Data Analysis and Visualization Platform Design for Batteries Using Flask-Based Python Web Service

Liang, Zuyi; Liang, Zongwei; Zheng, Yubin; Liang, Binbin; Zheng, Ling

doi:10.3390/wevj12040187

Cited by 10 publications

(8 citation statements)

References 22 publications

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“…The architecture of Flask Framework is shown in Figure 2. We modified this architecture from the architecture used in (Liang et al, 2021). By using the Flask framework, users will perform interactions, such as providing input and receiving output, through the "views" component.…”

Section: Methodsmentioning

confidence: 99%

Development of stock price prediction system using Flask framework and LSTM algorithm

Bagastio,

Oetama,

Ramadhan

2023

J. Infras. Policy. Dev.

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Stock investment in Indonesia has been steadily growing in the past five years, offering profit potential alongside the risk of loss. Stockholders must analyze the stocks they intend to purchase. Stockholders often analyze stocks by observing patterns that occurred in the previous days to predict future prices. Therefore, a method is needed to simplify the process of analyzing the stock pattern. Although there are already several websites that have the concept of predicting stock prices, these websites do not utilize deep learning algorithms. This research aims to develop a stock price prediction website using deep learning algorithms, specifically the Long Short-Term Memory (LSTM) algorithm to help users predict stock prices. This research focuses on five banks with the highest market capitalization in Indonesia, namely Bank Central Asia, Bank Rakyat Indonesia, Bank Mandiri, Bank Negara Indonesia, and Bank Syariah Indonesia. The website utilizes Flask framework and LSTM. Flask is used to apply LSTM model to the website, while the LSTM can capture long-term dependencies in high-complexity data. The result of this research is a stock price prediction website application, where the prediction results are displayed through the website. The LSTM model for each stock has a Mean Absolute Percentage Error (MAPE) of less than 10%, which indicates that the model is “Highly accurate” based on the MAPE accuracy scale judgment.

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Section: Methodsmentioning

confidence: 99%

Development of stock price prediction system using Flask framework and LSTM algorithm

Bagastio,

Oetama,

Ramadhan

2023

J. Infras. Policy. Dev.

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“…Setelah jawaban didapatkan maka, response (hasil) akan diberikan oleh Flask dan diambil kembali oleh chatbot sebagai jawaban dari pertanyaan pengguna. Penggunaan Flask dalam penelitian ini dikarenakan Flask merupakan framework yang memiliki skalabilitas dan kompabilitas yang tinggi dalam penggunaannya [19]. Proses Flask dalam penelitian ini secara detail dapat dilihat pada Gambar 3.…”

Section: Flaskunclassified

Question Answering Al-Qur’an Menggunakan Generative Pre-Trained Transformer 3.5 Berbasis Chatbot Telegram

Saputra,

Harahap,

Jasril

et al. 2024

Jutisi J. Tek. Sis. Info

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“…e template-based extraction method, through the comparison and analysis of the web pages generated from the same template, always produces a set of general extraction templates, which can directly extract information in practice [19][20][21][22].…”

Section: Related Workmentioning

confidence: 99%

Information Visualization Design of Web under the Background of Big Data

Deng¹,

2022

Mathematical Problems in Engineering

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With the rapid development of the Internet, the information on the Internet presents an explosive growth. Cloud computing and big data analysis technology based on Internet information rise accordingly. However, all web pages contain not only important information but also the noise information irrelevant to the subject information. They seriously affect the accuracy of information extraction, so the research of web page information extraction technology arises at the historic moment and becomes the research hotspot. The quality of web page text information will directly affect the accuracy of later information processing and decision-making. If we can accurately evaluate the information of the web pages captured from the Internet and classify the extracted web pages according to the corresponding characteristics, we can not only improve the efficiency of information processing, but also improve the practical value of the information decision-making system. From the practical application requirements and user-friendly operation point of view, the information visualization of web design based on big data is studied in this paper. Specifically, the system designed in this paper improves the traditional template-based web information extraction method, establishes a web information extraction rule scheme combined with templates, and achieves the goal of web information extraction rule selection and template generation in the visual environment. Finally, the visualization algorithm based on T-SNE verifies the effectiveness of the web page information visualization algorithm designed in this paper.

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Data Analysis and Visualization Platform Design for Batteries Using Flask-Based Python Web Service

Cited by 10 publications

References 22 publications

Development of stock price prediction system using Flask framework and LSTM algorithm

Development of stock price prediction system using Flask framework and LSTM algorithm

Question Answering Al-Qur’an Menggunakan Generative Pre-Trained Transformer 3.5 Berbasis Chatbot Telegram

Information Visualization Design of Web under the Background of Big Data

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