Average Probability Research Articles

Performance analysis of FSO communications over a generalized turbulence fading channel with pointing error

SummaryQuantitatively assessing the performance of free space optical (FSO) communication systems requires an accurate description of turbulence induced fading. However, it is well known that common irradiance distributions inaccurately model intensity tail regions. Recently, a general fading model as the product of arbitrary number of Gamma with inverse Gamma was proposed and shown to accurately predict measurements, besides containing many well‐known models as special cases. This paper is concerned with analyzing the effect of discrepancies among different fading distributions on optical system performance in terms of bit error rates and capacity. Based on the general fading model a unified analysis of the channel structure effects on FSO communications in the presence of turbulence and pointing error is presented. The outage probability is investigated for both homodyne and direct detection schemes. Closed form expressions for the average probability of bit error for intensity modulation, phase shift keying and polarization shift keying, single‐input‐single‐output systems are given and verified by Monte‐Carlo simulations. Spatial diversity is also studied through single‐input‐multiple‐output systems. Also, the ergodic capacity is derived. Comparisons between the proposed distributions and other widely used distributions are carried out and show significant differences among existing fading models. This suggests possible improvements in the spectral efficiency and error performance design of optical wireless communication systems.

Independent external validation and comparison of existing pancreatic fistula risk scores after laparoscopic pancreaticoduodenectomy with Bing’s pancreaticojejunostomy

The fistula risk score (FRS) is the widely acknowledged prediction model for clinically relevant postoperative pancreatic fistula (CR-POPF). In addition, the alternative FRS (a-FRS) and updated alternative FRS (ua-FRS) have been developed. This study performed external validation and comparison of these 3 models in patients who underwent laparoscopic pancreaticoduodenectomy (LPD) with Bing's pancreaticojejunostomy. The FRS total points and predictive probabilities of a-FRS and ua-FRS were retrospectively calculated using patient data from a completed randomized controlled trial. Postoperative pancreatic fistula (POPF) and CR-POPF were defined according to the 2016 International Study Group of Pancreatic Surgery criteria. The correlations of the 4 risk items of the FRS model with CR-POPF and POPF were analyzed and represented using the Cramer V coefficient. The performance of the 3 models was measured using the area under the curve (AUC) and calibration plot and compared using the DeLong test. This study enrolled 200 patients. Pancreatic texture and pathology had discrimination for CR-POPF (Cramer V coefficient: 0.180 vs 0.167, respectively). Pancreatic duct diameter, pancreatic texture, and pathology had discrimination for POPF (Cramer V coefficient: 0.357 vs 0.322 vs 0.257, respectively). Only the calibration of a-FRS predicting CR-POPF was good. The differences among the AUC values of the FRS, a-FRS, and ua-FRS were not statistically significant (CR-POPF: 0.687 vs 0.701 vs 0.710, respectively; POPF: 0.733 vs 0.741 vs 0.750, respectively). After recalibrating, the ua-FRS got sufficient calibration, and the AUC was 0.713 for predicting CR-POPF. For LPD cases with Bing's pancreaticojejunostomy, the 3 models predicted POPF with better discrimination than predicting CR-POPF. The recalibrated ua-FRS had sufficient discrimination and calibration for predicting CR-POPF.

Spatio-temporal analysis and risk modeling of foot-and-mouth disease outbreaks in China

FMD is an acute contagious disease that poses a significant threat to the health and safety of cloven-hoofed animals in Asia, Europe, and Africa. The impact of FMD exhibits geographical disparities within different regions of China. The present investigation undertook an exhaustive analysis of documented occurrences of bovine FMD in China, spanning the temporal range from 2011 to 2020. The overarching objective was to elucidate the temporal and spatial dynamics underpinning these outbreaks. Acknowledging the pivotal role of global factors in FMD outbreaks, advanced machine learning techniques were harnessed to formulate an optimal prediction model by integrating comprehensive meteorological data pertinent to global FMD. Random Forest algorithm was employed with top three contributing factors including Isothermality(bio3), Annual average temperature(bio1) and Minimum temperature in the coldest month(bio6), all relevant to temperature. By encompassing both local and global factors, our study provides a comprehensive framework for understanding and predicting FMD outbreaks. Furthermore, we conducted a phylogenetic analysis to trace the origin of Foot-and-mouth disease virus (FMDV), pinpointing India as the country posing the greatest potential hazard by leveraging the spatio-temporal attributes of the collected data. Based on this finding, a quantitative risk model was developed for the legal importation of live cattle from India to China. The model estimated an average probability of 0.002254% for FMDV-infected cattle imported from India to China. TA sensitivity analysis identified two critical nodes within the model: he possibility of false negative clinical examination in infected cattle at destination (P5) and he possibility of false negative clinical examination in infected cattle at source(P3). This comprehensive approach offers a thorough evaluation of FMD landscape within China, considering both domestic and global perspectives, thereby augmenting the efficacy of early warning mechanisms.

