
	1 Introduction
	2 Apriori Approach-Based Incremental Mining Methods
	3 Frequent Pattern (FP)-Growth Tree-Based Incremental Mining
	4 Discussion
	5 Conclusion and Future Scope
	References
Emotion Analysis on Hindi Audio
	1 Introduction
	2 Dataset Description
	3 Feature Extraction
	4 Classifiers
		4.1 Decision Tree Classifier
		4.2 K-Nearest Neighbor
		4.3 Random Forest Classifier
		4.4 Convolutional Neural Network
	5 Implementation
	6 Results
	7 Future Scope
	8 Conclusion
	References
Temporal Analysis of Human Serum Albumin with Recurrent Neural Networks for Changepoint Detection and Prediction
	1 Introduction
		1.1 Molecular Dynamics Simulation
		1.2 LSTM-RNN for Time-Series Data
		1.3 Validation
		1.4 Our Contributions
	2 Methodology
		2.1 Dataset Description
		2.2 RNN for Prediction
		2.3 Changepoint Detection
	3 Experimental Results
		3.1 RNN Prediction Results
		3.2 Changepoint Detection Predictions
	4 Discussion
	References
Modeling of Discrete Jaya Optimized Frequency Controller for Renewable-Based Interconnected Power System
	1 Introduction
	2 System Description
	3 Optimization Algorithm
	4 Results and Discussions
	5 Conclusion
	References
Grey Wolf Optimizer for Data Envelopment Analysis
	1 Introduction
	2 Data Envelopment Analysis (DEA)
		2.1 Basic Mathematical DEA Model
	3 Grey Wolf Optimizer (GWO) Algorithm
		3.1 Mathematical Model for GWO
		3.2 Constraint Handeling
	4 Application of GWO in DEA
		4.1 Experimental Data of IIMs
		4.2 Parameters settings for GWO
		4.3 Results and Discussions
	5 Conclusions
	References
A Model Based on Fuzzy C-Means with Density Peak Clustering for Seismicity Analysis of Earthquake Prone Regions
	1 Introduction
	2 Proposed De-clustering Model for Seismicity Analysis
		2.1 Phase-I: Spatial Domain Analysis with FCM Clustering
		2.2 Phase-II: Time Domain Analysis with Density Peak Clustering
		2.3 Phase-III: Deep Seismicity Analysis by Magnitude Thresholding
	3 Earthquake Catalogs of the Philippines and New Zealand Regions
	4 Results and Discussion
	5 Comparative Analysis with Benchmark De-Clustering Models
	6 Conclusion
	References
Memetic Flower Pollination Algorithm-Based Radiation Pattern in Time-Modulated Linear Antenna Arrays
	1 Introduction
	2 Analysis of Antenna Array
	3 Matlab Simulation Results
	4 Conclusion
	References
Multi-objective Adaptive Antenna Synthesis Using Teaching Learning Based Optimization
	1 Introduction
	2 Modeling of Circular Array
		2.1 Modeling of an Adaptive Antenna Array
	3 Differential Evolution Algorithm
	4 Harmony Search Algorithm
	5 Teaching and Learning-Based Optimzation (TLBO)
		5.1 Teacher Phase
		5.2 Learner Phase
	6 Simulation Results
	7 Conclusion
	References
A Secure Data Transfer in Cloud Environment Using Double-Layer Security for Internet of Medical Things
	1 Introduction
	2 Applications of IoMT
	3 Classification
	4 Literature Survey
	5 Various Methodologies
	6 Proposed System
	7 Results and Discussion
	8 Conclusion and Future Work
	References
Reversible Data Hiding Technique Using Multi-layer Perceptron Based Prediction and Adaptive Histogram Bin Shifting
	1 Introduction
	2 Proposed Multi-layer Perceptron-Based Pixel Prediction
		2.1 Considered Neighborhood Pixels for Prediction
		2.2 Considered Multi-layer Perceptron
		2.3 Pixel Selection Criteria
	3 Embedding
	4 Extraction
	5 Experimental Results
	6 Conclusion
	References
Epileptic Seizure Detection Using LSTM: A Deep Learning Technique
	1 Introduction
	2 Related Works
	3 Methodology
		3.1 Proposed System Architecture
		3.2 Long Short-Term Memory Architecture (LSTM)
		3.3 LSTM Equations
		3.4 Proposed LSTM Model Architecture
