Home / Journals / JBD / Vol.5, No.1, 2023
  • Open AccessOpen Access

    ARTICLE

    Correlation Analysis of Turbidity and Total Phosphorus in Water Quality Monitoring Data

    Wenwu Tan1, Jianjun Zhang1,*, Xing Liu1, Jiang Wu1, Yifu Sheng1, Ke Xiao2, Li Wang2, Haijun Lin1, Guang Sun3, Peng Guo4
    Journal on Big Data, Vol.5, pp. 85-97, 2023, DOI:10.32604/jbd.2022.030908 - 26 December 2023
    Abstract At present, water pollution has become an important factor affecting and restricting national and regional economic development. Total phosphorus is one of the main sources of water pollution and eutrophication, so the prediction of total phosphorus in water quality has good research significance. This paper selects the total phosphorus and turbidity data for analysis by crawling the data of the water quality monitoring platform. By constructing the attribute object mapping relationship, the correlation between the two indicators was analyzed and used to predict the future data. Firstly, the monthly mean and daily mean concentrations of More >

  • Open AccessOpen Access

    ARTICLE

    Analysis of Tourism Demand Difference Based on Data Mining and Intelligent Analysis

    Peng Cheng1,2,*
    Journal on Big Data, Vol.5, pp. 69-84, 2023, DOI:10.32604/jbd.2023.046294 - 24 November 2023
    Abstract To serve as a reference for future foreign tourism study, relevant tourist sectors have done in-depth investigations on foreign tourism both domestically and internationally. A study of outbound tourism activities from the viewpoint of tourists can examine its development law and create successful marketing tactics based on the rise in the number of foreign tourists. Based on this, this study suggests a data mining technique to examine the variations in travel needs and marketing tactics among various consumer groups. The combined example analysis demonstrates how logical and useful our data mining analysis is. Our data More >

  • Open AccessOpen Access

    ARTICLE

    Research on the Electric Energy Metering Data Sharing Method in Smart Grid Based on Blockchain

    Shaocheng Wu1, Honghao Liang1, Xiaowei Chen1, Tao Liu1, Junpeng Ru2,3, Qianhong Gong2,3, Jin Li2,3,*
    Journal on Big Data, Vol.5, pp. 57-67, 2023, DOI:10.32604/jbd.2023.044257 - 24 November 2023
    Abstract Enabling data sharing among smart grid power suppliers is a pressing challenge due to technical hurdles in verifying, storing, and synchronizing energy metering data. Access and sharing limitations are stringent for users, power companies, and researchers, demanding significant resources and time for permissions and verification. This paper proposes a blockchain-based architecture for secure and efficient sharing of electric energy metering data. Further, we propose a data sharing model based on evolutionary game theory. Based on the Lyapunov stability theory, the model’s evolutionary stable strategy (ESS) is analyzed. Numerical results verify the correctness and practicability of More >

  • Open AccessOpen Access

    ARTICLE

    Author’s Age and Gender Prediction on Hotel Review Using Machine Learning Techniques

    Muhammad Hood Khan1, Bilal Khan1,*, Saifullah Jan1, Muhammad Imran Chughtai2
    Journal on Big Data, Vol.5, pp. 41-56, 2023, DOI:10.32604/jbd.2022.044060 - 17 November 2023
    Abstract Author’s Profile (AP) may only be displayed as an article, similar to text collection of material, and must differentiate between gender, age, education, occupation, local language, and relative personality traits. In several information-related fields, including security, forensics, and marketing, and medicine, AP prediction is a significant issue. For instance, it is important to comprehend who wrote the harassing communication. In essence, from a marketing perspective, businesses will get to know one another through examining items and websites on the internet. Accordingly, they will direct their efforts towards a certain gender or age restriction based on… More >

  • Open AccessOpen Access

    ARTICLE

    Hybrid Model for Short-Term Passenger Flow Prediction in Rail Transit

    Yinghua Song1,2, Hairong Lyu1,2, Wei Zhang1,2,*
    Journal on Big Data, Vol.5, pp. 19-40, 2023, DOI:10.32604/jbd.2023.038249 - 05 October 2023
    Abstract A precise and timely forecast of short-term rail transit passenger flow provides data support for traffic management and operation, assisting rail operators in efficiently allocating resources and timely relieving pressure on passenger safety and operation. First, the passenger flow sequence models in the study are broken down using VMD for noise reduction. The objective environment features are then added to the characteristic factors that affect the passenger flow. The target station serves as an additional spatial feature and is mined concurrently using the KNN algorithm. It is shown that the hybrid model VMD-CLSMT has a More >

  • Open AccessOpen Access

    ARTICLE

    Sentiment Analysis Based on Performance of Linear Support Vector Machine and Multinomial Naïve Bayes Using Movie Reviews with Baseline Techniques

    Mian Muhammad Danyal1, Sarwar Shah Khan2,4, Muzammil Khan2,*, Muhammad Bilal Ghaffar1, Bilal Khan1, Muhammad Arshad3
    Journal on Big Data, Vol.5, pp. 1-18, 2023, DOI:10.32604/jbd.2023.041319 - 29 September 2023
    Abstract Movies are the better source of entertainment. Every year, a great percentage of movies are released. People comment on movies in the form of reviews after watching them. Since it is difficult to read all of the reviews for a movie, summarizing all of the reviews will help make this decision without wasting time in reading all of the reviews. Opinion mining also known as sentiment analysis is the process of extracting subjective information from textual data. Opinion mining involves identifying and extracting the opinions of individuals, which can be positive, neutral, or negative. The… More >

Per Page:

Share Link