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Seven Metaheuristics to Learn for your Next Data Science Project is a video book that will help you learn the seven most contemporary nature-based or metaheuristic algorithms simply and lucidly. It also includes 50 project ideas and 50 numericals for your practice. The content of the book is as follows: 1. INTRODUCTION1.1. Types of Metaheuristics1.2. Applications in Data Science1.3. Advantages and Limitations1.4. Comparison with other optimization techniques2. OVERVIEW OF METAHEURISTICS2.1. Application of Metaheuristics2.2. Application of Metaheuristics in Applied Fields2.3. Classification of Metaheuristic Algorithms2.4. Working Principle2,5. Limitations of Metaheuristic Algorithms2.5. Future Scopes of Metaheuristics3. METHOD I: ARTIFICIAL NEURAL NETWORK OR ANN4. METHOD II: POLYNOMIAL NEURAL NETWORK OR PNN5. METHOD III: GLOW WORM ALGORITHM OR GWA6. METHOD IV: MINE BLAST ALGORITHM OR MBA7. METHOD V: WATER CYCLE ALGORITHM OR WCA8. METHOD VI: DOLPHIN ECHOLOCATION ALGORITHM OR DEA9. METHOD VII: GENETIC ALGORITHM OR GA10. CONCLUSION10.1. Project Ideas10.2. Numerical ProblemsThe Project ideas and numerical problems are often updated.
The vulnerability of turbines is analyzed with the help of Artificial Neural Networks, followed by Multi Criteria Decision Making methods for development of intelligent indices to represent the level of vulnerability of turbines due to the change in climate.
This Brief highlights a novel model to find out the feasibility of any location to produce solar energy.
The uncontrolled utilization of natural resources to supply to the water demands of the ever-growing population has brought about worldwide scarcity. Unregulated discharge of waste water into fresh water resources is also polluting the available water resources and making them non-utilizable.
This Brief presents the impact of climatic abnormalities on hydropower potential of different regions of the World. The results from the study show that the hydro-energy potential of the Asian region is mostly vulnerable with respect to other regions of the World.
The present study has attempted to apply the advantage of neuro-genetic algorithms for optimal decision making in maximum utilization of natural resources. That is why the present study tries to utilize nature based algorithms to solve the problems of location selection for hydropower plants.
The increase in GHG gases in the atmosphere due to expansions in industrial and vehicular concentration is attributed to warming of the climate world wide. This Brief introduces a Vulnerability Index which will be directly proportional to the climatic impacts of the watersheds.
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