Beschreibung
This book is intended primarily for students, lecturers, researchers, analysts, statistical estimators, machine learning and other soft computing evaluators, institutions, government and non-governmental agencies, corporate bodies, and the public in the field of photosynthetically active radiation (PAR), renewable energy, ecology, solar and atmospheric physics, atmospheric and meteorological physics, plant science, agricultural meteorology and horticultural studies etc., to quantify, analyze, evaluate and model many challenges in a simple and logical way to present a few solutions application of, well-understandable and high-tech principles, knowledge and knowledge of PAR modeling. The purpose is to take readers' understanding into consideration of analytical procedure, techniques, applications and optimization techniques based on empirical algorithm, machine learning and evolutionary techniques applied in statistical machine learning modeling; and the confidence and skills necessary to effectively analyze, interpret, quantify and model PAR data.
Autorenporträt
The author received a BSc. in Physics from the University of Uyo. He also studied Renewable Energy/ Meteorological and Atmospheric Physics at University of Calabar. He conducted research in energy management and conversion, photosynthetically active radiation, reference evapotranspiration, renewable energy, sustainability, and solar energy.
Herstellerkennzeichnung:
OmniScriptum SRL
Str. Armeneasca 28/1, office 1
2012 Chisinau
MD
E-Mail: info@omniscriptum.com
