Inverse kinematics is an important basic theory in walking control of biped robot. This study focuses on the parameter setting using the improved algorithm in inverse kinematics. By analyzing the process of whether ca...
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Inverse kinematics is an important basic theory in walking control of biped robot. This study focuses on the parameter setting using the improved algorithm in inverse kinematics. By analyzing the process of whether can the robot legs arrive at the expected positions from different initial positions, the parameter value range is determined. It must be noted that, the parameter values exhibit clear physical significance. The robot legs can move stably within the allowable value range. Furthermore, the superiority of the improved algorithm was validated by 3D simulation of leg motion. Moreover, the present study can provide theoretical basis for optimizing the leg motion of biped robot and developing the related prototype.
Data mining algorithms can process target data and extract useful hidden information, which is helpful for decision making. However, current mining algorithms have some shortcomings such as time-consuming processing o...
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Data mining algorithms can process target data and extract useful hidden information, which is helpful for decision making. However, current mining algorithms have some shortcomings such as time-consuming processing of big data or inability to process massive data. Since data mining technology cannot be used in the traditional cloud platform environment, it is necessary to improve the algorithm to make it more suitable for the cloud platform environment. By analyzing the actual application process of BP classification algorithm, this paper expounds the practicability of BP classification algorithm, analyzes the data mining process based on Hadoop cloud platform, and expounds the development ideas of BP classification algorithm. The source of data mining algorithm supported by cloud computing is discussed. Finally, Hadoop cloud platform. This paper designed the corresponding system architecture and data interface, and established a suitable test environment for this system, and completed the simulation experiment test through the design. The calculation time of this algorithm is proportional to the amount of data, showing a linear relationship. In data mining, the optimized BP algorithm in this paper can significantly save resources in terms of spatial features. This paper designs an optimized operating system based on Hadoop platform through comprehensive analysis and improvement algorithm.
BP network, as the most commonly used model of artificial neural network, has many insurmountable problems in practical application. Therefore, scholars at home and abroad combined with practical application put forwa...
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ISBN:
(纸本)9789811697357;9789811697340
BP network, as the most commonly used model of artificial neural network, has many insurmountable problems in practical application. Therefore, scholars at home and abroad combined with practical application put forward an improved algorithm. In this paper, the understanding of the original BP neural network model is combined with the improved algorithm to analyze how it can be correctly applied.
With the vigorous development of e-commerce, higher requirements are put forward for the storage capacity and operation efficiency of the warehousing system to ensure the performance of the entire supply chain in the ...
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With the vigorous development of e-commerce, higher requirements are put forward for the storage capacity and operation efficiency of the warehousing system to ensure the performance of the entire supply chain in the business process. The factors that affect the operation efficiency and storage capacity of the warehousing system mainly include: storage space planning, shelf design, goods access strategy, stacker scheduling strategy, goods picking efficiency, etc. The main research object of this paper is the optimization of the scheduling strategy of the stacker in the storage system, which can solve the problem of the storage space detention caused by the irregular storage and the empty running time in the scheduling process of the stacker, so as to improve the operating efficiency of the storage system.
The association rule algorithm in data mining is used to study the factors that may affect students' performance, to make suggestions for teaching work, and to provide decision-making basis for teachers and teachi...
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The association rule algorithm in data mining is used to study the factors that may affect students' performance, to make suggestions for teaching work, and to provide decision-making basis for teachers and teaching administrators, which has practical significance. There are many potential applications for facial expression recognition technology. For example, in the teaching process, facial expression recognition technology helps teachers understand students and judge students' reactions to certain things. Based on the current research status of emotion recognition and data mining algorithms, this paper improves the AprioriTid algorithm and constructs an online teaching quality evaluation model based on teaching needs. In addition, this article applies the model constructed in this article to the evaluation of English online teaching quality and evaluates teaching quality through data mining. The experimental research shows that the model constructed in this paper has good performance.
In order to solve the hidden terminal problem of SPMA protocol in multihop environment, this paper proposes a distributed load sensing method. The cross layer joint optimization design of network layer and link layer ...
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ISBN:
(纸本)9781665490825
In order to solve the hidden terminal problem of SPMA protocol in multihop environment, this paper proposes a distributed load sensing method. The cross layer joint optimization design of network layer and link layer is adopted. The topology state perceived by network layer is used to correct the evaluation of the channel load rate in link layer, and then dynamically to adjust the priority threshold. The problem of inaccurate evaluation of SPMA channel load rate in multi-hop network environment is solved. And the message transmission success rate in multi-hop environment is improved. This paper establishes SPMA simulation scenario and improved algorithm model, then simulates and analyzes the application layer throughput, application layer end-to-end delivery rate, application layer end-to-end delay, link layer load, link layer throughput, link layer delivery rate, link layer queuing delay and other indicators. The results show that the improved algorithm proposed in this paper significantly improves the delivery rate of high-priority business. The strong QoS guarantee for highpriority business is realized.