Comparative Evaluation of Odontometric Parameters for Determining Gender

Background and Aim: Sex estimate is a crucial component of human identification in a forensic setting. Due to the sexual dimorphism of human teeth, odontometrics—the measuring and analysis of tooth size standards—is most frequently utilized in age and sex determination. The aim of this study was to assess the degree of sexualdimorphism in mandibular canine using mandibular canine index using mesiodistal (MD) and buccolingual (BL)dimensions of the crown and inter canine distance measured.Material and Methods: The study sample included 200 people (100 men and 100 women), ages 18 to 35, withan average age of 22 years. The distance between the mesial and distal contact points was used to calculate the mesiodistal dimension of the mandibular canine (CMD). Each subject’s right mandibular canine index and left mandibular canine index were used to construct the canine index. The standard canine index (SCI) value was used as a cutoff point to differentiate males from females.Results: Men’s right and left mandibular canines mesio-distal crown widths were found to be significantly greater than those of their female counterparts. The current study demonstrates a very high significance of p value seen in the left mandibular canine and a significant difference in mesiodistal breadth between males and females of the right mandibular canine of p value. The total probability of sex determination for the right mandibular canine is 55% and for the left canine is 59.5% based on the conventional MCI calculations for the right mandibular canine (0.22) and for the left mandibular canine (0.21), suggesting that the left mandibular canine is more relevant for sex determination.Conclusion: It has been proven beyond a reasonable doubt that mandibular canines exhibit significant sexual dimorphism when it comes to sex determination, and it is clear from the study that this breed is a more trustworthy source for sex determination.

Noninvasive Isocitrate Dehydrogenase 1 Status Prediction in Grade II/III Glioma Based on Magnetic Resonance Images: A Transfer Learning Strategy.

The aim of this study was to evaluate transfer learning combined with various convolutional neural networks (TL-CNNs) in predicting isocitrate dehydrogenase 1 ( IDH1 ) status of grade II/III gliomas. Grade II/III glioma patients diagnosed at the Tangdu Hospital (August 2009 to May 2017) were retrospectively enrolled, including 54 patients with IDH1 mutant and 56 patients with wild-type IDH1 . Convolutional neural networks, AlexNet, GoogLeNet, ResNet, and VGGNet were fine-tuned with T2-weighted imaging (T2WI), fluid attenuation inversion recovery (FLAIR), and contrast-enhanced T1-weighted imaging (T1CE) images. The single-modal networks were integrated with averaged sigmoid probabilities, logistic regression, and support vector machine. FLAIR-T1CE-fusion (FC-fusion), T2WI-T1CE-fusion (TC-fusion), and FLAIR-T2WI-T1CE-fusion (FTC-fusion) were used for fine-tuning TL-CNNs. IDH1 -mutant prediction accuracies using AlexNet, GoogLeNet, ResNet, and VGGNet achieved 70.0% (AUC = 0.660), 65.0% (AUC = 0.600), 70.0% (AUC = 0.700), and 80.0% (AUC = 0.730) for T2WI images, 70.0% (AUC = 0.660), 70.0% (AUC = 0.620), 70.0% (AUC = 0.710), and 80.0% (AUC = 0.720) for FLAIR images, and 73.7% (AUC = 0.744), 73.7% (AUC = 0.656), 73.7% (AUC = 0.633), and 73.7% (AUC = 0.700) for T1CE images, respectively. The highest AUC (0.800) was achieved using VGGNet and FC-fusion images. TL-CNNs (especially VGGNet) had a potential predictive value for IDH1 -mutant status of grade II/III gliomas.

