scholarly journals Influencing Factors and Forecasting Statistics of Enterprise Market Sales Based on Big Data and Intelligent IoT

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Zhen Guo ◽  
Tao Zou
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Big Data Analysis ◽  
Classification Algorithm ◽  
Processing Method ◽  
Enterprise Management ◽  
Training Process ◽  
Data Processing Method ◽  
Knn Classification ◽  
Positive Effect

With the acceleration of economic development, enterprise management is facing more severe challenges. Big data analysis based on the intelligent Internet of Things (IoT) has a positive effect on the development of enterprise management and can make up for the shortcomings of enterprise management. In this paper, we develop a big data processing method based on intelligent IoT which can mine the factors that affect the company’s market sales from the collected data. Then, we propose a KNN classification algorithm based on overlapping k -means clustering. This algorithm adds a training process to the traditional KNN algorithm, which can accurately classify data and greatly improve the efficiency of the classification algorithm. Numerical analysis results prove the effectiveness of the proposed algorithm.

scholarly journals Analysis of Enterprise Strategic Management Issues and Coping Strategies Based on Big Data Analysis

2020 ◽  
Vol 214 ◽  
pp. 01017
Author(s):  
Ziqi ZHONG ◽  
Wang Haoran ◽  
WANG JUNSHENG
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Strategic Management ◽  
Big Data Analysis ◽  
Practical Significance ◽  
Enterprise Management ◽  
Chinese Enterprises ◽  
Corporate Strategic Management ◽  
The Times ◽  
And Coping

Corporate strategic management is an important management mode that affects the development of an enterprise. It plays a very important role in the development of corporate strategic management. In recent years, information technology has developed rapidly, data is frequently updated, and huge amounts of data are generated every day. Social development has entered the era of big data, which makes enterprises face more opportunities and challenges in formulating strategies and operating management. In order to enable enterprises to adapt to the development of the times and obtain healthy and sound development results. This article analyzes and summarizes the new characteristics of enterprise management in the context of big data, and applies big data analysis technology to the environmental analysis of enterprises, and points out the problems of strategic management of enterprises in the context of big data. This article aims at the current problems and proposes specific strategies after in-depth research, which provides a reference basis for strategic management of enterprises in the era of big data. It has certain practical significance and can help Chinese enterprises quickly adapt to the new environment.

scholarly journals IoT-based Machinery Failure Predictive Solution using Big Data Analysis on the MIMII Dataset

2020 ◽  
Author(s):  
Sana Talmoudi ◽  
Tetsuya Kanada ◽  
Yasuhisa Hirata
Keyword(s):  
Complex System ◽  
Big Data ◽  
Data Analysis ◽  
Big Data Analysis ◽  
Analysis Method ◽  
Prior Training ◽  
Training Process ◽  
Learning Methods ◽  
Vibration Data ◽  
Smart Industry

Abstract One of the main focuses of smart industry is machinery failure predictive solutions. To achieve this, IoT-based solutions have been widely deployed. However, data processing and decision making remain challenging. The absence of enough knowledge has been the primarily limitation of statistical methods and supervised learning methods. Therefore, unsupervised learning methods are gaining more popularity but still have limits to cover effectively the pre-signs of failures due to the complexity of training process and results visualization. Previously, we proposed a novel Big Data Analysis method on audio/vibration data to cover effectively the pre-signs of failures through data visualization without complex learning or processing. We validated our proposal on a demo system. In the present work, we are using part of the MIMII dataset to test our proposed analysis method on a real-world-like data and verify the validity of our proposal on a more complex system. We are showing that we can detect abnormal machine behaviors and predict failures without prior training or knowledge of the target monitored machine.

scholarly journals Feature Recognition of English Based on Deep Belief Neural Network and Big Data Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Xiaoling Liu
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Feature Recognition ◽  
Evaluation Method ◽  
Training Model ◽  
Recognition System ◽  
Big Data Analysis ◽  
Classification Algorithm ◽  
Deep Belief Network ◽  
Belief Network

Realizing accurate recognition of Chinese and English information is a major difficulty in English feature recognition. Based on this difficulty, this paper studies the English feature recognition model based on deep belief network classification algorithm and Big Data analysis. First, the basic framework based on deep belief network classification algorithm and Big Data analysis is proposed. Combined with the Big Data analysis training model, the English feature information is processed. Through the recognition of different English text features, the recognition and matching of English features are realized. Then the errors of deep belief network classification algorithm and Big Data analysis are evaluated. Second, this paper describes the quantitative evaluation of deep belief network classification algorithm and Big Data analysis in this system. In the evaluation, the language feature evaluation method is used to improve the evaluation function. At the same time, the deep belief network classification algorithm and Big Data analysis are used to self-study the model, and the English feature recognition method with strong applicability is established. Finally, the effectiveness of the recognition system is verified by the experiment.

scholarly journals The link between transformational leadership and the team performance in China through big data analysis

2021 ◽  
Vol 251 ◽  
pp. 01040
Author(s):  
Mingxi Peng
Keyword(s):  
Transformational Leadership ◽  
Big Data ◽  
Data Analysis ◽  
Team Performance ◽  
Management Practice ◽  
Big Data Analysis ◽  
Enterprise Management ◽  
Chinese Labor

Transformational leadership as one kind of management field increasingly affects the performance of an organization. The paper aims to explore the link between transformational leadership and team performance through big data approach, and examine whether the transformational leadership can be adopted appropriately in Chinese labor intensive enterprise’ management practice.

Insights into seismic hazard from big data analysis of ground motion simulations

2019 ◽  
Vol 9 (1) ◽  
pp. 01-12 ◽  
Author(s):  
Kristy F. Tiampo ◽  
Javad Kazemian ◽  
Hadi Ghofrani ◽  
Yelena Kropivnitskaya ◽  
Gero Michel
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Seismic Hazard ◽  
Ground Motion ◽  
Big Data Analysis ◽  
Ground Motion Simulations

A Social Big Data Analysis on Sport Participation

2020 ◽  
Vol 25 (2) ◽  
pp. 18-30
Author(s):  
Seung Wook Oh ◽  
Jin-Wook Han ◽  
Min Soo Kim
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Sport Participation ◽  
Big Data Analysis ◽  
Social Big Data
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