Abstract

This research focuses on the analytic hierarchy model in the decision-making system that has a more complex structure and maintains the stability of the system, models the application process with the complexity and diversity of the rural economy, collects sample data with the help of different types of rural tourism questionnaire surveys, and integrates the data of rural tourism and other tourism into the model. The following are obtained: (1) During the level analysis, each phenotype track uses RRM, C 1 = 0.26 , C 2 = 0.223 , C 3 = 0.52 , C 4 = 0.25 , C 5 = 0.833 , C 6 = 0.442 , C 7 = 0.75 , C 8 = 0.127 , C 9 = 0.876 , C 10 = 0.792 , C 11 = 0.049 , C 12 = 0.16 , C 13 = 0.166 , and C 14 = 0.049 . The problems of the complex structure of the evaluation can be divided into simple analysis modules, and each module is analyzed at a level. The phenotypic trajectory of each individual is divided into target layer, standard layer, and scheme layer. (2) Arrangement and decision modeling were performed according to one or several indicators of different factors. In the hierarchical random regression model, APC = 0.214 , UPUA = 0.042 , TO = 0.081 , YPUA = 0.082 , PCP = 0.068 , and APS = 0.067 . The characteristic quantity analysis of different environments can be carried out, and the amplitude error and frequency error obtained are relatively small. IAND = 0.115 , AVA = 0.198 , RD = 0.119 , PI = 0.041 , PCCL = 0.142 , IOC = 0.201 , and DSTC = 0.069 . The comparison shows that the hierarchical analysis model is better than the hierarchical random regression model. (3) High-efficiency hybrid model correlation acceleration is the worst model. The experimental data are APC = 0.147 , UPUA = 0.029 , TO = 0.055 , YPUA = 0.06 , PCP = 0.047 , APS = 0.046 , IAND = 0.079 , AVA = 0.136 , RD = 0.082 , PI = 0.028 , PCCL = 0.098 , IOC = 0.139 , and DSTC = 0.048 . (4) The predicted 2020 data and the actual data have small errors. The data obtained by the AHP model is GDP = 1262.1 , finance = 185.09 , budget = 68 , tax = 51.92 , fund budget = 69.23 , transfer income = 40.14 , debt income = 7.73 , disposable financial power = 177.37 , fiscal expenditure = 191.26 , public budget = 88.68 , government expenditure = 71.39 , transfer expenditure = 23.46 , debt expenditure = 7.73 , and last year balance = 2.39 .

Highlights

  • The analytic hierarchy model is proposed on the basis of operation research

  • The problems of the complex structure of the evaluation can be divided into simple analysis modules, and each module is analyzed at a level

  • The phenotypic trajectory of each individual is divided into target layer, standard layer, and scheme layer

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Summary

Introduction

The analytic hierarchy model is proposed on the basis of operation research It is suitable for decision-making systems with complex structures and maintaining system stability. In the process of tracing the current of the research problem, the decision criterion distance between the points of the analytic hierarchy process is used as the reference quantity of the experimental model. The analytic hierarchy model can track the power flow, using the multiple linear regression trajectory distance between the nodes as the reference quantity, clustering the nodes. Compared with the existing RRM-based bending distance analysis, the regression marker can perform multiple linear regressions on the rocking curve data meter of each motor calculated by the software time domain fault simulation. Performing dimensionality reduction test processing on the Hi-RRM modeling data first can significantly reduce the complexity of repeated measurements. This study uses the analytic hierarchy process, focusing on the decision-making system that the analytic hierarchy model has a more complex structure and maintains the stability of the system, models the application process with the complexity and diversity of the rural economy, collects sample data with the help of different types of rural tourism questionnaire surveys, and integrates rural tourism and other tourism data into the model

Scenario Analysis Process Method
Indicator System
Advantages of Rural Tourism
C11 C12 C13 C14
Development Trend
Weight Indicators
Model Comparison
Rural Tourism Management Strategy
Simulation Experiment and Prediction
Conclusion
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