Implementation of three-qubit Deutsch-Jozsa algorithm with pendular states of polar molecules by optimal control

Ultracold polar molecules have gained much attention as a potential candidate for quantum information processing due to their long coherence time and strong dipole–dipole interaction. In the present study, we explore the dynamics of three polar molecules that are mutually coupled and arranged in an equilateral triangle configuration within a gradient electric field. By employing the pendular states of polar molecules as qubits, we simulate the three-qubit Deutsch-Jozsa algorithm via multi-target optimal control. Through the design of optimal microwave pulses with multiple iterations, our approach can accomplish the operations required to complete the algorithm in a single operational step with high fidelity and large transition probability. Furthermore, we compare and analyze the fidelity and average transition probability with respect to iteration numbers for each unitary operation Uf pulse. It is found that by combining the optimized X, H⊗H⊗H, Uf, and H⊗H gate pulses, the Deutsch-Jozsa algorithm in the three-dipole system can be performed well for distinguishing between constant and balanced functions. Our findings could shed some light on the physical realization of multi-particle quantum algorithm based on polar molecules in external electric fields.

Study of energy transfer process and radiative properties of CaAl4O7:Ho3+ phosphor for green light emission

This work comprehensively analyse the structural and photoluminescence properties of Ho3+-doped CaAl4O7 phosphor systems. X-ray diffraction (XRD), diffuse reflectance spectrum (DRS), photoluminescence (PL), and Fourier transform infrared (FT-IR) spectroscopy measurements were carried out, and Rietveld analysis confirmed the pure monoclinic structure of CaAl4O7:Ho3+ phosphor. The FT-IR spectrum showed absorption bands for the tetrahedral sites of the Al-O bonds and the octahedral sites of the Ca-O bonds, which indicate the formation of the CaAl4O7:Ho3+ phosphor. The diffuse reflectance spectrum shows sharp peaks in the visible and near-infrared regions. Photoluminescence excitation (PLE) measurements were performed on all the phosphor samples by monitoring emissions at 545 nm. Radiative properties such as total radiative transition probabilities (AT), radiative lifetime (τ rad), and branching ratios (β) are reported by Judd–Ofelt analysis and PLE spectral measurements. Upon 454 nm excitation, a green emission band is observed at around 545 nm (5F4 + 5S2 → 5I8), and these results indicate that x = 0.05 mol Ho3+ is the optimum concentration as the 5F4 + 5S2 → 5I8 emission intensity reaches its maximum. The emission intensity quenching and energy transfer mechanism are discussed, and the results suggest that the CaAl4O7:Ho3+ samples are suitable for green-emitting phosphor.

Numerical evaluation of space form design for outpatient waiting space to reduce airborne infection risk in hospitals

The outpatient waiting space (OWS), with high density and frequent variations of occupants, represents a high-risk space for the spread of respiratory infectious diseases (RIDs) in hospitals. While previous studies have proposed strategies related to occupant behavior and environmental quality, there is a limited exploration of the impact of space form design on infection risk in OWSs. This study developed a numerical method for assessing the airborne infection risk, considering the non-uniform distribution of infectious particles and variations in occupant distributions. Validated computational fluid dynamics (CFD) simulations were employed to calculate the particle distributions. The intake fraction, accumulated throughout the waiting process, was then integrated into the Wells-Riley model for risk evaluation. Using the typical ventilation form of ceiling supply and ceiling return, with an air change per hour (ACH) set to 6 h−1 as the baseline, 12 typical space forms, including four space shapes (L shape, T shape, U shape, and O shape) and three entrance layouts (single-side entrance, middle entrance, and double-side entrances), were selected for comparisons. The results showed significant variations in infectious particle distributions across the 12 space forms, with average infection probabilities (IPs) ranging from 3.47 % to 19.75 %, suggesting that appropriate space form design has the potential to reduce IP by 16.28 %. These findings offer a novel perspective on mitigating airborne infection risk in hospitals by emphasizing the significance of architectural design. Moreover, precise space design guidance is proposed for OWS to safeguard human health against the spread of RIDs.

