Analysis of Environmental Governance Expense Prediction Reform With the Background of Artificial Intelligence

Analysis of Environmental Governance Expense Prediction Reform With the Background of Artificial Intelligence

Xiaohui Wu
Copyright: © 2022 |Pages: 19
DOI: 10.4018/JOEUC.287874
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Abstract

In this paper, Artificial Intelligence assisted rule-based confidence metric (AI-CRBM) framework has been introduced for analyzing environmental governance expense prediction reform. A metric method is to assess a level of collective environmental governance representing general, government, and corporate aspects. The equilibrium approach is used to calculate improvements in the source of environmental management based on cost, and it is tailored to test the public sector-corporation for environmental shared governance. The overall concept of cost prediction or estimation of environmental governance is achieved by the rule-based confidence method. The framework compares the expected cost to the environment of governance to determine the efficiency of the cost prediction process.
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2. Background Study On Data Dissemination In Wireless Sensor Network

This section discusses several works that have been carried out by the various researchers; (Das et al., 2017) developed Diverse ecologies: Mapping complexity (DE-MC) in environmental governance. The proposed method explores a new paradigm for the study of dynamic connections between the various environment and economical as well as cost development governance.

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