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한국정보처리학회> JIPS(Journal of Information Processing Systems)

JIPS(Journal of Information Processing Systems) update

  • : 한국정보처리학회
  • : 공학분야  >  전자공학
  • : KCI등재
  • : SCOPUS
  • : 연속간행물
  • : 격월
  • : 1976-913x
  • : 2092-805X
  • : International journal of information processing systems(~2007)→Journal of information processing system(2008~)

수록정보
18권4호(2022) |수록논문 수 : 12
간행물 제목
18권6호(2022년 12월) 수록논문
최근 권호 논문
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KCI등재 SCOPUS

저자 : Ruibo Ai , Cheng Li , Na Li

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 6호 발행 연도 : 2022 페이지 : pp. 719-728 (10 pages)

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The prediction of short-term traffic flow is the theoretical basis of intelligent transportation as well as the key technology in traffic flow induction systems. The research on short-term traffic flow prediction has showed the considerable social value. At present, the support vector regression (SVR) intelligent prediction model that is suitable for small samples has been applied in this domain. Aiming at parameter selection difficulty and prediction accuracy improvement, the artificial bee colony (ABC) is adopted in optimizing SVR parameters, which is referred to as the ABC-SVR algorithm in the paper. The simulation experiments are carried out by comparing the ABC-SVR algorithm with SVR algorithm, and the feasibility of the proposed ABC-SVR algorithm is verified by result analysis. Continuously, the simulation experiments are carried out by comparing the ABC-SVR algorithm with particle swarm optimization SVR (PSO-SVR) algorithm and genetic optimization SVR (GA-SVR) algorithm, and a better optimization effect has been attained by simulation experiments and verified by statistical test. Simultaneously, the simulation experiments are carried out by comparing the ABC-SVR algorithm and wavelet neural network time series (WNN-TS) algorithm, and the prediction accuracy of the proposed ABC-SVR algorithm is improved and satisfactory prediction effects have been obtained.

KCI등재 SCOPUS

저자 : Suman Pandey , Yang-sae Moon , Mi-jung Choi

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 6호 발행 연도 : 2022 페이지 : pp. 729-740 (12 pages)

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Netflix, Amazon Prime, and YouTube are the most popular and fastest-growing streaming services globally. It is a matter of great interest for the streaming service providers to preview their service infrastructure and streaming strategy in order to provide new streaming services. Hence, the first part of the paper presents a detailed survey of the Content Distribution Network (CDN) and cloud infrastructure of these service providers. To understand the streaming strategy of these service providers, the second part of the paper deduces a common quality-of-service (QoS) model based on rebuffering time, bitrate, progressive download ratio, and standard deviation of the On-Off cycle. This model is then used to analyze and compare the streaming behaviors of these services. This study concluded that the streaming behaviors of all these services are similar as they all use Dynamic Adaptive Streaming over HTTP (DASH) on top of TCP. However, the amount of data that they download in the buffering state and steady-state vary, resulting in different progressive download ratios, rebuffering levels, and bitrates. The characteristics of their On-Off cycle are also different resulting in different QoS. Hence a thorough adaptive bit rate (ABR) analysis is presented in this paper. The streaming behaviors of these services are tested on different access network bandwidths, ranging from 75 kbps to 30 Mbps. The survey results indicate that Netflix QoS and streaming behavior are significantly consistent followed by Amazon Prime and YouTube. Our approach can be used to compare and contrast the streaming services' strategies and fine-tune their ABR and flow control mechanisms.

KCI등재 SCOPUS

저자 : Youngjong Kim , Sungil Jang , Myung Ho Kim , Jinho Park

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 6호 발행 연도 : 2022 페이지 : pp. 741-754 (14 pages)

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Openstack is widely used as a representative open-source infrastructure of the service (IaaS) platform. The Openstack Identity Service is a centralized approach component based on the token including the Memcached for cache, which is the in-memory key-value store. Token validation requests are concentrated on the centralized server as the number of differently encrypted tokens increases. This paper proposes the practical Byzantine fault tolerance (PBFT) blockchain-based Openstack Identity Service, which can improve the performance efficiency and reduce security vulnerabilities through a PBFT blockchain framework-based decentralized approach. The experiment conducted by using the Apache JMeter demonstrated that latency was improved by more than 33.99% and 72.57% in the PBFT blockchain-based Openstack Identity Service, compared to the Openstack Identity Service, for 500 and 1,000 differently encrypted tokens, respectively.