Enriched Presheaf Model of Quantum FPC

Selinger gave a superoperator model of a first-order quantum programming language and proved that it is fully definable and hence fully abstract. This paper proposes an extension of the superoperator model to higher-order programs based on modules over superoperators or, equivalently, enriched presheaves over the category of superoperators. The enriched presheaf category can be easily proved to be a model of intuitionistic linear logic with cofree exponential, from which one can cave out a model of classical linear logic by a kind of bi-orthogonality construction. Although the structures of an enriched presheaf category are usually rather complex, a morphism in the classical model can be expressed simply as a matrix of completely positive maps. The model inherits many desirable properties from the superoperator model. A conceptually interesting property is that our model has only a state whose “total probability” is bounded by 1, i.e. ‍does not have a state where true and false each occur with probability 2/3. Another convenient property inherited from the superoperator model is a ωCPO-enrichment. Remarkably, our model has a sufficient structure to interpret arbitrary recursive types by the standard domain theoretic technique. We introduce Quantum FPC , a quantum λ-calculus with recursive types, and prove that our model is a fully abstract model of Quantum FPC.

Nonlinear energy harvesting based alternate cooperative nonorthogonal multiple access with adaptive interference cancellation

We consider an energy-limited network, where a source node intends to communicate with two energy harvesting (EH) near-users and one far-user. We design a nonlinear EH-based alternate cooperative nonorthogonal multiple access (CNOMA) scheme, where the source node alternately superimposes the data of each near-user and the far-user and broadcasts the composite signal. When one near-user decodes the data of both the far-user and itself by using the adaptive interference cancellation technique, the other near-user can harvest energy from the received signal. The two near-users alternately and adaptively forward data to the far-user. We properly model the energy statuses of both the two near-users by defining a group of unequally-spaced discrete energy levels. We analyze the average success probability and throughput of each user, and use the differential evolution (DE) algorithm to efficiently achieve the maximum system throughput by jointly optimizing both the time and power allocation factors. We also present two benchmark EH-based transmission schemes for comparison. Extensive simulations are conducted to validate our theoretical analysis and reveal the impacts of various parameters.

Performance assessment of full-duplex two-way Internet-of-vehicles relay networks under practical imperfect conditions

Contemporary Internet-of-Things (IoT) devices in general and Internet-of-Vehicles (IoV) networks in specific are taking the benefits from using full-duplex (FD) communication with the help of relay nodes to facilitate data transmission. However, self-interference between transmit and receive antennas at the relay node may cause big trouble if self-interference cancellation (SIC) is not applied. In this paper, a rigorous analysis on the performance of FD two-way relay networks (FDTWRNs) for IoV applications under imperfect conditions is provided. Different from earlier studies on the performance of FDTWRNs where one or two imperfect factors were considered, this work simultaneously takes into account many practical issues in the implementation of the IoV networks at the physical layer, including errors in channel state information at all channel links, imperfect SIC and transceiver hardware impairment at all nodes. For relaying protocol, we consider amplify-and-forward with both fixed-gain (FG) and variable-gain (VG) protocols. The exact closed-form expressions (in terms of the system parameters) of key performance factors such as signal-to-interference-plus-noise-distortion-and-error ratio (SINER), outage probability (OP), achievable data rate (ADR), and average symbol error probabilities (ASEP) of the considered system over Rayleigh fading channels and under the combined effect of imperfect CSI, SIC, and transceiver hardware are derived mathematically using probabilistic model analysis. The correctness of the analysis is then verified by Monte Carlo simulations. Drawing upon both analytical and numerical findings, the efficacy of the FDTWRNs under consideration is meticulously and comprehensively assessed in comparison to its performance in ideal conditions characterized by one or multiple critical factors. The disparity between perfect and imperfect scenarios serves as a valuable metric for appraising the practical viability of the considered FDTWRNs when deployed in practical IoV networks.

A time-dependent quantum wavepacket method on stair-shaped grids for reactive scattering using the hyperspherical coordinates

Development of efficient numerical methods for quantum reactive scattering process by using time-dependent quantum wavepacket method is always necessary in the field of quantum chemistry, due to the complexity of the system, and the large computational efforts required. To perform quantum reactive scattering calculation in hyperspherical coordinates, as the hyper-radial (ρ) increases, the potential well along the angular degree of the freedom (χ) becomes narrower and narrower, which thus requires denser and denser grid points for well describing the diatomic vibrational motion. This makes the time dependent wavepacket packet calculations prohibitively difficult using hyperspherical coordinate when the reaction involves long range interaction potential or requires long absorption potential. In this study, we developed a stair-shaped grid based quantum wavepacket method to overcome this difficulty. In this method, the hyper-radial is partitioned into multidomains in the form of a stair-shape. In each domain, different grid point numbers could be applied for the angular degree of the freedom (χ). In this way, the computational effort could be saved. For numerical example, the stair-shaped grid based quantum wavepacket method is applied to compute the total reaction probability of the F+HCl (v0,j0)→ HF+Cl reaction , which involves long range interaction potential. The results are compared with those calculated with the reactant coordinate-based (RCB) Jacobi coordinate and Interaction Asymptotic Region Decomposition (IARD) method.