	4 Experimental Results
		4.1 Dataset
		4.2 Implementation of LSTM
	5 Results and Analysis
		5.1 Binary Classification
		5.2 Multiclass Classification
	6 Conclusion
	References
A Manta Ray Foraging Algorithm Solution for Practical Reactive Power Optimization Problem
	1 Introduction
	2 Related Works
		2.1 Manta Ray Foraging Algorithm
		2.2 Mathematical Model of Reactive Power Optimal Dispatch
	3 Application of MRFO in Optimal Reactive Power Dispatch
	4 Experimental Results
	5 Conclusion
	References
Indexing on Healthcare Big Data
	1 Introduction
	2 Literature Survey
	3 Proposed Work
		3.1 Indexing
		3.2 Grouping of the Data Based on Keys
		3.3 Input Selection for Mapper
	4 Implementation
		4.1 Grouping the Data
		4.2 Creation of Index
		4.3 Querying the Database
	5 Results and Discussion
		5.1 Experimental Setup
		5.2 Index Building Time
		5.3 Performance Based on Time
		5.4 Performance Based on Speed-up
	6 Conclusion
	References
A Stochastic Approach for Automatic Collection of Precise Training Data for a Soft Machine Learning Algorithm Using Remote Sensing Images
	1 Introduction
	2 Satellite Multispectral Datasets and Study Area
	3 Mathematical Description of Algorithms
		3.1 A SoftML Algorithm Driven by Stochastic, Deterministic, and Hybrid Spectral Similarity Measures
		3.2 Proposed Stochastic Region Growing Algorithm for Precise Training Data Collection
	4 Methodology
	5 Results and Discussion
		5.1 Results
		5.2 Discussion
	6 Conclusion
	References
Optimized Convolutional Neural Network-Based Classification of Arrhythmia Disease Using ECG Signals
	1 Introduction
	2 Proposed Mechanism
	3 Results and Analysis
	4 Conclusion
	References
β-Hill Climbing Grey Wolf Optimizer
	1 Introduction
	2 Related Work
		2.1 β-Hill Climbing
		2.2 Grey Wolf Optimizer
	3 Proposed Hybrid Algorithm
	4 Results
	5 Conclusion
	References
A Power System Economic Load Dispatch Using Jellyfish Search Algorithm
	1 Introduction
	2 Model of the ELD
		2.1 Objective Function
		2.2 Objective Function’s Constraints
	3 Jellyfish Search Algorithm
	4 Jellyfish Search Algorithm for the ELD Problem
	5 Experimental Results
	6 Conclusion
	References
ANN Based Security Analysis of Block Ciphers with Focus on Non-linear Component
	1 Introduction
	2 Preliminaries
		2.1 ANN and Classification Model
		2.2 The PICO Block Cipher
		2.3 AES Block Cipher
	3 Method for Cryptanalysis of Cipher
	4 Experimental Results and Comparative Analysis
	5 Conclusion
	References
Employing LRCN Model for Application Classification in SDN
	1 Introduction
	2 Related Work
	3 Proposed Methodology
		3.1 Dataset Preparation and Pre-processing
		3.2 Configuration of Proposed LRCN Model
		3.3 Compared Techniques
		3.4 Experimentation Details
	4 Experimental Results
		4.1 Model Loss and Accuracy
		4.2 Comparative Results
	5 Conclusions and Future Work
	References
Advanced Rainfall Prediction Model  for India Using Various Regression Algorithms
	1 Introduction
	2 Literature Review
	3 Datasets Used
	4 Proposed Model
		4.1 Stage I: Attribute-Based Prediction
		4.2 Stage II: Input-Based Prediction
		4.3 Stage III: Finding Optimal Parameters for Final Prediction
	5 Result Analysis
		5.1 Stage I: Attribute-Based Prediction
		5.2 Stage II: Input-Based Prediction
		5.3 Stage III: Finding Optimal Parameters for Final Prediction
		5.4 Predicted Model Briefing
	6 Comparitive Analysis
		6.1 Comparison with Model Proposed by Srivastava et al. ch30srivastava2020monthly
		6.2 Comparison with Model Proposed by Tharun et al. ch30tharun2018prediction
		6.3 Comparison with Model Proposed by Bang et al. ch30bang2019fuzzy
	7 Conclusion
	References