KCI등재 SCOPUS

저자 : Zhe Zhang , Yongchang Zhang

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 6호 발행 연도 : 2022 페이지 : pp. 755-762 (8 pages)

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The existing electrical engineering design method and the dynamic objective function in the application process of automatic control system fail to meet the unbounded condition, which affects the control tracking accuracy. In order to improve the tracking control accuracy, this paper studies the electrical engineering design method based on neural network and the application of automatic control system. This paper analyzes the structure and working mechanism of electrical engineering automation control system by an automation control model with main control objectives. Following the analysis, an optimal solution of controllability design and fault-tolerant control is figured out. The automatic control power coefficient is distributed based on an ideal control effect of system. According to the distribution results, an automatic control algorithm is based on neural network for accurate control. The experimental results show that the electrical automation control method based on neural network can significantly reduce the control following error to 3.62%, improve the accuracy of the electrical automation tracking control, thus meeting the actual production needs of electrical engineering automation control system.

KCI등재 SCOPUS

저자 : Xia Wei

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 6호 발행 연도 : 2022 페이지 : pp. 763-769 (7 pages)

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Transportation allocation requires information such as storage location and order information. In order to guarantee the safe transmission and real-time sharing of information in all links, an intelligent transportation control system based on blockchain technology is designed. Firstly, the technical architecture of intelligent transportation information traceability blockchain and the overall architecture of intelligent transportation control system were designed. Secondly, the transportation management demand module and storage demand management module were designed, and the control process of each module was given. Then, the type of intelligent transportation vehicle was defined, the objective function of intelligent transportation control was designed, and the objective function of intelligent transportation control was constructed. Finally, the intelligent transportation control was realized by genetic algorithm. It was found that when the transportation order volume was 50×103, and the CPU occupancy of the designed system was only 11.8%. The reliability attenuation of the code deletion scheme was lower, indicating better performance of the designed system.

KCI등재 SCOPUS

저자 : Taiyo Ichinose , Tomoya Kawakami

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 6호 발행 연도 : 2022 페이지 : pp. 770-783 (14 pages)

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Early evacuations reduce the damage caused by catastrophic events such as terrorism, tsunamis, heavy rains, landslides, and river floods. However, even when warnings are issued, people do not easily evacuate during these events. To shorten the evacuation time, initiative-evacuation and its executors, initiative evacuees, are crucial in inducing other evacuations. The initiative evacuees take the initiative in evacuating and call out to their surroundings. This paper proposes a fast method to induce initiative-evacuation based on social graphs. The candidates are determined in descending order of the number of links for each person. The proposed method was evaluated through simulations. The simulation results showed a significant reduction in evacuation time.

KCI등재 SCOPUS

저자 : Jiyong Jin

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 6호 발행 연도 : 2022 페이지 : pp. 784-793 (10 pages)

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Grid-connected distributed power generation has been widely used in green energy generation. However, due to the distributed characteristics, distributed power generation is difficult to be dynamically allocated and monitored in the electrical control process. In order to solve this problem, this research combined the Internet of Things (IoT) with the automatic control system of electrical engineering to improve the control strategy of the power grid inverter according to the characteristics of the IoT system. In the research, a connection system of the power grid inverter and the IoT controller were designed, and the application effect was tested by simulation experiments. The results showed that the power grid inverter had strong tracking control ability for current and power control. Meanwhile, the electrical control system of the IoT could independently and dynamically control the three-phase current and power. The given value was reached within 50 ms after the step signal was input, which could protect the power grid from being affected by the current. The overall system could realize effective control, dynamic control and protective control.

