Technique For Order Preference By Similarity To An Ideal Solution Research Articles

Exploring the Toxicity of Oxytetracycline in Earthworms (Eisenia fetida) Based on the Integrated Biomarker Response Method

Antibiotic contamination has become a global environmental issue of widespread concern, among which oxytetracycline contamination is very severe. In this study, earthworm (Eisenia fetida) was exposed to oxytetracycline to study its impact on the soil environment. The total protein (TP), catalase (CAT), superoxide dismutase (SOD), peroxidase (POD), malondialdehyde (MDA), glutathione S-transferase (GST), and glutathione peroxidase (GPX) oxidative stress indicators in earthworms were measured, and the integrated biomarker response (IBR) approach was used to evaluate the toxic effect of oxytetracycline on earthworms. A Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and a path analysis model were used to explore the physiological and metabolic processes of earthworms after stress occurs. The results showed that SOD, GPX, and GST play important roles in resisting oxytetracycline stress. In addition, stress injury showed a good dose–effect relationship, and long-term stress from pollutants resulted in the most serious damage to the head tissue of earthworms. These results provide a theoretical basis for understanding the toxic effect of oxytetracycline on soil animals, monitoring the pollution status of oxytetracycline in soil, and conducting ecological security risk assessment.

A multi-criteria decision framework to evaluate sustainable alternatives for repurposing of abandoned or closed surface coal mines

Surface coal mines, when abandoned or closed, pose significant environmental and socioeconomic challenges. Repurposing these sites is crucial for sustainable land use and responsible resource management. This study presents a comprehensive decision framework tailored to the Indian mining context, utilizing a hybrid approach combining the analytic hierarchy process (AHP) and technique for order preference by similarity to an ideal solution (TOPSIS) methodology. The proposed framework assesses and ranks alternative repurposing options by considering a multi-criteria evaluation, including ecological, economic, social, and regulatory factors. AHP is employed to determine the relative importance of these criteria, reflecting the unique priorities and perspectives of stakeholders involved in the repurposing process. TOPSIS then identifies the optimal alternatives based on their overall performance against the established criteria. This hybrid methodology contributes to informed decision-making in the sustainable repurposing of abandoned surface coal mines in India. It aids in identifying the most viable and environmentally responsible alternatives, promoting efficient land use and resource conservation while addressing the challenges associated with abandoned mine sites. The methodology’s applicability extends globally to industries facing similar repurposing challenges, facilitating the transition toward a more sustainable and responsible land reclamation and resource management approach. The methodology is implemented using real mine data and demonstrates the analysis for evaluation among multiple alternatives such as solar parks, fish farming, eco-resorts, forestry, and museums. In our study, eco-resorts show more promise based on the significant potential for local economic development, provision of local employment, long-term revenue generation, potential for upskilling local youth in management, gardening, construction, and animal husbandry, and serving as a site for exhibitions of various arts and crafts.

A Fuzzy Ontology-Based Decision Tool for Concept Selection to Maintain Consistency Throughout Design Iterations

Abstract Concept selection is one of the most important activities in new product development processes in that it greatly influences the direction of subsequent design activities. As a complex multiple-criteria decision-making problem, it often requires iterations before reaching the final decision where each selection is based on previous selection results. Reusing key decision elements ensures decision consistency between iterations and improves decision efficiency. To support this reuse, this article proposes a fuzzy ontology-based decision tool for concept selection. It models the key decision elements and their relations in an ontological way and scores the concepts using weighted fuzzy TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution). By applying the tool to an example, this article demonstrates how the concepts, criteria, weights, and results generated for one decision can be reused in the next iteration.

Oil extraction desulfurization based on ionic liquid: Back-extractant screening, experiment and process simulation

