Feasibility Model of Solar Energy Plants by ANN and MCDM Techniques

This Brief highlights a novel model to find out the feasibility of any location to produce solar energy. The model utilizes the latest multi-criteria decision making techniques and artificial neural networks to predict the suitability of a location to maximize allocation of available energy for prod...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Majumder, Mrinmoy (Autor), Saha, Apu K. (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Singapore : Springer Nature Singapore : Imprint: Springer, 2016.
Edición:1st ed. 2016.
Colección:SpringerBriefs in Energy,
Temas:
Renewable energy sources.
Computational intelligence.
Electric power production.
Environmental economics.
Climatology.
Renewable Energy.
Computational Intelligence.
Electrical Power Engineering.
Mechanical Power Engineering.
Environmental Economics.
Climate Sciences.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • Introduction
  • Justification
  • Solar Energy
  • Solar Energy
  • Importance
  • Benefits of Solar energy
  • MCDM
  • Definitions
  • Applications
  • Artificial Neural Network
  • Definition
  • Development Procedure of Models
  • Development of the Feasibility Model
  • Application of MCDM
  • Development of Feasibility Index
  • Model Validation of the Model
  • Sensitivity Analysis
  • Case Studies
  • Locations
  • Why this location ?
  • Results and Discussion
  • MCDM Results
  • ANN Results
  • Conclusion.

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