Preface
Acknowledgments
Contents
Part I: New Nature Based Algorithms
Chapter 1: Selection of Optimized Location for Ecoparks Using Ant Colony Optimization
1.1 Introduction
1.1.1 Ecoparks and Ecotourism
1.1.2 Objective and Methodology Overview
1.1.3 Ant Colony Food-Search Logic and Algorithms
1.1.3.1 Applications
1.2 Methodology
1.3 Conclusion
References
Chapter 2: Application of Hive Theory to the Identification of Suitable Porcupine Habitats
2.1 Introduction
2.1.1 Importance of Porcupine Species to the Ecosystem
2.1.2 Habitat of Porcupines
2.1.3 Food Habits of Porcupines
2.1.4 Porcupine Predators
2.1.5 Objective
2.1.6 Brief Methodology
2.2 Artificial Bee Colony Algorithm
2.3 Methodology
2.4 Results and Discussion
2.5 Conclusion
References
Chapter 3: Tradeoff Analysis Between Rainfall and Load Factor of a Small-Scale Hydropower Plant by Particle Swarm Optimization
3.1 Introduction
3.1.1 Classification of Hydropower Plants
3.1.1.1 Low-Head Hydroelectric Power Plants
3.1.1.2 Medium-Head Hydroelectric Power Plants
3.1.1.3 High-Head Hydroelectric Power Plants
3.1.2 Impact of Climate Change on Hydropower Plants
3.1.3 Objective and Scope
3.1.4 Brief Methodology
3.2 Particle Swarm Optimization
3.3 Necessity of Hydropower Plans
3.3.1 Global Scenario of Renewable Energy
3.3.2 Classification of Hydropower Plants
3.3.2.1 Classification with Respect to Quantity of Water
Runoff River Plants Without Pondage
Runoff River Plants with Pondage
Reservoir Plants
3.3.2.2 Classification by Availability of Water Head
3.3.2.3 Classification with Respect to Nature of Load
3.4 Methodology
3.5 Results and Discussion
3.6 Conclusion
References
Chapter 4: Application of Artificial Neural Networks in Short-Term Rainfall Forecasting
4.1 Introduction
4.1.1 Earlier Studies on the Prediction of Short-Term Rainfall
4.1.2 Neural Network for Short-Term Rainfall Prediction
4.1.3 Neurogenetic Algorithms
4.1.4 Objective
4.1.5 Brief Methodology
4.2 Methodology
4.2.1 Data Preprocessing
4.2.2 Model Training, Testing, and Validation
4.3 Results and Discussion
4.4 Conclusion
References
Chapter 5: Application of a Genetic Algorithm to Predict the Growth Rate of Bufo melanostictus in Urban Forest
5.1 Introduction
5.1.1 Bufo sp.
5.1.2 Life Cycle of Asian Common Toad
5.1.3 Factors Affecting Growth Rate of Asian Common Toad
5.1.4 Objective of Study
5.1.5 Brief Methodology
5.2 Neural Network and Genetic Algorithm
5.2.1 Genetic Algorithm
5.2.2 Recent Application of Genetic Algorithm to Practical Problem Solving
5.3 Methodology
5.4 Results and Discussion
5.5 Conclusion
References
Part II: Site Selection Algorithms
Chapter 6: Comparison of Nature-Based Algorithms in Impact Analysis of Climate Change on Water Resources
6.1 Introduction
6.1.1 Climate Change and Water Availability
6.1.2 Nature-Based Algorithms
6.2 Methodology
6.2.1 Preparation of Data Set
6.2.2 Development of Nature-Based Algorithms
6.2.3 Performance Metrics
6.3 Results and Discussion
6.4 Conclusion
References
Chapter 7: A Neuro-Fuzzy Approach to Selecting Crops in Vertical Irrigation
7.1 Introduction
7.1.1 Brief Methodology
7.1.2 Fuzzy Logic
7.1.3 Neurogenetic Models
7.1.4 Genetic Algorithm
7.2 Methodology
7.3 Results and Discussion
7.4 Conclusion
References
Chapter 8: Application of Neuro-Fuzzy Techniques in the Estimation of Extreme Events
8.1 Introduction
8.1.1 Prediction of Extreme Events
8.1.2 Objective and Scope
8.1.3 Brief Methodology