A comprehensive back-extractant screening method was first developed for regenerating ionic liquids (ILs) after oil extraction desulfurization (EDS). Statistical analysis was performed using the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) with the Entropy Weighting Method (EWM) on screening indices obtained based on the COnductor-like Screening MOdel for Realistic Solvents (COSMO-RS) and the Quantitative Structure Activity Relationship (QSAR) models. CCl4 was selected as the optimal back-extractant among 196 candidates for regenerating the IL, 1-butyl-3-methylpyridinium dicyanamide ([BMPy][DCA]), targeting the simultaneous removal of thiophene (TS), benzothiophene (BT), dibenzothiophene (DBT), and 4,6-dimethyldibenzothiophene (4,6-DMDBT). The experimentally measured hexary liquid–liquid equilibrium (LLE) confirmed the satisfactory selectivities and distribution coefficients of CCl4. Based on the NRTL parameters correlated from the LLE data, a complete EDS process including IL-extraction and IL-regeneration was established and evaluated economically based on the total annual cost (TAC). The results demonstrated that this process significantly decreased the sulfur content from 500 ppm to less than 10 ppm. The study results verified the feasibility and effectiveness of the proposed method and showed the excellent industrial performance of the selected IL and back-extractant.

Driving factors and key paths of greenhouse gas and air pollutants synergistic control using hybrid multiple-criteria decision-making

Humanity has consumed a large amount of energy and resources to maintain the rapid development of the economy and society, causing greenhouse gas and air pollutants to rise continuously, generating enormous pressures for the sustainable development of many cities. It is economical to control greenhouse gas and air pollutants from the synergy perspective. To identify the key driving factors involved in synergistic control, this paper uses the pressure-state-response (PSR) model to design a performance evaluation model of greenhouse gas and air pollutants synergistic control (GASC) utilizing pressure, state, and response dimensions. The performance evaluation factor system of GASC comprises three primary aspects and 18 criteria. The analytic hierarchy process (AHP) was used to determine the weight of each factor in the evaluation system. The technique for order preference by similarity to an ideal solution (TOPSIS) method was used to calculate the ranking of the synergistic control effects of the four representative provinces in China. We use Importance-performance analysis (IPA) to analyze the performance of driving factors of synergistic control in the province with the lowest ranking from 2016 to 2020. The research shows that in Northeast China, represented by Liaoning province, the government’s response should include changing the support strategy for the new energy consumer, introducing synergistic control standards and policies, and making flexible adjustments to the supply chain. The research provides a scientific basis for the performance evaluation of GASC and decision-making support for lean response strategies.

Multi-objective optimal input design for grey-box identification modelling of ship manoeuvring motion

ABSTRACT Grey-box modelling has been widely used to predict the ship manoeuvring motion. In order to design input signals for the grey-box model of ship manoeuvring motion, a multi-objective optimal input design (MOID) method is proposed in this paper. In the proposed method, the MOID is regarded as a multi-objective optimization problem (MOP), where both of D-optimality criterion and condition number are taken as two-objective functions to improve the accuracy and robustness of identifying the grey-box model. The correlation factor is also presented as a constraint for reducing the parameter drift. The MOP is solved by the non-dominated sorting genetic algorithm-II (NSGA-II) with a constraint handling technique. The technique for order preference by similarity to an ideal solution (TOPSIS) is also adopted to screen out an optimal solution from the Pareto solutions. The effectiveness of MOID signals is validated by Monte Carlo analysis and grey-box identification of the MMG model.

Safety assessment of existing subgrade retaining wall based on a combined Weighting-TOPSIS evaluation method

The safety assessment of existing retaining walls is currently a potential research direction in developing built environment. However, current assessment results are generally carried out by a single evaluation method with poor applicability and operability. Thus, this paper proposed a comprehensive safety assessment model for existing subgrade retaining walls. The qualitative and quantitative indexes were summarized systematically and then were weighted by the entropy weight method (EWM), interval analytic hierarchy process (IAHP), and improved radial movement optimization (IRMO) algorithm. With these indexes weighted, the safety situation can be assessed by the technique for order preference by similarity to an ideal solution (TOPSIS) method. The proposed method was applied to five cases. The results show that the method reduces the subjective arbitrariness in weighting calculation, making the evaluation more objective and reasonable. The model improves the accuracy and applicability of the safety assessment of existing retaining walls.

