Development of ecological management system for planted forest based on ELM deep learning algorithm

Abstract

Plantations play a central and lever role in maintaining the ecological balance of the earth, maintaining the overall function of the terrestrial ecosystem, and promoting the coordinated development of economic society and ecological construction. In order to strengthen the ecological management of plantation forests and improve the ecological level of forest region, the C/S framework is taken as the basic structure, and the programming mode of business model-user interface controller is used, on J2EE platform. The ecological management system of a planted forest is constructed by the evaluation module, the principal component comprehensive analysis module of ecological function value and the demand prediction module of planted forest based on extreme learning machine and deep learning algorithm, and runs under the support of windows system, oracle 15G and above database software. The indexes and factors affecting the ecological function of plantation forests were evaluated and analyzed, and the final management decision was given by the prediction module. The results showed that the plant density significantly affected plant biomass, organic carbon storage, water content and nutrient accumulation, and the comprehensive evaluation indexes of four ecological functions increased from 32.69, 31.84, 33.71 and 35.46 to 86.18, 89.46, 89.83 and 88.76, respectively. Although the degree of influence of the system on lemon strip plants, herbaceous plants, surface litter and soil varies, it still has good feasibility, effectiveness and practicality, and can assist the scientific ecological management of artificial plantation forests.