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ITALIAN JOURNAL OF PURE AND APPLIED MATHEMATICS 2018年第40期 244-255页

作者： Feng, Jiayin Jia, Dongyan Cui, Li Cao, Jing Lin, Zhuo Zhang, Min Hebei Normal Univ Sci & Technol Qinhuangdao Haigang Dist 066000 Heibei Peoples R China

As the education in China develops rapidly, the scientific research of higher vocational education has gradually drawn extensive attentions. In order to construct a reasonable evaluation model of scientific research performance to further enhance the research enthusiasm of teachers, this study constructed a model based on relevant theories of the support vector machine (SVM) algorithm and the back propagation (bp) algorithm. In addition, the simulation of the model was performed and the accuracy rate and errors of these two algorithms were compared and analyzed. Then the most appropriate algorithm was applied to the evaluation index system. The simulation results showed that, simplified data of scientific research evaluation could be applied as the input data of the SVM algorithm to accurately and effectively construct an evaluation index system of scientific research performances of vocational colleges. Thus a more reasonable and accurate evaluation system was constructed.

关键词： SVM algorithm bp algorithm vocational colleges scientific research performance evaluation

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The tool for building an NN based on improved bp algorithm

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Journal of Harbin Institute of Technology(New Series) 2001年第3期8卷 312-316页

作者：冯玉强潘启澍 Management School Harbin Institute of Technology

Back propagation (bp) algorithm is a very useful algorithm in many areas, but its leaning process is a very complicated non linear convergence process, in which, chaos often happens, and slow convergence speed and local least often make it difficult for the non experts to use it widely, and an improved bp (Ibp) algorithm is therefore suggested to expedite the convergence speed. The algorithm can judge local least and take some steps automatically to jump out from the local least. Furthermore, this algorithm introduces the expert knowledge base. An Ibp based agile and current neural network (NN) constructed tool is designed. An initial NN can be constructed automatically using an expert knowledge base. And an Aitken’s Δ 2 process method is used to expedite the convergent speed for NN. Besides, the method of changing the parameter of Sigmoid function and increasing the hidden node is used to bring surge for NN to jump out from the local

关键词： neural network (NN) bp algorithm

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Research on human resource management performance evaluation based on bp algorithm

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APPLIED MATHEMATICS AND NONLINEAR SCIENCES 2023年第2期8卷 1155-1166页

作者： Lv, Rui Xian Eurasia Univ Xian 710065 Shaanxi Peoples R China

With economic globalisation and in the face of increasingly fierce market competition, enterprises must establish an evaluation mechanism that can promote the company's development and motivate employees to improve performance in order to achieve the company's strategic goals. In view of the characteristics and problems of enterprise performance appraisal, a performance evaluation method based on artificial neural network (ANN) technology is proposed. This study uses bp algorithm to comprehensively evaluate the performance of enterprises and construct an evaluation network. According to the statistics of 75 power companies in the province from 2018 to 2021, the training was carried out in batches, and the 10-fold cross-validation method was used to find the smallest optimisation value of the error term (average overall relative error) of the test set. The training set is set as 70% and the test set as 30%, and the termination condition is used to end the training process when the training error is <0.0001. This proves that the use of bp neural network for performance evaluation can effectively avoid the influence of subjective factors on the evaluation results, so as to establish a more objective comprehensive evaluation system.

