Kolmogorov-Arnold Representation Based Informed Orchestration in Solving Partial Differential Equations for Carbon Balance Sustainability

Abstract

This paper introduces the Kolmogorov-Arnold Credit Informed Network Orchestration (KACINO), a novel framework proposed to comprehensively structure and analyze the carbon dynamic system. By synthesizing dynamic processes such as carbon emission and sequestration, a credit information of carbon dynamics is built accumulation, KACINO provides a holistic approach to model the complexities inherent in carbon dynamics. Through systematic analysis and scenario simulations, KACINO facilitates informed policy recommendations aimed at optimizing carbon credit utilization and achieving sustainable environmental outcomes. This paper outlines the theoretical foundation, methodology, and practical applications of KACINO, highlighting its potential to support transformative strategies in climate change mitigation and sustainable development.