Sports competition characteristics play an important role in judging the fairness of the game and improving the skills of the athletes. At present, the feature recognition of sports competition is affected by the envi...
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Sports competition characteristics play an important role in judging the fairness of the game and improving the skills of the athletes. At present, the feature recognition of sports competition is affected by the environmental background, which causes problems in feature recognition. In order to improve the effect of feature recognition of sports competition, this study improves the TLD algorithm, and uses machine learning to build a feature recognition model of sports competition based on the improved TLD algorithm. Moreover, this study applies the TLD algorithm to the long-term pedestrian tracking of PTZ cameras. In view of the shortcomings of the TLD algorithm, this study improves the TLD algorithm. In addition, the improved TLD algorithm is experimentally analyzed on a standard data set, and the improved TLD algorithm is experimentally verified. Finally, the experimental results are visually represented by mathematical statistics methods. The research shows that the method proposed by this paper has certain effects.
The intelligent evaluation of classroom teaching quality is one of the development directions of modern education. At present, some teaching quality evaluation models have accuracy problems, and the evaluation process...
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The intelligent evaluation of classroom teaching quality is one of the development directions of modern education. At present, some teaching quality evaluation models have accuracy problems, and the evaluation process is affected by a variety of interference factors, which leads to inaccurate model results, and it is impossible to find out the specific factors that affect teaching. In order to improve the accuracy of classroom teaching quality evaluation, this study improves RVM based on the method of feature extraction and empirical modal decomposition of ACLLMD method, and establishes classroom theoretical teaching quality evaluation model and experimental teaching quality evaluation model based on RVM algorithm. Moreover, this study uses test data to analyze the accuracy and reliability of the evaluation results to verify the feasibility and reliability of the new method. In addition, this study verifies the reliability of this algorithm by comparing with the manual scoring results. The research results show that RVM can be used to construct classroom theory teaching quality evaluation models and experimental teaching quality evaluation models with high accuracy and good reliability.
There are many factors that need to be considered when planning a city's green economy, so it is difficult to simulate the planning effect through manual models. In order to improve the effect of urban green econo...
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There are many factors that need to be considered when planning a city's green economy, so it is difficult to simulate the planning effect through manual models. In order to improve the effect of urban green economic planning, this paper improves the traditional algorithm and combines the principle of machine learning algorithm to build a model that can be used in urban green economic planning. Moreover, this paper considers the measurement of green economic efficiency from the perspective of input, expected output and undesired output. In addition, this paper compares and analyzes the green efficiency calculated by the SE-SBM model, including horizontal comparison analysis and vertical comparison analysis, and conducts model simulation analysis in combination with data simulation research. Finally, this paper sets the simulation area, combines the data to perform model performance analysis, summarizes the data with statistical analysis methods, and draws charts. The research results show that the model constructed in this paper has a certain effect and can be applied to the design stage of urban green planning.
An experimental apparatus for normal spectral emissivity measurements at low temperatures was constructed by using the Fourier transform infrared (FTIR) spectrometer. The FTIR spectrometer was calibrated against a hig...
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An experimental apparatus for normal spectral emissivity measurements at low temperatures was constructed by using the Fourier transform infrared (FTIR) spectrometer. The FTIR spectrometer was calibrated against a high quality reference blackbody based on the multi-temperature method. The spectral response function R (2) was computed by the least-square method. To improve the precision of emissivity measurement, an improved algorithm to eliminate disturbances by background radiation was presented. Emissivity uncertainty caused by the spectral response function R (lambda) was analyzed. A comparison between the results obtained by the multi-temperature calibration method and the two temperature method was presented. The linearity of the FTIR spectrometer response in the studied spectral range is better than 1% except spectral bands due to atmospheric absorptions. A high-purity (99 wt%) alumina sample was used to validate emissivity results obtained by the improved algorithm. The excellent agreement with the literature data around Christiansen wavelength demonstrates that our experimental apparatus and the improved algorithm can provide reliable measurements. The calculated relative combined uncertainty of the spectral emissivity for the alumina sample is estimated to be less than 5.1% for the spectral range considered. (C) 2017 Elsevier Ltd. All rights reserved.
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