An Optimal Dispatch of Microgrid Based on Improved Particle Swarm Algorithm
	1 Introduction
	2 A Mathematical Model for Optimal Dispatching of Microgrid
		2.1 The Objective Function
		2.2 Constraints
	3 Particle Swarm Optimization Algorithm
		3.1 Basic Particle Swarm Optimization
		3.2 Improved Particle Swarm Algorithm
		3.3 Improved Particle Swarm Algorithm Steps
	4 Example Analysis
	5 Conclusion
	References
ACO-Based Optimal Route Scheduling for EV Fleet Operation
	1 Introduction
	2 ACO for Optimal Scheduling
	3 ACO for Optimal Route Scheduling—System Description
	4 Algorithm Execution and Result Validation
	5 Conclusion
	References
An Analysis of Machine Learning Algorithm for the Classification of Emotion Recognition
	1 Introduction
	2 Related Work
		2.1 Fast Fourier Transform
		2.2 Multilayer Perceptron (MLP)
		2.3 K-Nearest Neighbor (KNN) classifier
		2.4 Support Vector Machine (SVM)
		2.5 Genetic Programming (GP)
	3 Methodology
		3.1 Experimental Setup
	4 Experimental Results
	5 Conclusion
	References
Adaptive Neuro-Fuzzy Inference System-Based Information Fusion Model for Smart Monitoring of Public Amenities
	1 Introduction
	2 Literature Survey
	3 Proposed Smart Application
	4 Information Fusion Model for Proposed Application
	5 Experimental Setup
	6 Conclusion
	References
Deep Neural Networks to Predict Sub-surface Ocean Temperatures from Satellite-Derived Surface Ocean Parameters
	1 Introduction
	2 Deep Learning Methodology
	3 Data for Calibration of DLSOT Model
	4 Performance Evaluation of DLSOT Model
	5 Conclusions
	6 Future Works
	References
Density Estimation of Heterogeneous Crowd in Mass Religious Gatherings Using Image Processing and Denoising Filter
	1 Introduction
	2 Related Works
	3 Methodology
		3.1 Image Processing Module
		3.2 Denoising Filters
	4 Case Study
		4.1 Dataset Preparation
		4.2 Model Training
		4.3 Prediction
		4.4 Estimation of Densities for Study Location
	5 Corroboration of Results
	6 Summary and Conclusions
	References
Workload Prediction for Cloud Resource Provisioning using Time Series Data
	1 Introduction
	2 Motivation
	3 Background Approaches for Workload Prediction
		3.1 Simple Moving Average(SMA)
		3.2 Autoregressive Moving Average (ARMA)
	4 Related Work
	5 Implementation of ARIMA Model
	6 Experimental Setup and Result Analysis
		6.1 Dataset
		6.2 Approach
		6.3 Result Analysis
	7 Conclusion and Future Scope
	References
A Trust-Based Framework to Reduce Message Dissemination Latency Using CFC Model for Internet of Vehicle
	1 Introduction
		1.1 VANET Architecture
		1.2 Types of VANET
		1.3 Internet of Things (IoT)
		1.4 Internet of Vehicles (IOV)
		1.5 Trust Idea and Definition
	2 Literature Review
		2.1 Problem Statement
		2.2 Research Gap
	3 Motivation
	4 Objective of the Study
	5 Methodology
		5.1 Trust Calculation
		5.2 Message Spread
	6 Scope of the Study
	7 Expected Outcome
		7.1 Comparison Analyses from Existing Approaches
	8 Conclusion
	References
Generative Adversarial Network for Cloud Removal from Optical Temporal Satellite Imagery
	1 Introduction
	2 Generative Adversarial Networks
	3 Materials and Methods
		3.1 Study Area and Data Details
		3.2 Methodology Adopted
	4 Results and Discussion
	5 Conclusion
	References
Streamed Covid-19 Data Analysis Using LSTM—A Deep Learning Technique
	1 Introduction
	2 Architecture of LSTM
	3 Literature Review
	4 Proposed Methodology
	5 Implementation
		5.1 Dataset
	6 Results and Analysis
		6.1 Confirmation of 20,000 Cured Cases in India
		6.2 When Was the Earliest Case in India
		6.3 Per Person Number of People Are Infected
		6.4 The Incubation Period of the Virus
		6.5 The Rank of States as Per the Number of Confirmed Cases