8.2 Artificial Neural Networks and Fuzzy Logic
8.2.1 Artificial Neural Network
8.2.2 Fuzzy Logic
8.2.2.1 Application of Fuzzy Logic
8.3 Methodology
8.3.1 Data Set Preparation
8.3.2 Development of Scoring Mechanism by Fuzzy Logic
8.4 Results and Discussion
8.5 Conclusion
References
Chapter 9: Impact of Climate Change on Selection of Sites for Lotus Cultivation
9.1 Introduction
9.1.1 Objective and Scope
9.1.2 Brief Methodology
9.1.3 Neurogenetic Models
9.1.4 Genetic Algorithm
9.2 Methodology
9.3 Results and Discussion
9.4 Conclusion
References
Chapter 10: Comparison of Bat and Fuzzy Clusterization for Identification of Suitable Locations for a Small-Scale Hydropower Plant
10.1 Introduction
10.1.1 Indian Scenario of Energy Distribution
10.1.2 Types of Hydropower Plants
10.1.2.1 Classification by Quantity of Water
Runoff River Plants Without Pondage
Runoff River Plants with Pondage
Reservoir Plants
10.1.2.2 Classification by Availability of Water Head
10.1.2.3 Classification by Nature of Load
Base Load Plants
Peak Load Plants
10.1.3 Importance of Location on Use Factor of Hydropower Plants
10.1.4 Cluster Analysis Algorithms
10.1.4.1 Hierarchical Clustering
10.1.4.2 K-Means Clustering
10.1.4.3 Principal Component Analysis
10.1.5 Objective and Scope
10.1.6 Proposed Methodology
10.1.7 Bat Clusterization
10.2 Methodology
10.2.1 Selection of Factors
10.2.1.1 Hydrologic and Geophysical Factors
Average Change in Flow
Average Change in Net Head
Soil Strength
Slope
10.2.1.2 Environmental Factors
Land Use and Land Cover or Loss Coefficient ( L c)
Frequency of Fish Navigation
Water Quality
10.2.1.3 Socioeconomic Factors
Average Energy Potential
Potential Profit
Distance from Grid
Distance from Consumers
10.2.2 Development of Clusterization Algorithm
10.2.2.1 Application of Fuzzy Clusterization
10.2.2.2 Application of Bat Algorithm
Definition of Good and Bad Location for Availability of Food
Assignment of Randomly Flying Bats to Locations
Food Spotting
10.3 Results and Discussion
10.4 Conclusion
References
Part III: Impact Studies
Chapter 11: Impact of Climate Change on Ecological Sensitivity of Wetlands
11.1 Introduction
11.1.1 Ecology and Ecosystem
11.1.2 Wetland Ecosystem
11.1.3 Climatic Impacts on Ecosystems
11.1.4 Objective and Scope
11.2 Study Area
11.2.1 Wetlands of Tripura
11.2.2 Reasons for Wetland Degradation
11.2.3 Important Wetlands of Tripura (Fig.ย 11.1)
11.2.3.1 Gumti Reservoir
11.2.3.2 Rudrasagar Lake
11.2.3.3 Sipahijala Reservoirs
11.2.3.4 Trishna Reservoirs
11.3 Methodology
11.3.1 Data Collection
11.3.2 Image Processing
11.3.3 Classification Rule
11.3.4 Prediction of Climatic Impact on Ecological Sensitivity
11.4 Results and Discussion
11.5 Conclusion
References
Chapter 12: Impact of Climate Change on the Hydrologic Sensitivity of Sundarban Reserve Forest
12.1 Introduction
12.1.1 Importance of the Sundarban Biosphere Reserve
12.1.2 Flora and Fauna
12.1.2.1 Flora
12.1.2.2 Fauna
12.1.3 Hydroclimatic Conditions of Sundarbans
12.1.4 Objective and Scope
12.1.5 Brief Methodology
12.2 Artificial Neural Network
12.2.1 Applications
12.3 Methodology
12.3.1 Selection of Network Topology
12.3.2 Selection of Training Algorithms
12.3.3 Selection of Activation Function
12.3.4 Fitness Functions
12.4 Result and Discussion
12.4.1 IPCC Climate Uncertainty Scenarios
12.5 Conclusion
References
Chapter 13: Fuzzy -Based Impact Analysis Study on Site Selection of Tidal Power Plants
13.1 Introduction
