Demand Forecasting for Rural E-Commerce Logistics: A Gray Prediction Model Based on Weakening Buffer Operator

Zeng, Minling; Liu, Runmin; Jiang, Yizhang

doi:10.1155/2022/3395757

Cited by 16 publications

(14 citation statements)

References 12 publications

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“…Recommendation. Data mining is to mine valuable information from a large amount of data [20]. e data mined by data mining technology is huge and dynamic.…”

Section: Technical Foundation Of Dm Personalisedmentioning

confidence: 99%

[Retracted] Personalised Recommendation of PE Network Course Environment Resources Using Data Mining Analysis

Min

2022

Journal of Environmental and Public Health

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PE education reform is positively influenced by the creation and use of resources for PE courses as a supplement to and development of traditional teaching strategies. In order to mine the vast amount of data in the network PE curriculum resource system and find useful patterns, this paper uses highly automated DM technology. Additionally, you can forecast users’ upcoming actions and suggest particular course resources to them. This recommendation system makes course resources that users might be interested in based on their browsing history, browsing patterns, and browsing preferences. User registration and login, course retrieval, browsing history, course recommendation, and a module for course scoring are among the system’s primary features. Studies reveal that this method’s recommendation accuracy is up to 96.2 percent, or about 10% higher than that of conventional recommendation methods. The recommendation strategy put forth in this paper has a good recommendation effect, high accuracy, and coverage. It also plays a part in improving the hidden semantic model’s accuracy. For individualised curriculum resource recommendations, this recommendation system offers a good solution.

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“…Recommendation. Data mining is to mine valuable information from a large amount of data [20]. e data mined by data mining technology is huge and dynamic.…”

Section: Technical Foundation Of Dm Personalisedmentioning

confidence: 99%

[Retracted] Personalised Recommendation of PE Network Course Environment Resources Using Data Mining Analysis

Min

2022

Journal of Environmental and Public Health

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“…Communication in the Era of Big Data. e need for a network public opinion monitoring method based on big data technology [18][19][20] has gradually emerged as a result of the expansion of interconnected network data and the inability of the traditional network public opinion monitoring method to meet those needs. Although there are numerous technologies involved in monitoring public opinion, web crawlers, information extraction from webpages, and automatic word segmentation are among the most frequently used big data technologies overall.…”

Section: Analysis Of the Characteristics Of Network Public Opinionmentioning

confidence: 99%

[Retracted] The Spread, Rise, and Fall of University Students’ Interconnected Internet Public Opinion in the Age of Big Data

Wang

2022

Journal of Environmental and Public Health

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With the interconnected network’s quick growth and widespread adoption, it has only made sense that it would serve as a hub for the dissemination of ideologies and cultural information as well as an amplifier for public opinion. The world is dualistic. The popularity of the connected network has both positive and negative effects on society. It makes people’s lives more convenient, but it also has some drawbacks. Public opinion will quickly build up on the interconnected network as network communication becomes a significant method of disseminating social information, and the number of public opinion events on the interconnected network will also rise. Accurately understanding the law of higher education students’ online public opinion to effectively direct and utilise online public opinion to carry out ideological education for students and to realise the establishment of students' good values, mental health, and behavioural norms, it is necessary to understand how to spread and rise and fall in the era of big data work. The parameter inversion model of online public opinion is established in this article based on the aforementioned issues. The parameter inversion algorithm is used to calculate the trend value of online public opinion, and the degree of fitting between the trend value of actual data and the trend value of parameter inversion is compared. The study discovered that the experiment’s fitting value is as high as 90%. The model’s prediction of the overall trend of the event development is correct, indicating that the model parameters are inverted, even though the actual public opinion data are affected by a variety of random factors, so some deviations may occur at local points. The internal law of the evolution of events that spread public opinion has been discovered, and it can be used to accurately describe the evolution and development of the public opinion dissemination process as it is driven by its internal mechanism. In the age of big data, this article analyses and summarises the rise, fall, and distribution of online public opinion among students at institutions of higher education. It also serves as a guide for monitoring and directing online public opinion in colleges and other institutions of higher education.

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“…Every alteration in people's behavior, location, and even physical physiological data has now become data that can be analyzed and recorded with the advent of mobile terminal devices like smartphones. Big data-related technology development is the foundation for the visual display interface of big data information [ 7 ]. Data gathering, analysis, and presentation are the three main steps in the processing of big data.…”

Section: Introductionmentioning

confidence: 99%

Application of Big Data Clustering and Visual Communication in Business Website Interface Design

2022

Computational Intelligence and Neuroscience

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The interface design of commercial websites is used in this paper to demonstrate the application of big data clustering and visual communication technologies. This paper presents the new requirements of user integration, emotion, and personalization by analyzing the broad influence of big data clustering technology and visual communication on the design concept and design method of commercial website interface design. Then, focusing on the information of visual graphic elements in web interface design and discussing how structures, images, words, emotions, and other elements can convey information more effectively through graphic means, the information in the web interface is creatively divided into two types: implicit and explicit. The database for the interface interaction system is built as part of this paper, which also uses fuzzy clustering to organize the data from the interface retrieval database and the hierarchical structure design method of process constraints to carry out interface information interaction and big data fusion processing. According to experiments, this algorithm’s accuracy can reach 95.75%, which is about 11% higher than that of other approaches. This study can offer a workable design strategy for a business website’s user interface.

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Demand Forecasting for Rural E-Commerce Logistics: A Gray Prediction Model Based on Weakening Buffer Operator

Cited by 16 publications

References 12 publications

[Retracted] Personalised Recommendation of PE Network Course Environment Resources Using Data Mining Analysis

[Retracted] Personalised Recommendation of PE Network Course Environment Resources Using Data Mining Analysis

[Retracted] The Spread, Rise, and Fall of University Students’ Interconnected Internet Public Opinion in the Age of Big Data

Application of Big Data Clustering and Visual Communication in Business Website Interface Design

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