Extreme analysis of typhoons disaster in mainland China with insurance management

Due to climate change, typhoons, especially extreme typhoons, are becoming more intense and causing ascending financial losses. A majority of previous studies on typhoon economic losses over a period of time considered all types of typhoon rather than the extreme typhoons. This study focuses on the risk management of extreme typhoons by establishing the compensation mechanism and a typhoon-specific insurance product. The annual maximum losses of typhoons is first modelled by generalized extreme value distribution (GEV) under the Extreme Value Theory (EVT). The prediction of unexpected economic losses is then obtained via VaR and CVaR for the compensation mechanism among individual, insurance company and government. To analyse the typhoon vulnerability of 11 Chinese coastal provinces (or municipalities), the Multiple-Criteria Decision Making (MCDM) method, combining Analytic Hierarchy Process (AHP) based Grey Rational Analysis (GRA) and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), is applied for evaluating the typhoon vulnerability of these regions for 2022. The nationwide best estimates for typhoon reserves on the basis of insurance compensation mechanism is therefore calculated and will be allocated to these 11 provinces according to the vulnerability ranking obtained via MCDM method. The findings indicate that the top three provinces (Guangdong, Fujian and Zhejiang) in typhoon vulnerability rankings are also with the highest losses and frequency in practice, while Hebei has the highest insurance premium.

Multi-Objective Optimization of Tasks Scheduling Problem for Overlapping Multiple Tower Cranes

The scheduling of tower crane operations is a complex process. Overlapping areas between tower cranes often lead to increased collision possibilities, resulting in additional tower crane operation complexity. Single objectives related to time or economic aspects were always considered in dealing with this issue, which neglected other objectives and the relationships between different objectives. Therefore, this article proposes a novel method for the schedule of prefabricated component lifting tasks on the construction site, integrating the multi-objective optimization model with the decision-making method with the aim of minimizing energy consumption costs and minimizing the amplitude of the costs among multiple tower cranes. A non-dominated sorting genetic algorithm-III (NSGA-III) written in Python is used as the multi-objective optimization algorithm—which considers the selection of tasks for each tower crane and the order of lifting for each tower crane and technique for order preference by similarity to an ideal solution (TOPSIS), and is applied as the decision-making method for ranking the Pareto front. Then, a green construction production and education integration training building construction project located in Jinan, China is used as the case study to verify that the method is practical and reasonable. The results show that conflicts can be effectively avoided, energy consumption costs reduced, and equipment utilization increased by rationally distributing lifting tasks among multiple overlapping tower cranes. And among the top 11 solutions, the lifting tasks and priorities for tower crane 1 are close to the same. In contrast, the task lifting for tower crane 2 was assigned based on the balance of the energy consumption costs of the two tower cranes. The discovery of this article is helpful to eliminate collisions, interference, and frequent start and stop of several tower cranes, so as to realize the safe, stable, and efficient operation of the construction site.

Evaluating the landfill leachate quality using leachate pollution index (LPI) and technique for order preference by similarity to an ideal solution (TOPSIS)

Variability and diversity of landfill leachate cause difficulties in assessing the actual degree of threat to the environment and selecting an appropriate method of disposal or treatment. Therefore, quantifying leachate contamination potential is essential in landfill management and could be used to assess the accuracy of landfill operation and its impact on surrounding areas. The aim of this paper was to evaluate the performance of the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method and its suitability in determining leachate pollution potential in comparison to the Leachate Pollution Index (LPI) method. For this purpose, the quality of leachate from the landfill, collected four times a year from 2004 to 2021, was analysed. The following parameters were monitored: pH, EC, Pb, Cu, Zn, Cr, and Hg. On the basis of the measured parameters, the LPI and TOPSIS indexes were calculated. The obtained results indicated that the TOPSIS method is more sensitive and accurate in observing changes in leachate quality. It can be applied to any number of contaminant parameters without restrictions on scope, quantity, or their relative importance. It can also be used to compare the variations in leachate quality over time or to analyse differences in leachate quality among various landfill sites.

Effects of Nutrient Solution Application Rates on Yield, Quality, and Water-Fertilizer Use Efficiency on Greenhouse Tomatoes Using Grown-in Coir.

