Analysis of Factors Affecting the Honeybee Colony Size from the Model-based Perspective
DOI:
https://doi.org/10.54097/hset.v35i.7053Keywords:
Honeybee; Gray Forecast Model; Analytic Hierarchy Process; Markov Chain Monte Carlo.Abstract
Bees and other important animals are vital to human survival on the earth. They not only produce delicious honey, but also play an indispensable role in plant pollination, making a unique contribution to the world. The bee population reduction crisis is known as a global problem of sustainable development goals. To consider the factors that can influence the size of honey bee populations and how these factors can affect the size of honey bee populations, we will use the most basic evaluation model. Given the need to accurately calculate the weight of each factor, we use the Analytic Hierarchy Process (AHP) model. In order to analyze the results of the AHP model, we will list our variable factors, apply the AHP model and use sensitivity analysis on it. Also, to predict how many honeybees hives you will need to support pollination of an 81,000 square meters parcel of land containing crops that benefit from pollination. we consider to use Markov Chain Monte Carlo (MCMC) model, which can indicate a stationary distribution to the attendance rate of the bees after n times.
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