scholarly journals Comprehensive Evaluation of Tourism Resources Based on Multispecies Evolutionary Genetic Algorithm-Enabled Neural Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Xinglong Kan ◽  
Lin Li
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Influencing Factors ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Analysis And Evaluation ◽  
The Neural Network ◽  
Comprehensive Evaluation Model ◽  
Evolutionary Genetic ◽  
Tourism Resources

With the development of neural network technology and the rapid growth of China’s tourism economic income at this stage, the research on the comprehensive evaluation of tourism resources has gradually emerged. Based on this, this paper studies the neural network comprehensive evaluation model based on multispecies evolutionary genetic algorithm and designs the neural network analysis system of influencing factors of tourism resources based on multispecies evolutionary genetic algorithm. The collection and acquisition of data information are realized from the aspects of resource income status, tourism development investment, and sustainability evaluation in the tourism area. The multispecies evolutionary genetic algorithm is used for comprehensive analysis and evaluation. The algorithm can realize the complex analysis and comprehensive evaluation of the core influencing factors of neural network. Accurate analysis and evaluation were carried out according to the different characteristics of tourism resources and the current situation of tourism income. The results show that the neural network comprehensive evaluation model based on multispecies evolutionary genetic algorithm has the advantages of high practicability, good sorting effect of variable ratio, and good data integration. It can effectively analyze and compare the comprehensive evaluation factors affecting tourism resources in different ratios.

scholarly journals Study on the Intelligent Evaluation System of Tunnel Frost Damage in Cold Regions Based on the Fuzzy Comprehensive Evaluation Model

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Dao-yuan Wang ◽  
Yong-quan Zhu ◽  
Guang-yao Cui ◽  
Yong-jun Luan ◽  
Hai-long Cui ◽  
...  
Keyword(s):  
Influencing Factors ◽  
Evaluation System ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Fuzzy Comprehensive Evaluation ◽  
Frost Damage ◽  
Cold Regions ◽  
Research Results ◽  
Comprehensive Evaluation Model ◽  
Tunnel Design

At present, the tunnel design specifications in China do not provide a clear and systematic intelligent evaluation system of tunnel frost damage in cold regions. Based on the research results of 122 seasonal frozen soil tunnels in high-latitude areas of China, four key influencing factors of geohydrology, temperature, surrounding rock, and engineering measures were determined, the intelligent fuzzy comprehensive evaluation model was established, the weights of all factors were considered, and the intelligent evaluation technology system of tunnel frost damage in cold areas had been put forward. Meanwhile, the rationality of the intelligent model was verified by a specific engineering case. The research suggests that the intelligent evaluation model of tunnel frost damage proposed in this paper can accurately describe the relationship of influencing factors of tunnel frost damage in cold areas, the weight of each influencing factor is calculated by using analytic hierarchy process, and the main risk sources of tunnel frost damage in cold areas are found out. The intelligent evaluation model is an efficient and practical method for Intelligent prediction of frost damage. By using the subordinate function method, the improvement from qualitative analysis to quantitative index calculation is realized. The blindness of engineering analogy construction is avoided, and the scientificity and accuracy of renovation measures for frost damage have been improved. At the same time, the research results provide a theoretical basis for the improvement of the intelligent evaluation system of tunnel frost damage in cold regions.

Application of Genetic BP Neural Network in Safety Comprehensive Evaluation of Tailing

2014 ◽  
Vol 687-691 ◽  
pp. 2402-2406
Author(s):  
Song Jiang ◽  
Hui Wen He ◽  
Hong Bo Liu ◽  
Kang Ting Lv
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Bp Neural Network ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Threshold Value ◽  
Generalization Ability ◽  
Learning Speed ◽  
Security Levels ◽  
Improved Accuracy

Based on safety assessment factors determined by operation characteristics of a certain tailing ,genetic BP neural network evaluation model is established. To overcome such problems of BP neural network as slow convergence ,poor generalization ability and easy to fall into local minimum value,this paper proposes to use genetic algorithm to optimize threshold value,weights and structure of neural network. Thus,by taking advantage of extensive mapping ability of neural network and global search ability of genetic algorithm,neural network and genetic algorithm will have complementary advantages and the learning speed of network will be accelerated. The application of the described method shows optimized fitting precision,improved accuracy and efficiency ,and enhanced generalization ability of BP neural network. In conclusion,this model can effectively reflect and accurately evaluate non-linear relations between security levels and evaluation factors in tailing.