关键词： bp algorithm neural network human resource management the performance evaluation

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Evaluation of rural tourism development level using BERT-enhanced deep learning model and bp algorithm

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SCIENTIFIC REPORTS 2024年第1期14卷 1-14页

作者： Yuan, Xiaohe Tourism Coll Changchun Univ Tourism & Cultural Sch Dev Res Ctr Jilin Culture & Tourism Ind Changchun 130607 Jilin Peoples R China

To address the insufficient expressive capabilities of traditional methods in assessing the development level of rural tourism, this study explores the fusion application of the Bidirectional Encoder Representations from Transformers (BERT) and the Back Propagation (bp) algorithm to enhance the accuracy and comprehensiveness of rural tourism development assessment. Firstly, this study introduces the BERT deep learning model and its applications in natural language processing, alongside the role of the bp algorithm in pattern recognition and predictive analysis. Subsequently, a framework for assessing rural tourism development levels, integrating BERT and the bp algorithm, is proposed. This framework collects multidimensional rural tourism-related data and utilizes the BERT model for sentiment analysis and topic extraction from textual data. Empirical analysis of rural tourism development in a specific region validates the effectiveness of the proposed approach. Experimental results demonstrate: (1) The model achieves an accuracy of 84.33% and an F1 score of 85.33% on the publicly available Laptop dataset, with a processing time of 20 s, significantly outperforming other methods. Compared to traditional approaches, the proposed method accurately captures correlations between textual information and numerical data, thereby enhancing the credibility and accuracy of assessment results. (2) From the ablation study results, it is evident that removing any component from the model leads to performance degradation. Specifically, removing the Bidirectional Gated Recurrent Unit (BiGRU) reduces accuracy and F1 scores to 78.21% and 76.33% on the Laptop dataset, and to 85.10% and 70.45% on the Tourist_F dataset. Removing Text Convolutional Neural Network (CNN) reduces accuracy and F1 scores to 79.34% and 77.56% on the Laptop dataset, and to 86.25% and 72.11% on the Tourist_F dataset. The most significant performance decline occurs upon removing BERT, with accuracy and F1 scores

关键词： BERT-based deep learning model bp algorithm Rural tourism Accuracy F1 score

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Discovery Model and Classification Prediction of Dust Pollution at Different Altitudes Based on LS-SVM and bp algorithm

Discovery Model and Classification Prediction of Dust Pollut...

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International Smart Cities Conference (ISC2)

作者： Ju, XunGuang Shao, XiaoGen Bao, Rong Liu, Feng Li, Putao Xuzhou Univ Technol Sch Informat & Elect Engn Xuzhou Jiangsu Peoples R China

ISBN: (纸本)9781538625248

In order to solve the classification prediction of dust pollution at different altitudes, the least square support vector machine(LS-SVM) and bp neural network is used to construct the distribution model. Built by LS-SVM, the accuracy of the model was verified by bp neural network with the real-time dust pollution data of different high monitored by Unmanned aerial vehicles. The data analysis shows that the dust pollution below 30 meters is much serious than that above 90 meters, which mainly concentrated in the low altitude area of 20 to 30 meters. While in the range of 80 to 250 meters, the dust pollution is basically proportional to the height, that is to say, the higher the altitude, the greater the pollution index.

关键词： least square support vector machine bp algorithm dust pollution distribution model classification prediction

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An Improved bp algorithm over Out-of-order Streams for Big Data

An Improved BP Algorithm over Out-of-order Streams for Big D...

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8th International ICST Conference on Communications and Networking in China (CHINACOM)

作者： Wang, Kun Zhuo, Linchao Lu, Heng Guo, Huang Xu, Lili Zhang, Yuhua Nanjing Univ Posts & Telecommun Minist Educ Key Lab Broadband Wireless Commun & Sensor Networ Nanjing 210003 Jiangsu Peoples R China

ISBN: (纸本)9781479914067

Due to the difficulty of getting the association rules over out-of-order streams for big data, a new improved bp algorithm based on dynamic adjustment is proposed. We firstly use a dynamic adaptive structural adjustment mechanism to change the network training structure according to the environmental requirements, which can automatically remove invalid training node, and optimize the iterative training process. Secondly, we adjust three factors (i.e. learning index, momentum factor and scaling factor) during the learning process to speed up the learning response, and to enhance the stability of the network. Simulation results show that compared with traditional bp algorithm, this algorithm can get more convergence times, the convergence rate can be improved effectively, and finally obtain the association rules over out-of-order data streams.

