With the continuous development of the social economy, the urban residential structure is also changing, and people have higher and higher requirements for the living environment. Moreover, the landscape construction of public spaces in cities is an important part of the city. It is easy to neglect the comprehensive consideration of historical development and regional culture in architectural projects. The overall lack of individuality in urban design, the lack of characteristics of adapting measures to local conditions, and the blind emphasis on architectural landscaping have led to a serious lack of regional cultural characteristics and spiritual culture in public places. Therefore, in terms of the problems of insufficient landscape construction quality and green concepts being insufficient in the construction environment of cities, an evaluation method system is established in the paper to further study the shortcomings of the scenic area architecture. What is more, relying on the personal experience of the users in the scenic spot and understanding the real needs of the public space landscape environment around the scenic spot, scientific methods and a complete system are applied to make an overall assessment of the public space in the built residential area. Besides, according to the data analysis of the simulation experiment, the advantages and disadvantages of the public space in the residential area are extracted. Combined with the current research status, the green concept design strategy of the public space landscape environment in the scenic spot is summarized. Lastly, according to the data analysis of the simulation experiment, the evaluation satisfaction of the activity atmosphere, plant configuration, and overall layout is improved by 4.2%, 3.7%, and 3.1% compared with other methods, which proves that this study has a more reasonable planning program to meet the various needs of public open space. The development of urban landscape design provides a valuable reference.

With the rapid development of network technology, people are increasingly dependent on the internet. When BP neural network (BNN) performs simulation calculation, it has the advantages of fast training speed, high accuracy, and strong robustness and is widely used in large-scale public (LSP) building energy consumption (BEC) monitoring platforms (LPB). Therefore, the purpose of this paper to study the energy consumption monitoring platform of large public (LP) buildings is to better monitor the energy consumption of public buildings, so as to supplement or remedy at any time. This article mainly uses the data analysis method and the experimental method to carry on the relevant research and the system test to the BNN. The experimental results show that the monitoring system (MS) platform designed in this paper has real-time performance, and its time consumption is between 2 s and 3 s, and the data accords with theory and reality.

With the phased spatial planning of the rural revitalization strategy, the proportion of architecture energy consumption in the overall social energy consumption is also increasing year by year. Considering the hot summer and cold winter areas, the proportion of architecture energy consumption in the total energy consumption is very large. The ecological environment and natural resources have been greatly threatened, and the issue of energy conservation and environmental protection is imminent. Energy consumption prediction and analysis is an important branch of building energy conservation in the field of building technology and science. Aiming at the energy consumption characteristics of rural architectures in areas with hot summer and cold winter, this paper proposes a method for constructing a neural network model. When building a neural network, the dataset is called and the function is applied randomly to training samples. The data are used for simulation tests to analyze the fit between the predicted results and the calculated results. Flexible forecasting of specific target building energy consumption is achieved, which can provide optimization strategies for updating and adjusting architecture energy efficiency design. The experimental analysis benchmark parameters and the output value in the dataset are compared with the target simulation value. The relative error is less than 4%, and the average relative error value (mean) and the root mean square error (RMSE) value are both controlled within 2%. It is proved that the method in this paper can directly reflect the evaluation of energy consumption by the neural network and realize the high-speed conversion of the generalized model to the concrete goal, which has a certain value and research significance.

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With the continuous development of China's construction industry, China's demand for architectural professionals is increasing, which also promotes the great development of architectural education. In the practical teaching of architecture major in local universities, there are still some problems: classroom theory cannot be combined with practical courses, teaching mode is too single, teaching lacks flexibility and characteristics, teaching content lags behind, students have few opportunities to practice learning in society and enterprises, and their participation is not high. Through the reform and practice of practical teaching system, the characteristic architecture education of independent colleges is developed to improve the practical and hands-on design ability of architecture students.