Intelligent Recognition Method of Turning Tool Wear State Based on Information Fusion Technology and BP Neural Network

Xu, Yanwei; Gui, Lin; Xie, Tancheng

doi:10.1155/2021/7610884

Cited by 12 publications

(7 citation statements)

References 25 publications

(15 reference statements)

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“…Chen et al said that the new upsurge of machine translation in the 1970s was also related to automatic retrieval and artificial intelligence [ 7 ]. Xu et al said that with the progress of modern science and technology, machine translation in the 1970s was no longer a topic of natural language processing [ 8 ]. Sreelekha et al said that to establish various information retrieval systems, it is necessary to automatically index documents and even use computers to process natural languages.…”

Section: Related Workmentioning

confidence: 99%

Machine English Translation Evaluation System Based on BP Neural Network Algorithm

Han¹,

Shaoxiu

2022

Computational Intelligence and Neuroscience

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In order to solve the problems of machine translation efficiency and translation quality, this paper proposes an English translation evaluation system based on the BP neural network algorithm. This method provides users with a more intelligent machine translation service experience. With the help of the BP neural network algorithm, taking English online translation as the research object, Google’s translation quality is the best, with an error frequency of only 167, while Baidu translation and iFLYTEK translation in China have a high error rate of 266 and 301, respectively, which is much higher than Google translation. A model of machine translation evaluation based on the neural network algorithm is proposed to better solve the disadvantages of traditional English machine translation. The results show that the machine translation system based on the neural network algorithm can further optimize the problems existing in machine translation, such as insufficient use of information and large scale of model parameters, and further improve the performance of neural network machine translation.

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Section: Related Workmentioning

confidence: 99%

Machine English Translation Evaluation System Based on BP Neural Network Algorithm

Han¹,

Shaoxiu

2022

Computational Intelligence and Neuroscience

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“…The derivative of the unipolar sigmoid function, formula (16), is applied. For multihidden layer BPNN, it is only necessary to reversely derive the weight adjustment formula according to the rules [18]. The flow chart of the standard BP network program is shown in Figure 5.…”

Section: Wireless Communications and Mobile Computingmentioning

confidence: 99%

Innovative College Students’ Educational Management Mode Based on BP Neural Network

Zhang

2022

Wireless Communications and Mobile Computing

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With the advancement of society, the necessities for school graduates are getting increasingly elevated. In this unique situation, the conventional showing the board model in schools and colleges has not been able to adjust to the pattern of present day advancement and should be improved and developed likewise. By advancing the instructive administration model, this paper expects to work on the idea, conduct, and advancement capacity of undergrads to address the issues of social turn of events. In light of this, this paper principally concentrates on the issues existing in the instruction of the board of undergrads and the comparing imaginative models. This paper takes Wenzhou University students as the research object, combining qualitative analysis with quantitative analysis. This paper assembles a general travel industry proficient development and business venture schooling assessment framework based on BP brain organization. It lessens the impedance brought about by human elements in the assessment cycle and guarantees the precision of the assessment results. This paper improves the research and analysis framework of related fields, enriches the research results of innovation and entrepreneurship education evaluation in tourism, and has important theoretical value for improving the evaluation model in this field. The exploratory aftereffects of this paper show that the thorough organization yield esteem is 0.7261 as per the information gathered by Wenzhou University utilizing the poll review. It demonstrates that the advancement and business training of Wenzhou University is at a medium level, and there is still a lot of opportunity to get better.

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“…In Equation ( 2), f ðxÞ = θx + b. Aggregating user behavior data and user interaction data in social networks and representing these data as low-dimensional density vectors provide a good basis for mining user problems [17].…”

Section: Associated User Mining Algorithm Integrating User Attributes...mentioning

confidence: 99%

Implementation of Network Data Mining Algorithm for Associated Users Based on Multi-Information Fusion

Zhang

2022

Journal of Sensors

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In order to accurately and effectively mine relevant users in social networks, we can stop false information and illegal activities in the network, thereby ensuring the safety and integrity of the network environment. A method is proposed for the implementation of a data mining algorithm of a user network based on the fusion of several data. AUMA-MRL (associated user mining algorithm based on multi-information representation learning) proposes an associated user mining algorithm based on node characteristics, neighborhood information, and global network structure information. The steps of the algorithm are as follows: combining each user of the social network into a node using a method where each node is installed separately and combining network user characteristics and user relationship information. A user pair is a network similarity vector that represents the similarity of users in different dimensions. Based on these similarity vectors, a corresponding user separation algorithm is formed. It examines the feasibility and efficiency of the AUMA-MRL algorithm for researching relevant users. The proportion of associated users in the network to be fused is lower than that of nonassociated users, and the prediction has little effect on improving the recall rate of nonassociated users, so the recall rate is slightly lower than the accuracy. This algorithm can quickly get the embedding of new nodes and the similarity vector between new nodes and other nodes in the network, so as to quickly mine the associated users of new nodes in the network and enhance the robustness of the network associated user mining algorithm.

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Intelligent Recognition Method of Turning Tool Wear State Based on Information Fusion Technology and BP Neural Network

Cited by 12 publications

References 25 publications

Machine English Translation Evaluation System Based on BP Neural Network Algorithm

Machine English Translation Evaluation System Based on BP Neural Network Algorithm

Innovative College Students’ Educational Management Mode Based on BP Neural Network

Implementation of Network Data Mining Algorithm for Associated Users Based on Multi-Information Fusion

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