The yield, quality, and water-fertilizer use efficiency of crops are important parameters for assessing rational water and fertilizer management. For an optimal water and fertilizer system with respect to the nutrient solution irrigation of greenhouse tomatoes using cultivation substrates, a two-year greenhouse cultivation experiment was conducted from 2022 to 2023. Three drip fertigation treatments (T1, T2, and T3) were implemented in the experiment, where nutrient solutions were supplied when the substrate's water content reached 60%, 70%, and 80%. The frequency of nutrient solution applications is based on weighing coconut coir strips in the morning and evening at 7:00 to determine the daily water consumption of plants. Nutrient solutions were supplied when the substrate's water content reached the lower limit, and the upper limit for nutrient supply was set at 100% of the substrate water content. The nutrient solution application was carried out multiple times throughout the day, avoiding the midday heat. The nutrient solution formula used was the soilless tomato cultivation formula from South China Agricultural University. The results show that plant height and the leaf area index rapidly increased in the early and middle stages, and later growth tended to stabilize; the daily transpiration of tomatoes increased with an increase in nutrient solution supply, and it was the greatest in the T3 treatment. Between the amount of nutrient solution application and the number of years, the yield increased with the increase of the amount of nutrient solution, showing T3 > T2 > T1. Although the average yield of the T2 treatment was slightly lower than that of the T3 treatment by 3.65%, the average irrigation water use efficiency, water use efficiency, and partial fertilizer productivity of the T2 treatment were significantly higher than those of the T3 treatment by 29.10%, 19.99%, and 28.89%, respectively (p < 0.05). Additionally, soluble solid, vitamin C, and soluble sugar contents and the sugar-acid ratio of tomatoes in the T2 treatment were greater than those in the other two treatments (p < 0.05). Using the TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method, it was concluded that the nutrient solution application rate of 70% can significantly increase water and fertilizer use efficiency and markedly improve the nutritional and flavor quality of the fruit without a significant reduction in yield. This finding provides significant guidance for the high-yield, high-quality, and efficient production of coconut coir-based cultivated tomatoes in greenhouses.

A novel approach to hazard evaluation for MASS operation based on a hesitant fuzzy linguistic term set

Expert judgment has been widely utilized in ship risk assessment. The traditional method is believed to be capable of processing only designated linguistic variables, which fails to capture the degree of expert hesitation in assessing a complex system. A novel model, the bi-independent hesitant fuzzy linguistic term set (BHFLTS), based on the hesitant fuzzy linguistic term set (HFLTS), is proposed to incorporate this hesitation. This paper also identifies ten navigational hazards to maritime autonomous surface ship (MASS) operation based on a literature review. In addition, the BHFLTS approach combined with the technique for order preference by similarity to an ideal solution (TOPSIS) is utilized for hazard assessment and ranking, and with this method, “Collision avoidance decision algorithm malfunction”, “Ship situation awareness system failure” and “Command transmission system failure” are rated as the top three navigational hazards that threaten MASS operation.

The multi-objective optimization and mix parameter evaluation of one-part alkali-activated grouting material

To obtain a green and cost-effective one-part alkali-activated grouting material (OAGM) with good comprehensive performance for subgrade reinforcement and determine its proper mix parameters. In this study, using response surface methodology (RSM), multiple objective particle swarm optimization (MOPSO) algorithm and the technique for order preference by similarity to an ideal solution (TOPSIS) algorithm coupled with entropy weight method, two multi-objective optimization schemes for OAGM were performed, one only considering performance and another considering performance, embodied CO2 emission (ECO2e) and cost. Then, the correlation-based feature selection (CFS) algorithm was used to evaluate the importance of various molar ratios as mix parameters on the performance of OAGM. Finally, the effects of key mix parameters on the microstructure and reaction products of OAGM were studied. RSM results show that W/S (water to solid) ratio, borax (BR) content and UCG content chiefly govern the flowability, initial setting time and mechanical strength of OAGM respectively, and the interactions between some factors also significantly affect these properties. MOPSO and entropy-TOPSIS algorithm can be used to optimize OAGM objectively. Two optimal OAGM pastes both have better comprehensive performance and much lower ECO2e than ordinary Portland cement (OPC) paste. And the optimal OAGM considering performance, ECO2e and cost even has 7.68% lower cost than OPC paste. But another optimal OAGM has the best comprehensive performance. CFS results show that the molar ratios of Si/Al, Al/Ca, Na2O/H2O, B2O3/CaO and B2O3/Al2O3 are the key mix parameters of OAGM. Al/Ca rather than Si/Al is the most important mix parameter to the 28-day compressive strength. And higher Si/Al and Al/Ca deteriorates the microstructure and hinders the formation of C-A-S-H gel, while higher Na2O/H2O has the opposite effect. This study provides guidance for objective optimization and the determination of proper mix parameters of OAGM, and promotes the market-oriented application of OAGM.

