scholarly journals Cement pavement performance evaluation based on the discrete Hopfield neural network

2019 ◽  
Vol 136 ◽  
pp. 04069
Author(s):  
Huan Liu ◽  
Peng Liu ◽  
Qiuyu Peng
Keyword(s):  
Neural Network ◽  
Performance Evaluation ◽  
Evaluation Method ◽  
Functional Performance ◽  
Hopfield Neural Network ◽  
Evaluation Index ◽  
Pavement Performance ◽  
Index Matrix ◽  
Performance Evaluation Index ◽  
Grading Standards

Because of the deficiency of the index of cement pavement performance evaluation and the defect of the evaluation method in the specification, the performance of the pavement is comprehensively evaluated by seven optimized indexes and grading standards that reflect functional performance and structure of the pavement. Because the discrete Hopfield neural network is available with simple construction procedure, less training samples, and strong objectivity.The DHNN is constructed by MATLAB to evaluate the performance of test pavement. The ideal cement pavement performance grading evaluation index matrix and 6 places unclassified of test pavement performance evaluation index matrix are input to the neural network then the evaluation result is obtained after simulating and learning. Finally, comparing the result of the DHNN with the fuzzy complex matter element method and the nonlinear fuzzy method, it is proved that the discrete Hopfield neural network evaluation method is reliable.

Analysis of Performance Evaluation Index for bridge group networking monitoring and collaborative supervision

2021 ◽  
Author(s):  
Liye Zhang ◽  
Yong He ◽  
Shoushan Cheng ◽  
Guoliang Wang ◽  
Hongwei Ren ◽  
...  
Keyword(s):  
Performance Evaluation ◽  
Evaluation Method ◽  
Field Testing ◽  
Technical Condition ◽  
Evaluation Index ◽  
Technical Problems ◽  
Condition Evaluation ◽  
Bridge Group ◽  
Performance Evaluation Index ◽  
And Performance

<p>With the number of bridges increases, the bridge health monitoring (BHM) technique is developing from single bridge monitoring to collaborative supervision of bridge group. Therefore, there are many technical problems need to be solved especially the performance evaluation index for bridge group network. This paper analyses the performance evaluation index of the bridges and bridge group network, establishes the performance evaluation index for bridge group based on rating factor (RF) and technical condition evaluation index. Based on bridge field testing and monitoring data, bridge technical condition evaluation index and performance evaluation method for bridge group are proposed. A case study demonstrates that the research results provide support for bridge group networking monitoring and collaborative supervision.</p>

Performance evaluation of enterprises’ innovation capacity based on fuzzy system model and convolutional neural network

2020 ◽  
Vol 39 (2) ◽  
pp. 1563-1571
Author(s):  
Abuduaini Abudureheman ◽  
Aishanjiang Nilupaer ◽  
Yi He
Keyword(s):  
Neural Network ◽  
Performance Evaluation ◽  
Convolutional Neural Network ◽  
Fuzzy System ◽  
Evaluation Method ◽  
Innovation Performance ◽  
System Model ◽  
Innovation Capacity ◽  
Performance Evaluation Index ◽  
Breakthrough Innovation

Influenced by national policies and macro-economic environment, large domestic enterprises is actively promoting strategic transformation to enhance their core competitiveness, and performance evaluation of enterprises’ innovation capacity has become a hot topic in recent years. This paper proposes a performance evaluation method of enterprises’ innovation capacity based on deep learning fuzzy system model and convolutional neural network analysis of innovation network. First of all, on account of the characteristics of breakthrough innovation and drawing on the traditional innovation performance evaluation model, this paper constructs a breakthrough innovation performance evaluation index system for enterprises from the six dimensions of main resource input, technology out-turn, process management, product performance, social value and commercial Value. Secondly, the introduction of machine learning of fuzzy convolutional neural network to assess the advancement execution of enterprises is of great significance for enterprise managers to find out the problems and causes of enterprises’ innovation, optimize the allocation of enterprises’ resources and further improve the innovation performance of enterprises. The experimental results show to verify the adequacy of the algorithm.

scholarly journals Scheduling Performance Evaluation of Logistics Service Supply Chain Based on the Dynamic Index Weight

2014 ◽  
Vol 2014 ◽  
pp. 1-14
Author(s):  
Weihua Liu ◽  
Zhicheng Liang ◽  
Shuqing Wang ◽  
Yang Liu ◽  
Wenchen Xie
Keyword(s):  
Supply Chain ◽  
Performance Evaluation ◽  
Evaluation Method ◽  
Evaluation Index ◽  
Logistics Service ◽  
Service Supply Chain ◽  
Dynamic Index ◽  
Performance Evaluation Index ◽  
Performance Evaluation Method ◽  
Index Weight

