Factors Affecting the Evolution of Advanced Manufacturing Innovation Networks Based on Cloud Computing and Multiagent Simulation

Abstract

Facing the pressure of low-cost competition brought by the homogenization of commodities, the manufacturing industry seeks to survive by providing services. By providing outsourcing of value-added services to date, we are focusing on innovation in our business model. With the advancement of science and technology, manufacturing innovation is facing higher challenges, especially the popularization of the Internet, which makes the manufacturing industry have to move closer to new industries. Based on cloud computing, this paper conducts a multiagent simulation on the evolution factors of the innovation network of advanced manufacturing. This article takes three types of simulation subjects: evolutionary network, manufacturing (cluster), and innovation evolution system as the research objects. The factors affecting the evolution of the research are innovation resources, innovation opportunities, innovation desire, innovation pressure, relationship strength, network scale, and network scope. Network differences carry over variable indicators and analyze quantitative regression indicators and then build a research model. The research results show that the average conversion efficiency of the manufacturing industry (0.523) is significantly lower than the average R&D innovation efficiency (0.725), which to a certain extent indicates that the manufacturing industry still has weak links in the export conversion stage at the back end of the innovation value chain. Some of the companies may have problems such as low ability to transform scientific and technological achievements and insufficient export competitiveness of high-tech products, which to a large extent affects and restricts the improvement of manufacturing export transformation efficiency.

Analysis on Innovation Path of Business Administration Based on Artificial Intelligence

“…Wang and Cao. and others proposed that the business model is a comprehensive description of three key factors for the production and operation of enterprises: value flow, revenue flow, and logistics [6]. Li et al define a business model, which means that creating a profitable business activity will involve the overall structure of customers, processes, channels and suppliers, resources, and capabilities [7].…”

Application of Data Mining Algorithm in Electric Power Marketing Inspection Forecast Analysis

“…Whether electric power forecast is accurate or not has great influence on society and electric power enterprise itself. For example, China has experienced a serious shortage of power supply due to insufficient investment in power facilities due to insufficient prediction of future electricity demand, which has a great negative impact on the development of the 11th Five-Year Plan [3]. e importance of power demand forecasting can be seen.…”

Developing Business Management Concepts in the Economic Field Based on Artificial Intelligence in Light of Increasing Data

“…This will help enterprise business management better adapt to the requirements of future development. Furthermore, in this overall context, the integration of AI and corporate business management will showcase additional features that cater to demand rather than just highlighting the interplay between different kinds of financial data, not just to enhance transaction efficiency but also to lower operating costs by concentrating on the customer's product experience [4] [5]. Considering future development, the advancement of artificial intelligence enables company business management services and goods to become even more intimately connected to the user scene, comprehending user needs and continuously introducing workable solutions to satisfy the needs of various users rather than just a technical product.…”