Anaerobic biological treatment of wastewater is an important technology in environmental engineering and energy engineering, and it is one of the methods for powerful treatment of highly concentrated organic wastewater. The study was conducted to design an optimal control strategy based on the anaerobic digestion model ADM1. Taking the maximisation of total gas production as the control objective, the Composite Intelligent Optimised Extreme Value Control Algorithm (CIOEC) was designed by combining the extreme value search control method with the model-free optimisation algorithm. The effectiveness of the proposed algorithm is verified by a combination of simulation tests and empirical analyses, and the CIOEC algorithm can maintain fast convergence and relative stability under both stable and changing input materials, and obtain the highest real-time gas production. Among them, the average daily gas production of the ADM1 system with the addition of the CIOEC algorithm can reach 873.9 mL, which is an increase of 124.3% compared with the original system. It shows that the algorithm proposed in this paper can enhance the total gas production and optimise the treatment effect in performing anaerobic digestion of high concentration organic wastewater.

Due to the continuous increase of housing prices in recent years, many special groups of low and middle income do not have enough financial ability to pay for the high housing prices, and the problem of living environment is becoming more and more prominent. Based on the utility function in economic theory, this paper constructs a utility function model under the constraints of household budget income and price, and determines the income line of housing security households. The distributional efficiency of the implementation of the guaranteed housing policy is estimated through both in-kind rent allocation and rent subsidy. Based on the empirical distribution characteristics and public opinion surveys, a rational distribution model for the current stage of sheltered housing is proposed. Taking Singapore’s guaranteed housing policy as a case study, combining empirical evidence and simulation experiments, the effect of improving the living environment of special needs groups under the framework of social security is explored. The results show that: using a 10% allocation ratio of subsidised housing (5% each for affordable housing and public rental housing), the vacancy rate of public rental housing shows an oscillating state in the period of 7~16. In the period from 16 to 20, it shows a gradual increase. Therefore, this guaranteed housing policy should be gradually adjusted or cancelled around period 16.

In order to improve the efficiency of agricultural irrigation industry and ensure the economy and environmental protection in the production process. The study proposes an agricultural water-saving irrigation path optimisation method based on the NGSA-III algorithm, and establishes a multiobjective water-saving optimal allocation model for the agricultural water source irrigation system. The NGSA-III algorithm is used to obtain the optimal solution of the model and achieve the path optimisation of agricultural water-saving irrigation resources. The results show that the running time of the article method to get the optimal path result is 0.31s, which can improve the economic and environmental benefits of the agricultural irrigation industry, the model in this paper can achieve the effect of smaller environmental objectives when the economic objectives are larger, and three solutions are selected to trade-off the analysis of economic and environmental objectives. Among the three different optimal solutions, the decision maker can choose the decision scheme according to the actual situation, which provides reference for agricultural water saving path planning.

With the development of big data, cloud computing and 5G digital technology, smart finance has emerged. The use of modern information technology to create a smart financial management system to transform and upgrade the original financial management system of the hospital has become an indispensable part of the effective operation and management of public hospitals. The article focuses on the current problems in the development of smart finance in public hospitals, plans the smart finance space from the front, middle and back office, and proposes a financial resource allocation mechanism from the perspective of smart finance. In the performance evaluation analysis of smart financial construction, the weights of the professional level of accounting personnel, financial accounting, comprehensive budget management situation, medical revenue management, outpatient satisfaction, and the standardisation of data sets are 0.1067, 0.0857, 0.0670, 0.0630, 0.0512, and 0.0476 in that order. The weights of cultivating human resources, consolidating the hospital’s financial foundation work, strengthening comprehensive budget management, promoting data standardisation and enhancing patient satisfaction are important ways to promote the development of smart financial construction in hospitals. The purpose of this paper is to provide reference and reference for the financial revenue management of public hospitals, to help hospitals optimise the management process, to improve the quality of service and to ensure financial security.

Underground cable tunnels are important infrastructures to maintain the normal operation of cities, and problems such as cable insulation aging and discharge can easily cause fires or even explosions, so the requirements for maintenance are high. In this study, the DGPS positioning method is used to optimise the positioning system of the intelligent inspection robot for underground cable tunnels, and the LQR controller is used to realise the deviation correction of angle and position in the motion path of the intelligent inspection robot. Then the inspection robot and UHF sensor are used to detect and accurately locate the defects in the cable tunnel, and finally the deviation correction and defect detection methods are integrated to design an intelligent management system for underground cable tunnels. The results of simulation experiments and field surveys show that the proposed method can correct the deviation of the robot in the inspection process in a timely manner, avoiding the problems of hitting the obstacles and the path around the long distance, and the average time consumed in the simulation map scenario is only 6.89 s. The communication scheme of the intelligent management system is practicable, and it can effectively detect and identify the defects and the specific location of the defects in the underground cable tunnels. The system proposed in this paper is able to detect defects and faults in time in practical applications, providing a new solution for the inspection of underground cable tunnels.