Risk management of green supply chains for agricultural products based on social network evaluation framework

AbstractThe green supply chain of agricultural products (GSCAP) is a key link for rural revitalization and sustainable development in China. However, it faces various risks from internal and external environments that threaten its performance and stability. This paper proposes a novel framework and system for identifying and evaluating the main risks in the GSCAP from the perspective of agricultural enterprises. The framework combines social network analysis (SNA) and an improved technique for order preference by similarity to an ideal solution (TOPSIS) method. SNA is used to analyze the correlations and influences among different types of risks, while the improved TOPSIS method is used to rank the risks of different GSCAPs and identify the key risks in each supply chain. The framework and system are verified by a case study of CDYBIT, a leading platform of food safety big data service in China. The results show that the supermarket supply chain has the highest risk, followed by the group catering supply chain, and the five‐star hotel supply chain has the lowest risk. The main risk factors for each supply chain are also discussed, and some suggestions for risk management are provided. This paper contributes to the literature by providing a comprehensive and systematic risk assessment framework and system for the GSCAP, which can help agricultural enterprises improve their risk awareness and response capabilities.

Improvements of performance and emission characteristics of a diesel engine fueled with diesel/PODE3/n-butanol blended fuels by RSM-NSGA III in plateau environment

In order to reduce the pollutant emission and improve the performance characteristics, the RSM-NSGA III-TOPSIS optimization method was used to optimize a diesel engine fueled with different diesel/PODE3/n-butanol blended fuels in plateau environment. Firstly, a numerical model was developed and verified by the experimental results. An improved chemical reaction mechanism containing 164 species and 643 reactions was then employed to predict the combustion process. Secondly, a numerical model of the target parameters was obtained by using the Response Surface Method (RSM). Then, the mathematical model was optimized by Non-Dominated Sorting Genetic Algorithm III (NSGA III). Finally, the optimal solution was selected by Entropy Weight Method (EWM) and Technique for order preference by similarity to an ideal solution (TOPSIS). The optimized results showed a 5.14% improvement in BTE, a 52.12% decrease in soot, and a 20.6% improvement in BSFC compared with the original results at 2000 m. The optimized results showed a 11.9% improvement in BTE, a 37.7% decrease in soot, and a 0.5% improvement in BSFC compared with the original results at 4000 m. The results showed that the optimal solutions were different for different altitudes. Therefore, it is necessary to optimize the CI engine specifically for different altitudes.

Risk analysis and assessment of water resource carrying capacity based on weighted gray model with improved entropy weighting method in the central plains region of China

The issue of global water shortage is a serious concern. The scientific evaluation of water resource carrying capacity (WRCC) serves as the foundation for implementing measures to protect water resources. In addition, most of the studies are based on the analysis and research of regional WRCC from the aspects of water quantity and water quality. There are few studies on the four aspects of water resources endowment conditions, society, economy and ecological environment, which is difficult to scientifically and accurately reflect the analysis and evaluation of regional WRCC by the four systems. Therefore, it is necessary to conduct a deeper discussion and Analysis on this topic. This study presents a WRCC index system and corresponding ranking criteria based on 20 influencing factors from four aspects: water resources endowment (WRE), economy, society, and ecological environment. In addition, by combining the improved entropy weighting method (EWM) with gray correlation analysis, the weighted gray technique for order preference by similarity to an ideal solution (TOPSIS) model is proposed for analyzing and assessing WRCC risk. Finally, the WRCC of the study area from 2012 to 2021 is comprehensively evaluated in the central plains region of China (CPROC) as an example. The results show that the comprehensive evaluation obtained a multi-year average value of 0.2935, and the water resources shortage in the CPROC is generally in grade III status. The comprehensive average value of Beijing is 0.345, and the comprehensive average value of Henan is 0.397. The overall degree of water resources shortage is in the state of grade V shortage, Shaanxi is in the state of grade IV shortage, and the degree of water resources in Tianjin and Shanxi is relatively good. This study provides corresponding scientific basis and methodological guidance for the sustainable utilization of water resources and healthy socio-economic performance in the CPROC.

