Due to the expansion in scale, complexity in structure, and intelligence in functionality of the power system in recent years, the amount of data generated has been increasing daily, leading the power system into a "data explosion" era. Considering the unique properties of electric energy, load forecasting plays an extremely important role in power production. In the current environment, traditional load forecasting methods are difficult to meet the operational requirements of the power system. Therefore, it has become a top priority in the field of load forecasting to effectively establish models for processing large data to improve the accuracy of load forecasting. Based on the current research status both domestically and internationally, this article proposes a method for processing big data by building an artificial neural network using the backpropagation algorithm.
KEYWORDS: Blockchain, Databases, Design and modelling, Data modeling, Telecommunications, Tolerancing, Systems modeling, Failure analysis, Technology, Computing systems
The emergence of cryptocurrencies has promoted the development of blockchain technology. However, due to the low performance and poor scalability of the blockchain, it is difficult to apply the blockchain technology to production. Analysis of its essential reason is mainly caused by the distributed consensus protocol. Distributed consensus protocols provide data transparency, integrity, and immutability in a decentralized and untrusted environment, but good security greatly sacrifices scalability. In order to improve the performance and scalability of the system. This paper first improves the Byzantine consensus protocol and improves the throughput of a single shard; on this basis, an efficient shard formation protocol is designed, which can safely assign nodes to shards. This paper relies on trusted hardware (SGX) to achieve consensus and sharding protocol performance improvements. Second, we design a transaction protocol that ensures transaction security and flexibility even when the transaction coordinator is malicious; finally, our research is extensively evaluated on local clusters and on Google Cloud Platform. The results show that the consensus and shard formation protocol in this paper outperforms other advanced solutions in scale and can well scale the blockchain system through sharding and consensus formation protocol. More importantly, the scalable blockchain system based on the sharding strategy proposed in this paper achieves high throughput and can handle Visa-level workloads.
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