13.1.1 Selection of Sites for Tidal Power
13.1.2 Study Objective and Scope
13.1.3 Brief Methodology
13.1.4 Study Area: Sundarbans
13.2 Methodology
13.2.1 Determination of Stream Resources
13.2.2 Determination of Turbulence
13.2.3 Low-Cost Interconnection Point
13.2.4 Determination of Net Profit
13.2.5 COBALT Formulation
13.3 Results and Discussion
13.4 Conclusion
References
Part IV: New Computer Models
Chapter 14: Estimation of Groundwater Quality from Surface Water Quality Variables of a Tropical River Basin by Neurogenetic Models
14.1 Introduction
14.1.1 Objective and Scope
14.1.2 Study Area
14.1.3 Brief Methodology
14.1.4 Data Description
14.2 Methodology
14.2.1 Mathematical Modeling of Neural Networks
14.2.1.1 Selection of Network Topology
14.2.1.2 Training Algorithms
Quick Propagation
Conjugate Gradient Descent
Levenberg Merquadart
14.2.2 Performance Metrics
14.2.2.1 Root Mean Square Error
14.2.2.2 Correlation Coefficient
14.2.2.3 Covariance
14.3 Results and Discussion
14.4 Conclusion
References
Chapter 15: Rating Irrigation Canals Using Cognitive Indexes
15.1 Introduction
15.2 Artificial Neural Network
15.3 Decision Tree Algorithm (DTA)
15.4 Methodology
15.5 Results and Discussion
15.6 Conclusion
References
Chapter 16: CLIMAGE: A New Software for the Prediction of Short-Term Weather with the Help of Satellite Data and Neuro-Fuzzy Clustering
16.1 Introduction
16.1.1 Importance of Short-Term Weather Forecasting
16.1.2 Satellite Imagery
16.1.2.1 Importance of Satellite Imagery
16.1.3 Clustering
16.1.3.1 Importance of Clustering
16.1.4 Neuro-Fuzzy Clustering
16.2 Description of the Software: CLIMAGE
16.3 Benefits of CLIMAGE
16.4 Case Study
16.5 Conclusion
References
Chapter 17: OPTIDAL: A New Software for Simulation of Climatic Impacts on Tidal Power
17.1 Introduction
17.1.1 Importance of Tidal Energy
17.1.2 Need for Optimization of Tidal Power Production
17.1.3 Software Objective and Scope
17.2 Input, Output, and Working Principle of Software
17.3 Benefits of OPTIDAL Software
17.4 Drawbacks
17.5 Conclusion
References
Chapter 18: AGROSIM: A New Model for Predicting Water Productivity from Crop Characteristics
18.1 Introduction
18.1.1 Justification of the Software Development
18.2 Input, Output, and Working Principle of the Software
18.3 Benefits of the Software
18.4 Drawbacks of the Software
18.5 Conclusion
References
Chapter 19: QUALTR: Software for Simulating Output from Water Treatment Plants in the Face of Extreme Events
19.1 Introduction
19.1.1 Hazard Analysis of Water Treatment Plants
19.1.2 Components of Water Treatment Plants
19.1.3 Impact of Extreme Climate on Water Treatment Plants
19.1.4 Objective and Scope of the Present Software
19.1.5 Brief Methodology
19.2 Development of Neurogenetic Models
19.2.1 Development of the QTRWTP
19.3 Benefits of the Software
19.4 Drawback of the Software
19.5 Conclusion
Chapter 20: Development of a Neuro-Fuzzy System for Selection of Tree Species for Afforestation Purpose
20.1 Introduction
20.1.1 Desertification
20.1.2 Importance of Afforestation Projects
20.1.3 Drawbacks of Afforestation Projects
20.1.4 Suitable Species for Afforestation
20.1.5 Objective of Present Study
20.1.6 Brief Overview of Study Methodology
20.2 Neuro-Fuzzy Technique
20.2.1 Applications of Neuro-Fuzzy Techniques in Related Fields
20.3 Methodology
20.4 Results and Discussion
20.5 Conclusion
References
About the Authors
Principal Authors:
Coauthors:
Index