		6.6 The Gender-Wise and Age Group Distribution and Impact of COVID-19 in India
		6.7 Total Confirmed Cases, Cured Cases, and Death Cases for 20 States in India
	7 Conclusion
	References
Canonical Correlation Analysis with Bhattacharya Similarity Distance for Multiview Data Representation
	1 Introduction
	2 Related Work
		2.1 Canonical Correlation Analysis (CCA)
		2.2 Locality Preserving CCA (LP-CCA)
		2.3 A New Locality Preserving CCA (ALPCCA)
		2.4 Bhattacharya Distance
	3 Proposed Method
	4 Experiments and Results
		4.1 Performance Evaluation
	5 Conclusion
	References
An Optimization Nodes Layout in Deployment WSN Based on Improved Artificial Bee Colony
	1 Introduction
	2 Related Works
		2.1 Artificial Bee Colony Algorithm
		2.2 WSN Coverage Optimization Model
	3 Improved Artificial Bee Colony Algorithm for Nodes Coverage Deployment
		3.1 Improving Artificial Bee Colony
		3.2 Energy Saving Coverage Optimization
	4 Simulation Results
	5 Conclusion
	References
A Home Energy Management System with Peak Demand Reduction Using Ant Colony Optimization and Time of Use Pricing Scheme
	1 Introduction
	2 Problem Formulation
		2.1 Constraints
	3 Optimization Technique for Reducing Energy Consumption Cost
		3.1 Ant Colony Optimization (ACO)
	4 Simulation and Results
		4.1 Load Demand Comparison
		4.2 Cost–Benefit Analysis
		4.3 Task Completion Analysis
		4.4 Comparison of Energy Consumption Cost and % of Task Completion for Various Emax Value
	5 Conclusions
	References
An Apache Giraph Implementation of Distributed ADMM for Solving LASSO Problems
	1 Introduction and Motivation
	2 Implementation of Distributed ADMM on Apache Giraph
		2.1 Optimization Problem and ADMM
		2.2 LASSO Problem and Distributed ADMM
		2.3 Algorithm Description
	3 Numerical Experiments
	4 Conclusions and Future Work
	References
Integrated Optimization Model for Sustainable Supplier Selection and Order Allocation in Food Supply Chain
	1 Introduction
	2 Literature Review
	3 Case Problem
	4 Development of Three-Phase Integrated Mathematical Model
		4.1 Phase I-Sustainable Supplier Evaluation Process
		4.2 Phase II-Bi-objective Fuzzy Optimization Model Formulation
		4.3 Phase III-Fuzzy Programming Solution Approach
	5 Application of the Integrated Model
		5.1 Phase I-Sustainable Supplier Evaluation Process
		5.2 Phase II-Bi-objective Optimization Model Formulation
		5.3 Phase III-Fuzzy Programming Solution Approach
	6 Conclusion
	References
Performance-Based Supplier Selection and Order Allocation Model Incorporating Sustainable Development Strategies
	1 Introduction
	2 Literature Review
	3 Proposed Integrated Mathematical Model
	4 Mathematical Background of the Study
		4.1 Analytical Hierarchy Process (AHP)
	5 Case Description and Model Formulation
	6 Case Illustration
	7 Conclusion
	References
A Multi Objective Reverse Logistics Network Design Model Under Carbon Pricing: An Emerging Economy Perspective
	1 Introduction
	2 Literature Review
	3 Case Description and Fuzzy Mathematical Model Formulation
	4 Numerical Illustration
	5 Result and Discussion
	6 Conclusion
	References
Centralised Resource Allocation Model for Improving the Environmental Sustainability of Retailers with Imprecise Data Envelopment Analysis
	1 Introduction
	2 Literature Review, Research Gaps and Contributions
	3 Model Formulations
		3.1 Problem Definition
		3.2 Mathematical Model
	4 Model Validation
	5 Conclusion, Limitation and Future Scope
	References
Evaluation of Adoption of Blockchain Technology for Supply Chain Management: A Case of Indian MSME
	1 Introduction
	2 Problem Description
		2.1 Theoretical Basis
