Dynamic detection of geological environment carrying capacity of urban gardens based on whale optimization algorithm

Abstract

With the rapid expansion of urban areas in recent decades, the over-development and urban sprawl has severely disturbed natural landscapes, causing many adverse impacts on ecological environment. This study estimates the carrying capacity of urban garden environments based on dynamic detection for whale optimization (WDWO), which can accommodate various size of gardens. The WDWO is a novel algorithm that provides an efficient queueing mechanism for solving problems with updates to tasks that change dynamically; moreover, it achieves better results by computing multiple solutions without even knowing the nature of these changes. The dynamic detection method used herein is relatively simple and effective because it can search feasible parameters automatically and precisely predict its calculation range.To this purpose, three different characteristics are considered: (1) a model with an endogenous discount factor. (2) A model with a debt-elastic interest-rate premium. (3) A model with portfolio adjustment costs. The main finding of the paper is that all models deliver virtually identical dynamics at business-cycle frequencies, as measured impulse response functions. The noticeable difference among the alternative models is that the debt-elastic interest-rate premium model and portfolio adjustment costs model have dynamics changes.