The Bijection Property in the Law of Total Probability and Its Application in Communication Theory

The Bijection Property in the Law of Total Probability and Its Application in Communication Theory

Fuzzy Logic for the Improving of Handover Decision and the Adaptive Adjustment of Control Parameters in 5G Wireless Networks

Handover process is one of the most important aspects of mobility management in 5G wireless networks. It becomes a hot topic for researchers because it constitutes a guarantee of communication continuity during the user's movement, in addition to being the basic step on which the mobility load balancing process depends to distribute the load between the cells. The focus on this process is whether by providing solutions to improve the handover decision-making, or by modifying the values of the handover control parameters in a way that it guarantees the reduction of handover problems, because the inaccurate or unnecessary modification of these parameters values will cause a degradation in the quality of service. This paper presents a study targeting two mechanisms to improve handover decision-making and selection of handover control parameters adaptively based on different schemes. The first one, based on a learning model called LIM2 and the second one is based on fuzzy logic and is called RHOT-FLC. The results show that the RHOT-FLC mechanism, which relies on fuzzy logic and takes into account the user's velocity provides better performance in term of average throughput, packet drop rate, average HOPP probability, average HO latency, HO failure.

Selective-Fading Multiple-Access MIMO Channels: Diversity-MultiplexingTradeoff and Dominant Outage Event Regions

We establish the optimal diversity-multiplexing (DM) tradeoff for coherent selective-fading multiple-access MIMO channels and provide corresponding code design criteria. As a byproduct, on the conceptual level, we find an interesting relation between the DM tradeoff framework and the notion of dominant error event regions, first introduced in the AWGN case by Gallager, IEEE Trans. IT, 1985. This relation allows us to accurately characterize the error mechanisms in MIMO fading multiple-access channels. In particular, we find that, for a given rate tuple, the maximum achievable diversity order is determined by a single outage event that dominates the total error probability exponentially in SNR. Finally, we examine the distributed space-time code construction proposed by Badr and Belfiore, Int. Zurich Seminar on Commun., 2008, using the code design criteria derived in the present paper.

Probabilistički višekriterijumski robustni dizajn i njegova primena u sečenju metala

Introduction/purpose: Cutting is a typical material process. However, an appropriate solution for simultaneous optimization of material machinability and tool life in material cutting processes has not been obtained yet. In this article, probabilistic multi-objective robust design (PMORD) is expounded and the robust design problem in the simultaneous optimization of material machinability and tool life is analyzed by taking the machining of ferrite-bainite dual-phase steel as an example. Methods: According to PMORD, the arithmetic mean and its deviation of various performance and utility indexes of alternative schemes are evaluated as twin independent responses, which respectively contribute a part of the partial preferable probability to the performance indexes. In the evaluation, the arithmetic average of the utility index is taken as the representative of the utility attribute, and the evaluation is made in accordance with the function or preference of the utility index. However, the deviation term is generally used as an unbeneficial type of the index (that is, the smaller the better) to participate in the evaluation. The product of the two parts of partial preferable probability is the actual partial preferable probability of the corresponding performance index. The product of the partial preferable probability of all performance utility indexes gives the total preferable probability of the corresponding scheme, which is the only index for each scheme to participate in the competition in robust design. Results: The optimization result of this example is that the tool life is 1297.3333 s (standard deviation is 2.0817 s) and the surface roughness is 2.22mm (standard deviation is 0.2mm), while the corresponding working conditions are that the heat treatment temperature of the material is 790°C, the cutting speed is 150m/min, the feed speed is 0.15mm/rev, and the cutting depth is 0.2mm. Conclusion: The example of the parameter optimization of cutting of ferrite-bainite dual-phase steel by means of PMORD indicates the rationality of the appropriate solution.