关键词： bp algorithm Out-of-order Streams Machine Learning Big Data

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AN IMPROVED bp algorithm FOR PATTERN RECOGNITION

AN IMPROVED BP ALGORITHM FOR PATTERN RECOGNITION

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1998 Fourth International Conference Signal Processing

作者： Zeng Yujuan Wang Xiangdong Wang Shoujue Institute of Semiconductors CAS

An improved bp algorithm for pattern recognition is proposed in this *** a function substitution for error measure,it resolves the inconsistency of bp algorithm for pattern recognition problems,*** quadratic error is not sensitive to whether the training pattern is recognized correctly or *** by this new method,the computer simulation result shows that the convergence speed is increased to treble and performance of the network is better than conventional bp algorithm with momentum and adaptive step size.

关键词： bp algorithm Pattern recognition Neural Network misclassification rate

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Prediction of Oilfield Cementing Quality Based on Levenberg-Marquardt bp algorithm

Prediction of Oilfield Cementing Quality Based on Levenberg-...

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2011 First International Conference on High Performance Structures and Materials Engineering (ICHPSM 2011)

作者： WANG Yuxue ZHOU Shaohua School of Mathematical Science and Engineering Northeast Petroleum University

In this paper an improved algorithm of bp neural network—— Levenberg-Marquardt(LM) algorithm is introduced, and the simulation predictions of oilfield cementing quality is done by using this method. Finally, a pract... 详细信息

关键词： bp algorithm LM algorithm Cementing Quality Prediction

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The Prediction Model of Coal Mine Disaster Based on bp algorithm

The Prediction Model of Coal Mine Disaster Based on BP Algor...

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2011 4th IEEE International Conference on Computer Science and Information Technology(ICCSIT 2011)

作者： Mao Zheng-li Gao Song-feng Department of Survey & Urban Spatial information Henan University of Urban Construction Henan Pingdingshan China

The occurrence of coal mine disaster related with many environmental and social *** relationship between them was uncertainty,and was a kind of coupling relationship,and was *** was difficult to fit the relationship between them using a mathematical *** also was the important reason that coal mine disaster was always hard to *** artificial neural network based on bp algorithm had highly nonlinear mapping *** could nonlinear map the relationship between the probability of coal mine disaster’s occurrence and its effect factors on the condition of building no complex mathematical *** then the probability of coal mine disaster could be predicted relatively *** provided technical support for prevention and management of coal mine disaster.

关键词： coal mine disaster bp algorithm nonlinear mapping prediction model

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RESEARCH ON COAL GANGUE ON-LINE AUTOMATIC SEPARATION SYSTEM BASED ON THE IMPROVED bp algorithm AND ARM

RESEARCH ON COAL GANGUE ON-LINE AUTOMATIC SEPARATION SYSTEM ...

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2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

作者： XIAO-RU SONG FENG-JUN WANG Department of Electronic and Information Engineering XI'AN Technological University XI'AN 710032 The 20th Research Institute of the China Electronics and Technology Corporation XI'AN 710068 China

It is not satisfied with the increasing need day to day that the conventional digital image processing *** bp neural network is one of the most effective means with the merits such as parallel computation, nonlinear mapping and the self-adaptation;ARM (Advanced RISC Machines) microcontroller is widely used in lots of fields with characteristics of high-performance, small volume, low power dissipation and low-cost *** paper researches on coal gangue on-line automatic separation system based on the improved bp algorithm and ***, the general system is introduced in ***, it is the basal information on the bp neural network and the digital image processing *** is emphasized that the digital image processing is applied with the improved bp *** then the design of the interface circuits is in detail discussed and the ARM microcontroller and last the emulation debugging figures are *** show that the design is successful.A newly means, which automatically select the gangue from the coal, is explored.

关键词： ARM microcontroller Coal gangue bp algorithm Image processing CPLD

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