Smart Evaluation of Green Campus Sustainability Considering Energy Utilization

Abstract

With the change in energy utilization, a fast and accurate evaluation method is of great importance to promote green campus sustainability. In order to improve the feasibility and timeliness of evaluation, an intelligent evaluation model based on dynamic Bayesian inference and adaptive network fuzzy inference system (DBN-ANFIS) is proposed. Firstly, from the perspective of sustainability and considering the changes in energy utilization, a green campus evaluation index system is constructed from four levels: campus resource utilization, campus environment creation, campus usage management, and campus eco-efficiency. On this basis, the parameters of the adaptive network fuzzy inference system (ANFIS) are optimized based on dynamic Bayesian inference (DBN), so as to apply the modified model to the green campus evaluation work of the Spark big data operation platform. Finally, the scientificity of the model proposed in this paper is verified through example analysis, which is conducive to the real-time and effective evaluation of green campus sustainability and provides scientific and rational decision support to improve its management.

Preliminary Approach for the Development of Sustainable University Campuses: A Case Study Based on the Mitigation of Greenhouse Gas Emissions

“…The analysis should encompass the identification of trends and patterns in the results, including the community's preferences and priorities with respect to sustainability and energy efficiency [71,72]. It is imperative to determine whether the implemented measures are consistent with the community's expectations and requirements, and to identify areas where further work is necessary to satisfy the community's needs [73,74]. The assessment of user willingness through a survey is an effective methodology for ensuring the sustainability of university campuses and actively involving the university community in energy saving and efficiency initiatives [75,76].…”

Evaluating the Benefits and Potential of “Plastic Reduction”: A Case Study of College Students in Western China

“…It can be observed that the per capita plastic usage and waste of students at Xi'an Shiyou University are at a low level. In recent years, both domestic and international universities have actively i mented measures to establish universities as pivotal platforms for reducing plastic sumption in society [36][37][38][39]. The primary objective of Chinese colleges and universi to impart knowledge on ecological civilization to students, guiding them towards a In recent years, both domestic and international universities have actively implemented measures to establish universities as pivotal platforms for reducing plastic consumption in society [36][37][38][39].…”

“…In recent years, both domestic and international universities have actively i mented measures to establish universities as pivotal platforms for reducing plastic sumption in society [36][37][38][39]. The primary objective of Chinese colleges and universi to impart knowledge on ecological civilization to students, guiding them towards a In recent years, both domestic and international universities have actively implemented measures to establish universities as pivotal platforms for reducing plastic consumption in society [36][37][38][39]. The primary objective of Chinese colleges and universities is to impart knowledge on ecological civilization to students, guiding them towards adopting ecological consumption practices and implementing waste classification measures to minimize plastic usage.…”

A Novel Individual Carbon Emission Evaluation and Carbon Trading Model for Low-Carbon University Campuses

“…Several studies have recommended evaluation standards for low-carbon campuses based on the perspective of campus construction and have implemented various models to construct evaluation systems based on different dimensions. For instance, Zhao et al [36] proposed a green campus evaluation indicator system founded on dynamic Bayesian inference and adaptive network fuzzy inference system (DBN-ANFIS). Na et al [37] formulated an expert questionnaire, compared the Analytic Hierarchy Process (AHP) with the Entropy Weight Method (EWM), and assigned different weights to four aspects: management mechanism, low-carbon culture, renewable energy utilization, and emission reduction measures.…”