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Research and Application of Combined Algorithm Based on Sustainable Computing and Artificial Intelligence

机译:基于可持续计算和人工智能的组合算法的研究与应用

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The Internet is a popular form of information technology development in the new century, and it organizes and analyzes big data by taking effective measures to find useful information. With manpower, it is obviously not enough to be in such a huge information system, so the emergence of sustainable computing and artificial intelligence has become the core of large-scale data processing at this stage. This paper studies the application of the combined algorithm based on sustainable computing and artificial intelligence. In this paper, a new combined intelligent search algorithm is proposed by combining sustainable computing with artificial intelligence. The combination algorithm firstly analyzes the value from the aspects of ecological environment and economic benefits and studies the overall evaluation of sustainable development ability. Secondly, the energy analysis method is used to establish a reasonable comprehensive ecosystem and evaluate its impact on the sustainable development of environment and economy. Finally, the impact of resource consumption, wind speed detection, waste discharge, and utilization of renewable resources in a certain area is analyzed by simulation. Through the experimental results, on the one hand, it is proved that the data obtained by the combined algorithm are more accurate than the single algorithm; on the other hand, the combined algorithm can be further sublimated and widely used for other data detection. The combination algorithm proposed in this paper can effectively detect the required data and has high applicability.
机译:互联网是新世纪信息技术开发的流行形式,它通过采取有效措施来组织和分析大数据,以查找有用的信息。通过人力,显然不足以处于如此庞大的信息系统,因此可持续计算和人工智能的出现已成为此阶段大规模数据处理的核心。本文研究了基于可持续计算和人工智能的组合算法的应用。本文通过将可持续计算与人工智能相结合,提出了一种新的组合智能搜索算法。组合算法首先分析了生态环境的方面和经济效益的价值,研究了可持续发展能力的整体评价。其次,能源分析方法用于建立合理的综合生态系统,并评估其对环境与经济可持续发展的影响。最后,通过模拟分析了资源消耗,风速检测,废物放电和可再生资源利用的影响。通过实验结果一方面,证明了通过组合算法获得的数据比单算法更准确;另一方面,组合算法可以进一步升华并广泛用于其他数据检测。本文提出的组合算法可以有效地检测所需的数据并具有高适用性。

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