Analysis of Environmental Governance Expense Prediction Reform With the Background of Artificial Intelligence

In this paper, Artificial Intelligence assisted rule-based confidence metric (AI-CRBM) framework has been introduced for analyzing environmental governance expense prediction reform. A metric method is to assess a level of collective environmental governance representing general, government, and corporate aspects. The equilibrium approach is used to calculate improvements in the source of environmental management based on cost, and it is tailored to test the public sector-corporation for environmental shared governance. The overall concept of cost prediction or estimation of environmental governance is achieved by the rule-based confidence method. The framework compares the expected cost to the environment of governance to determine the efficiency of the cost prediction process.

The Agglomeration Mechanism of Network Emerging E-commerce Industry Based on Social Science

Network emerging e-commerce refers to the development of wireless broadband technology, smart terminal technology, near-field network, etc. as the driving force. It is the emerging e-commerce represented by the continuous development of modern e-commerce and the integration of commerce. This paper proposes to use Michael Porter’s cluster theory method, income increasing algorithm, and spatial Gini coefficient method to sort out and analyze the research results of industrial agglomeration problems, further study the relationship of e-commerce industry agglomeration mechanism, and build agglomeration simulation model , the construction of the centripetal force model of the industrial agglomeration area, through the analysis of the production factors of the e-commerce industry, and then study the influence of each factor on the development of the e-commerce industry. Finally, this paper selects and uses 16 standard mechanical data sets to investigate and analyze the agglomeration mechanism of the e-commerce industry, which verifies the accuracy and overall applicability of the method.

Implementation of Data Mining Technology in Bonded Warehouse Inbound and Outbound Goods Trade

For the taxed goods, the actual freight is generally determined by multiplying the allocated freight for each KG and actual outgoing weight based on the outgoing order number on the outgoing bill. Considering the conventional logistics is insufficient to cope with the rapid response of e-commerce orders to logistics requirements, this work discussed the implementation of data mining technology in bonded warehouse inbound and outbound goods trade. Specifically, a bonded warehouse decision-making system with data warehouse, conceptual model, online analytical processing system, human-computer interaction module and WEB data sharing platform was developed. The statistical query module can be used to perform statistics and queries on warehousing operations. After the optimization of the whole warehousing business process, it only takes 19.1 hours to get the actual freight, which is nearly one third less than the time before optimization. This study could create a better environment for the development of China's processing trade.

The Study of Para-Social Interaction with e-Word-of-Mouth for Influencer Marketing by Complex Computing

The purpose of this study was focused on exploring the relationship among the fans’ preferences, fans’ para-social interaction, and fans’ word-of-mouth. A survey consisted of 21 items based on the literature review and developed by this study. An online survey was distributed to the users of YouTube in Taiwan. A total of 606 valid samples was collected by survey. The instrument passed the reliability and validity test. Further, the data process applied the PLS (partial least squares) regression analysis methodology. The result shows that the ‘attractive’ impacted ‘para-social interaction’, ‘e-word-of-mouth’, and ‘preferences of fans’ positively. In addition, the para-social interaction plays an important role as a mediator between influencer’s attractiveness, w-word-of-mouth, and preferences of fans. Some suggestions were provided for social media influence’ related studies as reference.

Machine Learning Algorithms for Big Data Applications With Policy Implementation

This article examines the policy implementation literature using a text mining technique, known as a structural topic model (STM), to conduct a comprehensive analysis of 547 articles published by 11 major journals between 2000 and 2019. The subject analyzed was the policy implementation literature, and the search included titles, keywords, and abstracts. The application of the STM not only allowed us to provide snapshots of different research topics and variation across covariates but also let us track the evolution and influence of topics over time. Examining the policy implementation literature has contributed to the understanding of public policy areas; the authors also provided recommendations for future studies in policy implementation.

Analysis of the application of information technology in the management of rural population return based on the era of big data

Based on rural population return management, governance theory, and information technology theory, this paper analyzes the specific performance of rural areas in managing population return, and describes the overview, quantity, life status, and demographic characteristics of rural population return, as well as the current situation of rural population return management. A method of managing rural population return based on a rural population return management model constructed by a machine learning algorithm is designed. The empirical results show that the method designed in this paper is low-cost, fast, and highly accurate, and is well suited for improving and expanding the system for managing rural return flows. The research in this paper provides a reference for further promoting the transformation strategy of rural governance in the context of new urbanization.

Accounting Information Quality, Financing Constraints, And Company Innovation Investment Efficiency By Big Data Analysis

This paper takes the listed companies in China from 2008 to 2017 as the research sample to study the relationship between accounting information quality (AIQ) and company innovation investment efficiency. The results show that AIQ is negatively correlated with both the underinvestment and overinvestment of corporate innovation. Further, AIQ can alleviate financing constraints and reduce the lack of innovation investment; At the same time, AIQ can also alleviate the agency conflict and reduce the excessive investment in innovation. Finally, AIQ can promote the innovation investment efficiency of companies with low information environment.

Measurement Method and Application of a Deep Learning Digital Economy Scale Based on a Big Data Cloud Platform

In recent years, with the acceleration of the process of economic globalization and the deepening of my country's financial liberalization, the scale of international short-term capital flows has been extremely rapid. This article mainly studies the deep learning digital economy scale measurement method and its application based on the big data cloud platform. This article uses the indirect method to estimate the stock of renminbi circulating abroad. The results show that the application of big data cloud platforms can increase the development share of digital media and digital transactions in the digital economy, and optimize the structure of China's digital economy.

Application of CSK Encryption Algorithm in Video Synergic Command Systems

Video command and dispatch systems have become essential communication safeguard measures in circumstances of emergency rescue, epidemic prevention, and control command as, data security has become especially important. After meeting the requirements of voice and video dispatch, this paper proposes an end-to-end encryption method of multimedia information that introduces a multiple protection mechanism including selective encryption and selective integrity protection. The method has a network access authentication and service encryption workflow, which implants startup authentication and key distribution into the information control signaling procedure. This method constitutes a key pool with the three-dimensional Lorenz System, the four-dimensional Cellular Neural Network (CNN) System and the four-dimensional Chen System where the key source system and initial conditions are decided by the plaintext video frame itself. Then, this method optimizes the chaotic sequences to further enhance system security.

A two-echelon responsive health analytic model for triggering care plan revision in geriatric care management

Due to the increasing ageing population, how can caregivers effectively provide long-term care services to meet the older adults’ needs with finite resources is emerging. In addressing this issue, nursing homes are striving to adopt smart health with the internet of things and artificial intelligence to improve the efficiency and sustainability of healthcare. This study proposed a two-echelon responsive health analytic model (EHAM) to deliver appropriate healthcare services in nursing homes under the Internet of Medical Things environment. A novel care plan revision index is developed using a dual fuzzy logic approach for multidimensional health assessments, followed by care plan modification using case-based reasoning. The findings reveal that EHAM can generate patient-centred long-term care solutions of high quality to maximise the satisfaction of nursing home residents and their families. Ultimately, sustainable healthcare services can be within the communities.