مشخصات مقاله | |
ترجمه عنوان مقاله | تجزیه و تحلیل پیش بینی درآمد محصولات مالی بلاکچین مبتنی بر بهینه سازی ازدحام ذرات |
عنوان انگلیسی مقاله | Analysis of Earnings Forecast of Blockchain Financial Products based on Particle Swarm Optimization |
انتشار | مقاله سال 2020 |
تعداد صفحات مقاله انگلیسی | 21 صفحه |
هزینه | دانلود مقاله انگلیسی رایگان میباشد. |
پایگاه داده | نشریه الزویر |
نوع نگارش مقاله |
مقاله پژوهشی (Research Article) |
مقاله بیس | این مقاله بیس نمیباشد |
نمایه (index) | Scopus – Master Journals List – JCR |
نوع مقاله | ISI |
فرمت مقاله انگلیسی | |
ایمپکت فاکتور(IF) |
2.041 در سال 2019 |
شاخص H_index | 106 در سال 2020 |
شاخص SJR | 0.849 در سال 2019 |
شناسه ISSN | 0377-0427 |
شاخص Quartile (چارک) | Q2 در سال 2019 |
مدل مفهومی | ندارد |
پرسشنامه | ندارد |
متغیر | ندارد |
رفرنس | دارد |
رشته های مرتبط | مدیریت، مهندسی کامپیوتر |
گرایش های مرتبط | مدیریت مالی، مهندسی الگوریتم و محاسبات، هوش مصنوعی |
نوع ارائه مقاله |
ژورنال |
مجله | مجله ریاضی محاسباتی و کاربردی – Journal of Computational and Applied Mathematics |
دانشگاه | School of Economics and Management, Changchun University of Science and Technology, Changchun 130022, China |
کلمات کلیدی | بهینه سازی ازدحام ذرات، بلاکچین، محصولات مالی، درآمد |
کلمات کلیدی انگلیسی | particle swarm optimization; blockchain; financial product; earnings |
شناسه دیجیتال – doi |
https://doi.org/10.1016/j.cam.2020.112724 |
کد محصول | E14246 |
وضعیت ترجمه مقاله | ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید. |
دانلود رایگان مقاله | دانلود رایگان مقاله انگلیسی |
سفارش ترجمه این مقاله | سفارش ترجمه این مقاله |
فهرست مطالب مقاله: |
Abstract 1. Introduction 2. Literation review 3. Proposed method 4. Experiments 5. Discussion 6. Conclusions References |
بخشی از متن مقاله: |
Abstract
The purpose of this study is to solve the problems of large number of iterations, limitations and poor fitting effect of traditional algorithms in predicting the yield rate of blockchain financial products. In this study, bitcoin yield rate is taken as the research object, and data from June 2, 2016 to December 30, 2018 are collected, totaling 943 pieces. The BP neural network, support vector regression machine algorithm and particle swarm optimization least square vector algorithm are respectively adopted to carry out model simulation and empirical analysis on the collected data, and it is concluded that particle swarm optimization least square vector algorithm has the best fitting effect. Subsequently, the Ethereum (ETH) yield rate is selected as the research object, and the model simulation and empirical analysis are carried out on it, which verifies that the optimized algorithm have better prediction and fitting on the time series. The results show that the particle swarm optimization algorithm among the three algorithms mentioned in this research has the best prediction effect. Therefore, the results of this study have a good fitting effect on the prediction of the yield rate of blockchain financial products, have a good guiding effect on the investors of blockchain financial products, and have a good guiding significance for the study of the yield rate of China’s blockchain financial products. Introduction Since the beginning of the 20th century, the global economy has developed rapidly, and many factors that hinder economic development have been overwhelmed by the fast-growing economy. The financial market has developed rapidly. The financial market is the medium of economic development. It not only regulates the resource allocation of the entire economy and society, but also plays a vital role in economic development [1]. Since 2013, with the development of the Internet, many Internet financial products (such as Yu’E Bao, Baidu Financial Management, etc.) have been born, which has aroused the concern of the whole society. At present, emerging Internet finance with global influence includes crowdfunding, P2P, block chain and digital currency, which will play a crucial role in the future of global financial market [2]. Blockchain technology is an application under a new scenario developed based on computer technology, which has the characteristics of encryption algorithm, consensus mechanism, distributed node for data storage and point-to-point transmission. Consensus mechanism is an important part of blockchain, which uses mathematical algorithm to establish trust and obtain interests between different nodes in the blockchain system [3]. As the first successful application of blockchain technology, bitcoin has become a hot topic in blockchain research [4]. |