KCI등재 SCOPUS

저자 : Huihui Xu , Fei Li

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 6호 발행 연도 : 2022 페이지 : pp. 794-802 (9 pages)

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The recovery of reasonable depth information from different scenes is a popular topic in the field of computer vision. For generating depth maps with better details, we present an efficacious monocular depth prediction framework with coordinate attention and feature fusion. Specifically, the proposed framework contains attention, multi-scale and feature fusion modules. The attention module improves features based on coordinate attention to enhance the predicted effect, whereas the multi-scale module integrates useful low- and high-level contextual features with higher resolution. Moreover, we developed a feature fusion module to combine the heterogeneous features to generate high-quality depth outputs. We also designed a hybrid loss function that measures prediction errors from the perspective of depth and scale-invariant gradients, which contribute to preserving rich details. We conducted the experiments on public RGBD datasets, and the evaluation results show that the proposed scheme can considerably enhance the accuracy of depth prediction, achieving 0.051 for log10 and 0.992 for δ<1.253 on the NYUv2 dataset.

KCI등재 SCOPUS

저자 : Yoonjeong Choi , Yujin Lim

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 6호 발행 연도 : 2022 페이지 : pp. 803-812 (10 pages)

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With the increasing number of mobile device users worldwide, utilizing mobile edge computing (MEC) devices close to users for content caching can reduce transmission latency than receiving content from a server or cloud. However, because MEC has limited storage capacity, it is necessary to determine the content types and sizes to be cached. In this study, we investigate a caching strategy that increases the hit ratio from small base stations (SBSs) for mobile users in a heterogeneous network consisting of one macro base station (MBS) and multiple SBSs. If there are several SBSs that users can access, the hit ratio can be improved by reducing duplicate content and increasing the diversity of content in SBSs. We propose a Deep Q-Network (DQN)-based caching strategy that considers time-varying content popularity and content redundancy in multiple SBSs. Content is stored in the SBS in a divided form using maximum distance separable (MDS) codes to enhance the diversity of the content. Experiments in various environments show that the proposed caching strategy outperforms the other methods in terms of hit ratio.

KCI등재 SCOPUS

저자 : Husheng Zhou

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 6호 발행 연도 : 2022 페이지 : pp. 813-821 (9 pages)

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Intelligent monitoring, life entertainment, medical rehabilitation, and other fields are only a few examples where visual image technology is becoming increasingly sophisticated and playing a significant role. Recognizing Wushu, or martial arts, movements through the use of visual image technology helps promote and develop Wushu. In order to segment and extract the signals of Wushu movements, this study analyzes the denoising of the original data using the wavelet transform and provides a sliding window data segmentation technique. Wushu movement The Wushu movement recognition model is built based on the hidden Markov model (HMM). The HMM model is trained and taught with the help of the Baum-Welch algorithm, which is then enhanced using the frequency weighted training approach and the mean training method. To identify the dynamic Wushu movement, the Viterbi algorithm is used to determine the probability of the optimal state sequence for each Wushu movement model. In light of the foregoing, an HMM-based martial arts movements recognition model is developed. The recognition accuracy of the HMM model increases to 99.60% when the number of samples is 4,000, which is greater than the accuracy of the SVM (by 0.94%), the CNN (by 1.12%), and the BP (by 1.14%). From what has been discussed, it appears that the suggested system for detecting martial arts acts is trustworthy and effective, and that it may contribute to the growth of martial arts.

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KCI등재SCOUPUS

저자 : Li Gong , Xuelei Gong , Ying Liang , Bingzong Zhang , Yiqun Yang

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 4호 발행 연도 : 2022 페이지 : pp. 457-469 (13 pages)