Comprehensive Evaluation of Implementation Effect on Later-Period Supportive Policy of Reservoir Resettlement Based on ANFIS

2014 ◽  
Vol 912-914 ◽  
pp. 1874-1878 ◽  
Author(s):  
Xin Xu ◽  
Xiao Yi Wang ◽  
Zhao Yang Wang ◽  
Yu Hang Long ◽  
Suo Jun Xu
Keyword(s):  
Neural Network ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Evaluation Process ◽  
Evaluation Index System ◽  
Evaluation Index ◽  
Nonlinear Characteristics ◽  
Comprehensive Evaluation Model ◽  
Implementation Effect ◽  
Reservoir Resettlement

According to engineering features of later-period supportive policy on reservoir resettlement, Economic evaluation index system of implementation effect on later-period supportive policy of reservoir resettlement is built to assess the implementation result of reservoir resettlement policy effectively in recent years. Considering the complexity of the evaluation index and the nonlinear characteristics of evaluation process, it is built that the comprehensive evaluation model of implementation effect on later-period supportive policy of reservoir resettlement based on ANFIS(Fuzzy artificial neural network) to provide the decision-making reference for implementation and improvement of later-period supportive policy of reservoir resettlement.

The Construction of Index System and Comprehensive Evaluation Model Based on Improved Genetic Algorithm and Fuzzy Neural Network

2010 ◽  
Vol 20-23 ◽  
pp. 1229-1235 ◽  
Author(s):  
Yuan Yuan Zhang ◽  
Shi Song Yang ◽  
Peng Dong
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Artificial Neural Network ◽  
Index System ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Back Propagation ◽  
Improved Genetic Algorithm ◽  
Artificial Neural ◽  
Artificial Neural Network Ann

Artificial neural network(ANN) and genetic algorithm (GA) have both prevalent uses in large area. Along with the development of technology a method based on the combination of Artificial neural network (ANN) and genetic algorithm (GA) aroused. In such a case, the paper uses the combination of Artificial neural network(ANN) and genetic algorithm (GA) to solve the problems of costructing index system and comprehensive evaluation. Firstly establishing feedforward neural network model and make sure about the input and output variables. Secondly improved genetic algorithm is used to solve the problem of network weight and threshold value which is constitute by three steps real codes, random selection and Genetic Manipulation of Chromosome. Moreover as it know to all, error back propagation(BP) algorithm is effective in local searching so adding error back propagation(BP) algorithm to genetic algorithm is a good way to get the satisfying result. Thirdly the paper gets the output of index effectiveness. Thirdly according to the entropy theory that the summation of effective value which could be involved in the index system should be larger than a certain critical value, the paper screened out the final index. Fourthly it uses the fuzzy neural network method to establishing the comprehensive evaluation model. Finally take the evaluation for teaching quality for example to authenticate the feasibility of the method.

Research on Vague Evaluation Based on Loader Cab Man-Machine Inferface

2011 ◽  
Vol 145 ◽  
pp. 510-514
Author(s):  
Jian Tao Lu ◽  
Yan Hui Zhu
Keyword(s):  
Optimal Design ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Fuzzy Mathematics ◽  
Analysis And Evaluation ◽  
Set Membership ◽  
Comprehensive Evaluation Model ◽  
Machine Interface ◽  
Multi Level ◽  
Man Machine Interface

In this paper, the application of fuzzy mathematics theory to the loader cab man-machine interface analysis and evaluation, preliminary built the interface multi level comprehensive evaluation model, using alternative score set membership function, through the evaluation model of certain type of loader cab man-machine interface for comprehensive evaluation, conducive to the realization of the loader driving human-machine interface optimal design target.

Intelligent Lighting Control System in Large-Scale Sports Competition Venues

2018 ◽  
pp. 172-182 ◽  
Author(s):  
Shengmin CAO
Keyword(s):  
Control System ◽  
Large Scale ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Fuzzy Comprehensive Evaluation ◽  
Practical Significance ◽  
Lighting Control ◽  
Sports Events ◽  
Planning And Design ◽  
Comprehensive Evaluation Model

This paper mainly studies the application of intelligent lighting control system in different sports events in large sports competition venues. We take the Xiantao Stadium, a large­scale sports competition venue in Zaozhuang City, Shandong Province as an example, to study its intelligent lighting control system. In this paper, the PID (proportion – integral – derivative) incremental control model and the Karatsuba multiplication model are used, and the intelligent lighting control system is designed and implemented by multi­level fuzzy comprehensive evaluation model. Finally, the paper evaluates the actual effect of the intelligent lighting control system. The research shows that the intelligent lighting control system designed in this paper can accurately control the lighting of different sports in large stadiums. The research in this paper has important practical significance for the planning and design of large­scale sports competition venues.

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