In this paper, the development of blast and shock engineering technology problems using linear algebra’s measure analysis is used to make expected judgements through the performance of the data. The problem can be simplified and the frequency stability of the communication transmission system can be optimised by using the data as a benchmark through linear transformations, eigenvectors, matrices and other arithmetic methods. Regularisation and quantisation process the image to improve the science and accuracy of large-scale image restoration algorithm operation. It has been shown that the optimised prediction formula is very consistent with the experimental results in blasting experiments with a building as the object of study. The frequency drift of the optimised laser is reduced from 850 MHz to 160 MHz. the acquired noise intensity is optimal at different communication transmission moments, and the highest noise intensity acquired at frequency is 0.097 dB. The stability is optimal at different times of communication signal switching. The regularisation optimised ship navigation images have the largest values of structural similarity and information entropy metrics.

With the deep development of digital transformation, the field of environmental art design is experiencing unprecedented changes. In this study, under the 3D scene reconstruction algorithm, the feature points of environmental art design images are collected and extracted using the camera selfcalibration algorithm, and the shape and topology of the point cloud dataset interpolated surfaces are explored using the triangular meshing algorithm. The rotation matrix is obtained by optimising the internal and external parameters of the camera using the essential matrix, basis matrix and Kruppa’s equation to clarify its effect on the efficiency of digital feature extraction of images in the process of environmental art design. The results show that the mesh surfaces constructed by the algorithm proposed in this paper make better use of the point cloud data when the number of cloud points input for environmental art design is the same. The rotation matrix algorithm used in this paper can increase the correct matching point pairs of the data, reduce the false matching point pairs, reduce the false matching rate, reduce the matching time, and eliminate more false matching points. And the triangular grid formed by this method is more uniform, and the quality of the grid is improved. In addition, the average satisfaction ratings of the subjects on the nine secondary test indicators are 4.45, 4.95, 4.75, 4.18, 4.70, 4.60, 4.44, 4.50 and 4.40, respectively. It can be seen that the effect of the application of the digital transformation of the 3D model proposed in this paper has been affirmed.

Shallow loess landslides, as one of the widely distributed and high-frequency geologic hazards, have brought great economic losses and ecological damage to human society. In this study, Qinzhou District, Tianshui City, Gansu Province, is taken as the study area, and the Scoops3D model is used to predict the occurrence of loess landslides in the area based on the DEM data of the area. Bishop’s simplified method and box search method were used to calculate and analyze the landslide stability in the study area. The landslide prediction results of the Scoops3D model of this paper are compared and analyzed under different DEM data resolutions. Subsequently, local environmental data are collected to study the correlation between environmental impact factors and shallow loess landslides. Finally, the prediction accuracy of the shallow loess landslide prediction model based on Scoops3D in this paper is tested by comparing the difference between the prediction results of the Scoops3D model of this paper and other prediction models with the actual results. The resolution of the DEM data has an important influence on the prediction results of the Scoops3D model, and the accuracy of the high-resolution DEM prediction results is higher than that of the low-resolution prediction results. There is a significant correlation between landslide displacement and humidity and cumulative precipitation, and the difference between the predicted and measured values of the GA-BP and GA-Elman models is within 8 mm, and the difference gradually increases. The difference between the predicted and measured values of the Scoops3D model in this paper is between 0.00 and 2.30 mm, and the prediction effect is optimal.

The inheritance and protection of urban cultural heritage faces the dilemma of narrow coverage and lack of change in form, and to solve this dilemma, we need to find a breakthrough in cultural creation and animation design, and carry out creative activities and popularisation among all people. The article proposes a feature extraction model that integrates multi-scale features and housing element information mining, and applies it to the feature extraction of housing elements in urban cultural heritage. A hybrid attention module is embedded in the ResNet-18 backbone network to enhance housing element features and suppress redundant information, and a CEB module and learnable parameters are combined to filter out the background information of the low-level features, so as to obtain finer architectural housing element features. The extracted housing elements are used as the basis for the design of creative products and animation scenes, and the feasibility of the programme is investigated through questionnaires. The overall evaluation mean value of the research respondents on the design of cultural and creative products for the housing was 7.64 points, and more than 95% of the evaluation respondents indicated that the housing elements were more suitable for the animation scene design. Relying on modern technology to extract housing elements from urban cultural heritage and realising the innovative application of cultural heritage in the form of cultural creation and animation provides a new path for the revitalisation and inheritance of urban cultural heritage.

According to the connotation of traditional and modern design elements in rural landscape beautification, multi-dimensional data cube mining method is adopted to construct the research data set of this paper. According to the ratio of 2:8, the data set is divided into test set and training set. The data of traditional and modern design elements are used as inputs, substituted into the decision tree model for training and classification, and the CART algorithm is used to construct a decision tree model for traditional and modern design elements in rural landscape beautification. Combining the dataset and the model in this paper, the simulation analysis of traditional and modern design elements in rural landscape beautification is carried out. The data show that based on the Gini index calculation formula of CART algorithm, it is concluded that the Gini index of X9 (0.9581) is the largest, so X9 is chosen as the root node for decision making, and the decision tree is derived downward until the leaf node, and the decision tree oriented to the countryside landscaping is obtained, and the rural landscape beautification scheme is induced based on the results of the analysis and the effect of the rural landscaping is found to have the difference between the before and after mean values of 3.36 ( 20.11-16.75=3.36), while there is a significant difference between the two, similarly, there is also a significant difference in the building living comfort above. This study enhances the effect of rural landscape beautification, which is of great significance in promoting rural revitalisation and architectural design development.