Research on Precision Teaching Reform of Japanese Language Education in Colleges and Universities Based on the CRS Model

Abstract The traditional Japanese language teaching method is challenging to mobilize students’ enthusiasm, and it is impossible to objectively understand students’ mastery of knowledge points. To address this teaching problem, this paper combines the CRS model with K-Means cluster analysis to construct a precise teaching model for teaching Japanese language in colleges and universities based on the CRS model. Through the CRS model to obtain the students’ mastery of knowledge and differentiated data, the K-Means algorithm is used to analyze the teaching model accurately, so Japanese teachers can make timely adjustments to the classroom teaching situation and improve the quality of teaching. After the model design was completed, a controlled teaching experiment was conducted in two colleges and universities in a province, and an independent square root t-test was performed. The ratio of teachers’ verbal behavior in the experimental class of Japanese language in colleges and universities was 71.58%, which was 18.86% lower than the ratio of teachers’ verbal behavior in the classroom of the control case, and the ratio of students’ verbal behavior was 21.58%, which was 18.36% higher. The average probability of students’ mastery of the Japanese language points studied in the semester was above 0.6. The independent square root t-test for the two classes was less than 0.05, showing a significant difference.

Game-Theoretic Analysis of Fusion Rules Over Molecular Reporting Channels.

This work adopts a game theoretic approach to analyze the behavior of transmitter nanomachines (TNMs) in a diffusive 3-dimensional (3-D) channel. In order to communicate the local observations about the region of interest (RoI) to a common supervisor nanomachine (SNM), TNMs transmit information-carrying molecules to SNM. For the production of information-carrying molecules, all the TNMs share the common food molecular budget (CFMB). The TNMs apply cooperative and greedy strategic efforts to get their share from the CFMB. In the cooperative case, all the TNMs communicate to SNM as a group, therefore they cooperatively consume the CFMB to increase the group outcome, whereas, in the greedy scenario, all TNMs decide to perform alone and thus greedily consume the CFMB to increase their individual outcomes. The performance is evaluated in terms of the average rate of success, the average probability of error, and the receiver operating characteristic (ROC) of RoI detection. The derived results are verified through Monte-Carlo and particle-based simulations (PBS).

Analysis and Optimization of the Effectiveness of College Physical Education Courses Based on Fuzzy Cognitive Evaluation

Abstract Cognitive diagnostic theory can provide a comprehensive and detailed objective evaluation of individual macro learning ability, thus providing an effective reference for targeted teaching and learning. In this paper, a fuzzy cognitive diagnostic model is used to evaluate the degree of mastery of a college student on the physical education course, calculate the probability of mastery of each attribute, and statistically analyze the degree of mastery of the attributes of the individual as well as the class as a whole. Then, a learning effect evaluation standard is constructed to evaluate the learning effects of the physical education course for all students. The empirical results show that the mean value of the evaluation of the students’ cognition of physical education in School X is 0.6587, and the average probability of mastery of physical education emotion is 0.6021, both of which have reached the degree of good mastery. The average probability of mastering sports operations was 0.5909, which indicates that university students have an average level of mastery in all sports skills through the physical education program. The outcome is in line with the current situation, which can serve as a reference for teachers to make targeted teaching decisions. The study has both theoretical value and practical significance in promoting the development of wisdom education.

Dance movement error correction based on decision tree algorithm

Abstract In an environment where action recognition technology is widely used, dance action recognition technology has also received extensive attention. Due to the complexity of dance movements, there will be a large number of errors in dance movement recognition. Therefore, this paper uses the decision tree algorithm to optimize dance movement recognition. In this paper, the general framework of dance movement recognition is first constructed, and the human body features are extracted and calculated by using the Laban motion analysis method for the changes in the joints of dance movements. Then, use the decision tree algorithm to classify and identify the dance movements, and use it to optimize the self-obscuring motion information repair algorithm to solve the problem of dance movement occlusion and error, and complete the construction of the dance movement recognition model based on CNN network. Empirical analysis shows that the model method's Top-1 and Top-5 accuracy are both 84.7% and 89.32%, respectively. The average probability of incorrect recognition, error recognition, and correct recognition of the optimized dance action recognition in this paper is 8.84%, 3.78 and 87.38 respectively. The average recognition correctness is improved by 12.02%, which indicates that the effect of recognition of the optimized model of dance action masking and error correction in this paper is excellent. It has achieved a better construction in the field of dance action error correction.