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Hydraulic concrete buildings in the northwest of China are often subject to the combined effects of low-temperature frost damage, during drying and wetting cycles, and salt erosion, so the study of concrete deterioration prediction is of major importance. The prediction model of the relative dynamic elastic modulus (RDEM) of four different kinds of modified concrete under the special environment in the northwest of China was established using Grey residual Markov theory. Based on the available test data, modified values of the dynamic elastic modulus were obtained based on the Grey GM(1,1) model and the residual GM(1,1) model, combined with the Markov sign correction, and the dynamic elastic modulus of concrete was predicted. The computational analysis showed that the maximum relative error of the corrected dynamic elastic modulus was significantly reduced, from 1.599% to 0.270% for the BS2 group. The analysis error showed that the model was more adjusted to the concrete mixed with fly ash and mineral powder, and its calculation error was significantly lower than that of the rest of the groups. The analysis of the data for each group proved that the model could predict the loss of dynamic elastic modulus of the deterioration of the concrete effectively, as well as the number of cycles when the concrete reached the damaged state.

KCI등재SCOUPUS

저자 : Jia Lim

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 4호 발행 연도 : 2022 페이지 : pp. 470-479 (10 pages)

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Mukbang is a type of foodcasting where a host records or streams their eating rituals for audience consumption in live format. With origins in South Korea via the online broadcast genre found on Afreeca TV in the mid- 2000s, the phenomenon has since found global popularity. Its development as a full-fledged genre is based on a communication culture that invites people to a meal rather than to talk to one another; viewers watch in silence as a host consumes a copious number of dishes from Korean gastronomy to fast food to other ethnic cuisine on display. An invitation to eat means the beginning of a public relationship that quickly turns to a private shared experience. This study analyzes several Mukbang video postings and makes use of Linden's culture approach model to provide a view toward a number of cross-cultural connections by Koreans and non-Korean audiences. Prior to the study, 10 Korean eating shows were selected and used as standard models. Korean Mukbang mainly consists of eating behavior and ASMR, with very few storytelling or narrative devices utilized by its creators. For this reason, eating shows make a very private connection. In other ways, this paper shows how 28 Mukbangrelated YouTube contents selected by Ranker were evolving and examined through notions of acculturation and reception theory.

KCI등재SCOUPUS

저자 : Yuxiang Shan , Qin Ren , Cheng Wang , Xiuhui Wang

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 4호 발행 연도 : 2022 페이지 : pp. 480-488 (9 pages)

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Images of tobacco retail licenses have complex unstructured characteristics, which is an urgent technical problem in the robot process automation of tobacco marketing. In this paper, a novel recognition approach using a double attention mechanism is presented to realize the automatic recognition and information extraction from such images. First, we utilized a DenseNet network to extract the license information from the input tobacco retail license data. Second, bi-directional long short-term memory was used for coding and decoding using a continuous decoder integrating dual attention to realize the recognition and information extraction of tobacco retail license images without segmentation. Finally, several performance experiments were conducted using a largescale dataset of tobacco retail licenses. The experimental results show that the proposed approach achieves a correction accuracy of 98.36% on the ZY-LQ dataset, outperforming most existing methods.

KCI등재SCOUPUS

저자 : Hee-hyun Kim , Jinho Yoo

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 4호 발행 연도 : 2022 페이지 : pp. 489-499 (11 pages)

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Recently, the number of Internet of Things (IoT) devices has been increasing exponentially. These IoT devices are directly connected to the internet to exchange information. IoT devices are becoming smaller and lighter. However, security measures are not taken in a timely manner compared to the security vulnerabilities of IoT devices. This is often the case when the security patches cannot be applied to the device because the security patches are not adequately applied or there is no patch function. Thus, security vulnerabilities continue to exist, and security incidents continue to increase. In this study, we classified and analyzed the most common security vulnerabilities for IoT devices and identify the essential vulnerabilities of IoT devices that should be considered for security when producing IoT devices. This paper will contribute to reducing the occurrence of security vulnerabilities in companies that produce IoT devices. Additionally, companies can identify vulnerabilities that frequently occur in IoT devices and take preemptive measures.