Scheduling is crucial to the operation of logistics service supply chain (LSSC), so scientific performance evaluation method is required to evaluate the scheduling performance. Different from general project performance evaluation, scheduling activities are usually continuous and multiperiod. Therefore, the weight of scheduling performance evaluation index is not unchanged, but dynamically varied. In this paper, the factors that influence the scheduling performance are analyzed in three levels which are strategic environment, operating process, and scheduling results. Based on these three levels, the scheduling performance evaluation index system of LSSC is established. In all, a new performance evaluation method proposed based on dynamic index weight will have three innovation points. Firstly, a multiphase dynamic interaction method is introduced to improve the quality of quantification. Secondly, due to the large quantity of second-level indexes and the requirements of dynamic weight adjustment, the maximum attribute deviation method is introduced to determine weight of second-level indexes, which can remove the uncertainty of subjective factors. Thirdly, an adjustment coefficient method based on set-valued statistics is introduced to determine the first-level indexes weight. In the end, an application example from a logistics company in China is given to illustrate the effectiveness of the proposed method.

Asphalt Pavement Performance Evaluation Based on SOM Neural Network

2012 ◽  
Vol 188 ◽  
pp. 219-225
Author(s):  
Man Jiang Hu ◽  
Ru Hai Ge ◽  
Qi Feng Qiu ◽  
Qiao Jin
Keyword(s):  
Neural Network ◽  
Performance Evaluation ◽  
Evaluation Method ◽  
Asphalt Pavement ◽  
Pavement Performance ◽  
Ride Quality ◽  
Skid Resistance ◽  
Affecting Factors ◽  
Pavement Condition ◽  
Som Neural Network

In order to make the performance evaluation of asphalt pavement more scientific and reasonable, the author put forward an evaluation method based on SOM neural Network. This method takes comprehensive consideration of four affecting factors including pavement ride quality, pavement condition, pavement structure bearing capacity and pavement skid resistance. Then designs and simulates the SOMNN programming to comprehensive evaluate the pavement performance. Finally, the method was verified by an example, and the calculation has been compared with the traditional evaluation methods. Results showed that the method was reasonable and effective. Compared with others, this method was simpler, cheaper and easier to promote and has better superiority.

scholarly journals Contribution Modeling on Condition Evaluation of Asphalt Pavement Using Uncertainty Measurement and Entropy Theory

2021 ◽  
Vol 2021 ◽  
pp. 1-10 ◽  
Author(s):  
Jue Li ◽  
Hui Wei ◽  
Yongsheng Yao ◽  
Xin Hu ◽  
Lei Wang
Keyword(s):  
Performance Evaluation ◽  
Evaluation Index ◽  
Pavement Performance ◽  
Entropy Theory ◽  
Minimum Entropy ◽  
Uncertainty Measurement ◽  
Measurement Function ◽  
Performance Evaluation Index ◽  
Index Weight ◽  
The Impact

In view of the deficiency that traditional pavement performance evaluation index did not consider the influence of their difference on weight, the grade of the evaluation index also did not take into account intermediate state and the impact of uncertainty on the evaluation results, a determination method of pavement performance evaluation index weight based on entropy theory was developed. The unascertained measurement function of evaluation index was performed by left-half ladder distribution, and unascertained measurement matrix was obtained. The index weight was calculated by minimum entropy theory, and the practicability of this method was verified through a concrete example finally. The results show that there were different weights in different samples, which depended on index measurement function and were the overall characterization of comprehensive measurement of every index. The method which is based on the given weighting factor did not conform to the engineering facts. It was difficult to identify the importance of the pavement performance evaluation index in different samples. The balance of the various indexes is better to be considered in the proposed method, and the comprehensive situation of pavement performance is really reflected, which improves the evaluation of the reliability.

Study on Performance Evaluation for Maritime Control in Inland Complex Waters

2014 ◽  
Vol 501-504 ◽  
pp. 2034-2039
Author(s):  
Qing Liu ◽  
Chong Zheng
Keyword(s):  
Performance Evaluation ◽  
Evaluation Method ◽  
Cloud Model ◽  
Evaluation Model ◽  
Control Level ◽  
Evaluation Index System ◽  
Evaluation Index ◽  
Control Problems ◽  
Control Performance ◽  
Performance Evaluation Index

In order to grasp the effects of maritime management accurately and improve the maritime control level in complex waters, we should evaluate the performance in maritime sectors. Directing at maritime control problems in complex waters and combining with functions of maritime sectors, this paper established a performance evaluation index system of maritime control in inland complex waters. Based on the cloud model, a synthetic evaluation method is proposed to maritime control performance in inland complex waters. Through analyzing the survey data in Jingzhou River Bridge waters, the result shows that the evaluation model is scientific and feasible. The evaluation method provides a reference for improving the maritime control performance in inland complex waters.

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