Regional differences in health resource allocation: a longitudinal study in the Chengdu-Chongqing economic circle, China

ObjectiveTo analyse regional differences in health resource allocation in the Chengdu-Chongqing economic circle.DesignA longitudinal analysis that collected data on health resource allocation from 2017 to 2021.SettingThe number of beds, health...

Design and investigation of novel gradient flow fields for proton exchange membrane fuel cell

Ensuring sufficient gas supply and high distribution uniformity are crucial issues in the flow field design to improve the performance and durability of proton exchange membrane fuel cell (PEMFC). However, previous studies often ignore the gas-water distribution variations along the flow direction and adopt identical design for the entire flow field, resulting in unsatisfactory performance. To fill in this gap, this paper innovatively proposes two types of gradient flow field (gradient narrowing and gradient droplet) considering the gas-water distribution characteristics. The channel of the gradient narrowing flow field gradually decreases in all directions along the flow direction, and the gradient droplet flow field is composed of staggered droplet blocks, and the distribution density gradually decreases along the flow direction. The Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method is used for the comprehensive evaluation of flow fields. The results demonstrate that the gradient flow field can significantly improve the performance and physical field distribution. The gradient narrowing flow field has the best performance, with 11.39 % improvement in peak power density, 77.96 % increment in average oxygen mass fraction, and 43.11 % improvement in oxygen uniformity compared to parallel flow field. Further, the key geometric parameters sensitivity analysis of gradient narrowing flow field is carried out. This study contributes to understanding the underlying mechanism of mass transfer properties in the novel gradient flow field, and exploring its potential for high-performance flow fields design.

Rest Grazing from the Critical Period of Soil Thawing in Alpine Meadow of Tibetan Plateau Is Conducive to the Sexual Reproduction of Polygonum viviparum

(1) Background: The most important management measure and utilization method for grassland is grazing. The suitable beginning period of spring rest grazing in the alpine meadow was selected to provide a theoretical basis for more scientific management and sustainable utilization. The experimental site is located in the cold-season pasture of an alpine meadow, which is located in the eastern part of the Qinghai Tibet Plateau. (2) Methods: We set up five treatments with the critical soil thawing period, the late soil thawing period, the grass reviving early period, the grass reviving late period with local traditional rest grazing period as the start time of rest grazing, and the grass withering period as the end time of rest grazing, recorded as P1, P2, P3, P4, and P5 (CK, control check). We studied the reproductive characteristics of the dominant plant, Polygonum viviparum, during different rest grazing periods. (3) Results: The results showed that, in general, P. viviparum was mainly involved in asexual reproduction and tended to have sexual reproduction with the rest of the grazing in advance. The biomass proportion of sexual reproduction organs and asexual reproduction organs in P1 were higher than those of other treatments, which were 704% and 20% higher than P5 (CK), respectively. The seed yields of P1 were 135%, 535%, 690%, and 1269% higher than P2–P5, respectively. The indices of P. viviparum seed quality in P5 were lower than those of the other treatments. The seed length, seed size, seed setting rate, and satiety grain weight ratio of P1 were higher than those of other treatments. We use the TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) analysis method to comprehensively evaluate the indicators of the five plots. (4) Conclusions: It was concluded that the rest of the grazing from the critical period of soil thawing was conducive to the growth and sexual (seed) reproduction of P. viviparum. Therefore, the resting grazing period of alpine meadows in spring should start with the critical period of soil thawing.

Dynamic evolution and obstacle factor analysis of green development in China's agriculture and rural areas based on entropy-based TOPSIS model

Green development of agriculture and rural areas (GDARA) is an essential part of rural revitalization and high-quality development. Based on 2011 to 2020 provincial panel data from China, the entropy-based Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) model is constructed to measure the level of GDARA, finding that the overall level during the sample period was positive. Then the regional differences mainly from intra-regional were revealed by the methods of Dagum Gini coefficient and Kernel density estimation and were shrinking overall. Besides, the results of Markov chain transfer matrix show the dynamic characteristics clearly, which the low-level regions shift to the middle and high levels with a greater probability. The results of the spatial autocorrelation test display that GDARA has a spatial clustering effect. Finally, the industrial upgrading and the business income of leisure agriculture are respectively proven to hinder GDARA at most by the Obstacle degree model empirically. Based on a series of empirical tests, a few relevant policy recommendations are proposed to promote the road to strong agriculture and rural areas in China.