Jianqiao Sheng¹, Mengzhu Xu², Jin Han^3,*, Xingyan Deng²

Journal on Big Data, Vol.3, No.4, pp. 183-190, 2021, DOI:10.32604/jbd.2021.024892

Abstract Lightning disaster risk assessment, as an intuitive method to reflect the risk of regional lightning disasters, has aroused the research interest of many researchers. Nowadays, there are many schemes for lightning disaster risk assessment, but there are also some shortcomings, such as the resolution of the assessment is not clear enough, the accuracy rate cannot be verified, and the weight distribution has a strong subjective trend. This paper is guided by lightning disaster data and combines lightning data, population data and GDP data. Through support vector machine (SVM), it explores a way to combine artificial intelligence algorithms with lightning disaster… More >

Hanbo Liu^*, Guang Sun

Journal on Big Data, Vol.3, No.4, pp. 175-182, 2021, DOI:10.32604/jbd.2021.024074

Abstract With the advent of the era of big data, traditional financial management has been unable to meet the needs of modern enterprise business. Enterprises hope that financial management has the function of improving the accuracy of corporate financial data, assisting corporate management to make decisions that are more in line with the actual development of the company, and optimizing corporate management systems, thereby comprehensively improving the overall level of the company and ensuring that the company can be in business with the assistance of financial integration, can better improve and develop themselves. Based on the investigation of enterprises and universities,… More >

Imen Hamraoui^*, Adel Boubaker

Journal on Big Data, Vol.3, No.4, pp. 155-173, 2021, DOI:10.32604/jbd.2021.018703

Abstract Finance 3.0 is still in its infancy. Yet big data represents an unprecedented opportunity for finance. The massive increase in the volume of data generated by individuals every day on the Internet offers researchers the opportunity to approach the question of financial market predictability from a new perspective. In this article, we study the relationship between a well-known Twitter micro-blogging platform and the Tunisian financial market. In particular, we consider, over a 12-month period, Twitter volume and sentiment across the 22 stock companies that make up the Tunindex index. We find a relatively weak Pearson correlation and Granger causality between… More >

Weiwei Lin^1,2,*, Reiko Haga³

Journal on Big Data, Vol.3, No.4, pp. 147-153, 2021, DOI:10.32604/jbd.2021.017299

Abstract In this paper, a cybersecurity threat warning model based on ant colony algorithm is designed to strengthen the accuracy of the cybersecurity threat warning model in the warning process and optimize its algorithm structure. Through the ant colony algorithm structure, the local global optimal solution is obtained; and the cybersecurity threat warning index system is established. Next, the above two steps are integrated to build the cybersecurity threat warning model based on ant colony algorithm, and comparative experiment is also designed. The experimental results show that, compared with the traditional qualitative differential game-based cybersecurity threat warning model, the cybersecurity threat… More >

Jiajun Xie¹, Zuyan Li¹, Han Wu¹, Linhan Li², Bin Pan¹, Peng Guo³,Guang Sun1,*

Journal on Big Data, Vol.3, No.4, pp. 135-145, 2021, DOI:10.32604/jbd.2021.017017

Abstract With the development and progress of today’s network information technology, a variety of large-scale network databases have emerged with the situation, such as Baidu Library and Weipu Database, the number of documents in the inventory has reached nearly one million. So how do you quickly and effectively retrieve the information you want in such a huge database? This requires finding efficient algorithms to reduce the computational complexity of the computer during Information Retrieval, improve retrieval efficiency, and adapt to the rapid expansion of document data. The Quicksort Algorithm gives different weights to each position of the document, and multiplies the… More >

Ying Zhou^*, Weiwei Luo

Journal on Big Data, Vol.3, No.3, pp. 127-133, 2021, DOI:10.32604/jbd.2021.019236

Abstract In recent years, QR code has been widely used in the Internet and mobile devices. It is based on open standards and easy to generate a code, which lead to that anyone can generate their own QR code. Because the QR code does not have the ability of information hiding, any device can access the content in QR code. Thus, hiding the secret data in QR code becomes a hot topic. Previously, the information hiding methods based on QR code all use the way of information hiding based on image, mostly using digital watermarking technology, and not using the coding… More >

Hengyang Wang, Jin Liu^*, Haoliang Ren

Journal on Big Data, Vol.3, No.3, pp. 119-126, 2021, DOI:10.32604/jbd.2021.017184

Abstract The past decade has seen the rapid development of text detection based on deep learning. However, current methods of Chinese character detection and recognition have proven to be poor. The accuracy of segmenting text boxes in natural scenes is not impressive. The reasons for this strait can be summarized into two points: the complexity of natural scenes and numerous types of Chinese characters. In response to these problems, we proposed a lightweight neural network architecture named CTSF. It consists of two modules, one is a text detection network that combines CTPN and the image feature extraction modules of PVANet, named… More >

Yue Li, Jin Liu^*, Shengjie Shang

Journal on Big Data, Vol.3, No.3, pp. 111-118, 2021, DOI:10.32604/jbd.2021.017169

Abstract Visual Question Answering (VQA) has attracted extensive research focus and has become a hot topic in deep learning recently. The development of computer vision and natural language processing technology has contributed to the advancement of this research area. Key solutions to improve the performance of VQA system exist in feature extraction, multimodal fusion, and answer prediction modules. There exists an unsolved issue in the popular VQA image feature extraction module that extracts the fine-grained features from objects of different scale difficultly. In this paper, a novel feature extraction network that combines multi-scale convolution and self-attention branches to solve the above… More >

Wei Fang^1,2,*, Yupeng Chen¹, Qiongying Xue¹

Journal on Big Data, Vol.3, No.3, pp. 97-110, 2021, DOI:10.32604/jbd.2021.016993

Abstract In the past few years, deep learning has developed rapidly, and many researchers try to combine their subjects with deep learning. The algorithm based on Recurrent Neural Network (RNN) has been successfully applied in the fields of weather forecasting, stock forecasting, action recognition, etc. because of its excellent performance in processing Spatio-temporal sequence data. Among them, algorithms based on LSTM and GRU have developed most rapidly because of their good design. This paper reviews the RNN-based Spatiotemporal sequence prediction algorithm, introduces the development history of RNN and the common application directions of the Spatio-temporal sequence prediction, and includes precipitation nowcasting… More >

Neeraj Kumar Sirohi, Mamta Bansal, S. N. Rajan

Journal on Big Data, Vol.3, No.2, pp. 97-97, 2021, DOI:10.32604/jbd.2021.041299

Abstract This article has no abstract. More >