		2.2 Determinants for Evaluation of Adoption of BCT in SC in Indian MSME
	3 Research Methodology
		3.1 Fuzzy Analytic Hierarchy Process (F-AHP)
	4 Results and Discussion
	5 Conclusion
	References
Analysis of Critical Success Factors for Adopting Omni-Channel Retailing in India
	1 Introduction
	2 Problem Description
	3 Research Methodology
		3.1 F-TISM for Developing Structural Relationship
		3.2 Fuzzy-MICMAC for Classification
	4 Results and Discussion
	5 Conclusion
	References
Fuzzy MCDM Model for Analysis of Critical Success Factors for Sustainable Collaboration with Third Party Reverse Logistics Providers
	1 Introduction
	2 Literature Review
	3 Structural Model Analysis Based on Fuzzy Numbers
		3.1 Development of Interpretive Structural Model
		3.2 Fuzzy MICMAC Analysis
	4 Result Analysis and Implications
	5 Conclusion
	References
An integrated Fuzzy MCDM Approach for Evaluation of Barriers in Implementing LARS Paradigms in Supply Chain
	1 Introduction
	2 Problem Description
	3 Research Methodology
		3.1 Fuzzy-Delphi
		3.2 Fuzzy-DEMATEL
	4 Results and Discussions
	5 Conclusion
	References
Quality Improvement Using Fuzzy MCDM for Flexographic Printing Industry
	1 Introduction
	2 Research Methodology
		2.1 F-SAW
		2.2 F-ARAS
	3 Results and Discussions
	4 Conclusion
	References
Using Attractive–Repulsive Binary Local Gradient Contours for Sample-Consensus Background Modeling
	1 Introduction
	2 Literature Review
	3 Proposed Methodology
		3.1 Pixel Representation
		3.2 Background Model
		3.3 Pixel Classification
		3.4 Background Model Update
	4 Experimental Results
		4.1 Results
	5 Conclusion
	References
Lexical, Pragmatic and Linguistic Feature Based Two-Level Sarcasm Detection Using Machine Learning Techniques
	1 Introduction
	2 Relation Work
	3 Methodology
		3.1 Preprocessing
		3.2 Feature Extraction
		3.3 Classification of Sarcasm
		3.4 Classification Models
	4 Experimental Results and Analysis
		4.1 Dataset Description
		4.2 Experimental Setup
		4.3 Analysis of Results
	5 Conclusion
	References
Real-Time Statistics and Visualization of the Impact of COVID-19 in India with Future Prediction Using Deep Learning
	1 Introduction
	2 Aim of This Research Work
	3 Proposed Modules
	4 Implemented Results and Analysis
		4.1 Decomposition of the COVID-19 Data
		4.2 Hybrid CNN-LSTM Model
		4.3 Results
	5 Conclusion and Future Direction
	References
A Brief Survey on Concept Drifted Data Stream Regression
	1 Introduction
	2 Concept Drift
		2.1 Type of Concept Drift
	3 Related Work
	4 Evaluation Strategies
		4.1 Synthetic, Stationary, and Real-World Data Streams
	5 Discussion and Conclusions
	References
Differential Evolution Algorithm for Multimodal Optimization: A Short Survey
	1 Introduction
		1.1 Differential Evolution
		1.2 Niching Techniques
	2 Conventional Niching Method-Based DE for MMOP
	3 Speciation-Based Niching DE for MMOP
	4 Neighborhood-Based Niching DE for MMOP
	5 Adaptive Strategy-Based Niching DE for MMOP
	6 Hybridized DE for MMOP
	7 Multiobjective DE-Based Approach for MMOP
	8 Conclusion
	References
Implementation of Brain Tumor Segmentation Using CNN Deep Learning Algorithm
	1 Introduction
	2 Dataset
	3 Methodology
		3.1 Image Preprocessing
		3.2 Brain Tumor Segmentation
		3.3 Build CNN Model
	4 Implementation and Experimental Results
		4.1 Libraries Used
		4.2 Results
	5 Conclusion
	References
Improved Self-adaptive Differential Evolution Based Throughput Maximization of Energy Harvesting Cognitive Radio Network
	1 Introduction
	2 Formulation of the Proposed Algorithm
	3 Performance Evaluation
	4 Throughput Maximization Problem
	5 Conclusion
	References
Author Index