基于大数据和云计算的铝电解生产知识自动化决策系统设计方法与应用验证

现代铝电解生产的决策体系面临着企业集团化、产业集中化、原料多样化、能源价格差异和市场不确定带来的挑战，以往的人工决策方式已无法满足铝电解企业集团绿色高效生产的需求。先进的决策系统必须将大数据和决策知识相结合，才能为铝电解技术与产业升级提供支持，并实现绿色高效生产和节能减排。本项目从知识自动化的新概念出发，拟深入研究基于大数据和云计算的铝电解生产知识自动化决策系统的体系结构与设计方法，提出基于大数据与人机协同的知识自动获取方法，研究基于知识自动化的决策模型与方法，构建资源协调的知识自动化分级决策方法与系统，从而根据铝电解生产需求构建从数据到知识、从知识到决策的可演示技术原型，形成铝电解生产知识自动化决策理论框架。本项目将开拓知识自动化理论体系，发展应用技术基础，不仅具有重要的科学意义，而且对提升我国铝电解企业国际竞争力、实现铝电解工业可持续发展具有重要战略意义。

The decision-making system of modern aluminum production is facing the challenges of enterprise grouping, industrial concentration, resource variety, power price diversity and market uncertainty. The present manual decision mode is no longer able to meet the demand of aluminum group for green and efficient production. It is advisable to combine the big data with experience knowledge for decision-making. According to the new concept of knowledge automation, we bring a new thought and scheme of the knowledge automation decision-making method based on big data and cloud computing to solve the problem. In this project, we will research on the structure and environment design of knowledge automation decision-making system based on Big Data and cloud computation, propose the automatic knowledge acquisition method based on big data and human-machine cooperation, investigate the decision-making model and method based on knowledge automation and construct the leveled decision-making method and system of knowledge automation for resource balance. So that a demonstration technical model is proposed for connections from data to knowledge and from knowledge to decision and the related decision-making theoretical framework for aluminum production is formed. It is scientifically important to exploit the theoretical field of knowledge automation and develop the application method foundation. It is also technically significant to enhance the international competitiveness of aluminum enterprise and enable the sustainable development of the industry.