A review on smart city - IoT and deep learning algorithms, challenges

China has resolved to pay more and more attention to the sustainability of ecological construction and social development. The country has proposed a low-carbon economy policy; development and management of enterprises are also actively responding to the call for a low-carbon economy. Through a series of innovations and changes, it intends to realize its own low-carbon production and business development, thereby promoting transformation and optimization of industrial institutions. Innovation is a significant driving force of national economic development. In order to build China into an innovative country, there is a need of national innovation strategy and innovation system. The state vigorously promotes the implementation of innovation-driven development strategies. Enterprises are not only an important carrier for the state to implement mass entrepreneurship and innovation but also a powerful driving force for development of economy. There is a dire need and importance to identify techniques to evaluate impact of corporate innovation on development effects with low-carbon economy. Considering this aforementioned problem, random initialization parameters in back propagation network are used. This evaluation process can easily lead to the functioning of the model falling in the local optimum. The work designs an impact evaluation model (IGWO-BP) with improved gray wolf algorithm (IGWO) in order to optimize BP network. To improve optimization ability for GWO, the study uses the chaotic map to initialize the population. The nonlinear convergence factor strategy as well as dynamic weight strategy is used to promote GWO, so as to optimize initial weight as well as threshold point for the BP network. The IGWO-BP is applied to perform evaluation of the impact in case of enterprise innovation relevant to development effects with low-carbon economy.

Section: Related Workmentioning

confidence: 99%

Evaluation for Development Effect of Enterprise Innovation with Neural Network from Low-Carbon Economy

Bai

Zhang

2022

“…Literature [33] believes that people consume, not only buy things, but also hope to get an emotional experience, the experience of beauty, that is, aesthetics as the object of consumption. Reference [33][34][35] believes that products with technical aesthetics not only give people a sense of beauty in appearance but also make people more comfortable to use. Literature [36] proposed from the macro perspective of society that establishing a scientific design concept, establishing an identification system, and establishing a modern design talent training system are three ways to enhance the aesthetic value of the overall product in society.…”

Section: Wireless Communications and Mobile Computingmentioning

confidence: 99%

Aesthetic Value Evaluation for Digital Cultural and Creative Products with Artificial Intelligence

Liang

2022

The domestic cultural and creative industry has abundant resource advantages and broad development space. The design for cultural and creative products has evolved rapidly with the objective to improve its quality. The cultural and creative industries have seen rapid growth in the recent years wherein digital technologies have been incorporated with the traditional methodologies. The digital cultural and creative aspect acts are extremely important in the dissemination of traditional culture on the network platform. This is also supported by the state vigorously to implement innovative industrial policies. However, the adoption of digital technology in the cultural and creative industry is a novel approach. But there exists lack of understanding in terms of its nature and development protocols. It is thus necessary to study relevant theories to guide the development of digital cultural and creative industry. The increasingly prosperous aesthetic culture, especially development for cultural and creative industries, has comprehensively improved aesthetic value of the cultural and creative products. Therefore, the methods to evaluate and realize the aesthetic value of digital, cultural, and creative products are extremely important and relevant in the present day and age. In this study, neural network is used to design an improved back propagation (BP) network in order to evaluate the aesthetic value of digital cultural and creative products. At the outset, the basic idea, structural characteristics, the learning algorithm, and its flow of functioning in the BP network are analyzed. Then, an aesthetic value evaluation model of digital cultural and creative products with BP network is developed. Next, considering the shortcomings of BP network, a segmentation adaptive strategy is used to improve the view field and step size for artificial fish swarm algorithm (AFSA). Finally, the improvised algorithm is verified wherein the simulation results reveal improvement in algorithm convergence speed as well as improvement in optimal solution accuracy as part of the adaptive improvement approach.

“…Assume that all kinds produced within a region have the same fixed and variable costs. According to the principle of economies of scale, consumer preferences for different products, and firms will opt to manufacture products that are different from those of other firms [27,28]. Following Redding and Turner [10], the labor input l i required to make x i unit of products in region i is…”

Section: Firm Behaviorsmentioning

confidence: 99%

Does High-Speed Rail Promote Agglomeration in China?

Lin

Gan

2022

This paper constructs the agglomeration model of crossregional labor flow and market accessibility based on the new economic geography model. Using panel data in 2000-2013, this paper examines the impact of high-speed railways on industrial agglomeration. The results show that high-speed railway significantly promotes the spatial agglomeration of industrial firms. The high-speed railway promotes industrial agglomeration by promoting crossregional mobility of industrial labor and improving market accessibility. We also construct the instrument variable based on HSR construction cost and apply the TSLS model to solve the potential endogenous problems. At the same time, PSM results also get the net effect caused by the repair of a high-speed railway, which verifies the robustness of the results.