KCI등재SCOUPUS

저자 : Fang Dou

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 4호 발행 연도 : 2022 페이지 : pp. 500-509 (10 pages)

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With the rapid development of educational informatization, teaching methods become diversified characteristics, but a large number of information data restrict the evaluation on teaching subject and object in terms of the effect of English education. Therefore, this study adopts the concept of incremental learning and eigenvalue interval algorithm to improve the weighted decision tree, and builds an English education effect evaluation model based on association rules. According to the results, the average accuracy of information classification of the improved decision tree algorithm is 96.18%, the classification error rate can be as low as 0.02%, and the anti-fitting performance is good. The classification error rate between the improved decision tree algorithm and the original decision tree does not exceed 1%. The proposed educational evaluation method can effectively provide early warning of academic situation analysis, and improve the teachers' professional skills in an accelerated manner and perfect the education system.

KCI등재SCOUPUS

저자 : Chao Wang , Xiao Jianliang , Cheng Zhang

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 4호 발행 연도 : 2022 페이지 : pp. 510-523 (14 pages)

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Considering the problems of poor control effect, weak disturbance rejection ability and adaptive ability of twowheeled self-balanced robot (TWSBR) systems on undulating roads, this paper proposes a fuzzy neural network active disturbance rejection controller (FNNADRC), that is based on fuzzy neural network (FNN) for online correction of active disturbance rejection controller (ADRC)'s nonlinear control rate. Firstly, the dynamic model of the TWSBR is established and decoupled, the extended state observer (ESO) is used to compensate dynamically and linearize the upright and displacement subsystems. Then, the nonlinear PD control rate and FNN are designed, and the FNN is used to modify the control parameters of the nonlinear PD control rate in real time. Finally, the proposed control strategy is simulated and compared with the traditional ADRC and fuzzy active disturbance rejection controller (FADRC). The simulation results show that the control effect of the proposed control strategy is slightly better than ADRC and FADRC.

KCI등재SCOUPUS

저자 : Min-seok Jo , Seong-soo Han , Chang-sung Jeong

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 4호 발행 연도 : 2022 페이지 : pp. 524-534 (11 pages)

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In this paper, we produce Trash Object Detection (TOD) dataset to solve trash detection problems. A wellorganized dataset of sufficient size is essential to train object detection models and apply them to specific tasks. However, existing trash datasets have only a few hundred images, which are not sufficient to train deep neural networks. Most datasets are classification datasets that simply classify categories without location information. In addition, existing datasets differ from the actual guidelines for separating and discharging recyclables because the category definition is primarily the shape of the object. To address these issues, we build and experiment with trash datasets larger than conventional trash datasets and have more than twice the resolution. It was intended for general household goods. And annotated based on guidelines for separating and discharging recyclables from the Ministry of Environment. Our dataset has 10 categories, and around 33K objects were annotated for around 5K images with 1280×720 resolution. The dataset, as well as the pre-trained models, have been released at https://github.com/jms0923/tod.

KCI등재SCOUPUS

저자 : Cunli Mao , Zhibo Man , Zhengtao Yu , Xia Wu , Haoyuan Liang

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 4호 발행 연도 : 2022 페이지 : pp. 535-548 (14 pages)

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Using a rich resource language to classify sentiments in a language with few resources is a popular subject of research in natural language processing. Burmese is a low-resource language. In light of the scarcity of labeled training data for sentiment classification in Burmese, in this study, we propose a method of transfer learning for sentiment analysis of a language that uses the feature transfer technique on sentiments in English. This method generates a cross-language word-embedding representation of Burmese vocabulary to map Burmese text to the semantic space of English text. A model to classify sentiments in English is then pre-trained using a convolutional neural network and an attention mechanism, where the network shares the model for sentiment analysis of English. The parameters of the network layer are used to learn the cross-language features of the sentiments, which are then transferred to the model to classify sentiments in Burmese. Finally, the model was tuned using the labeled Burmese data. The results of the experiments show that the proposed method can significantly improve the classification of sentiments in Burmese compared to a model trained using only a Burmese corpus.

KCI등재SCOUPUS

저자 : Makara Mao , Sony Peng , Yixuan Yang , Doo-soon Park

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 4호 발행 연도 : 2022 페이지 : pp. 549-561 (13 pages)

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In the Khmer writing system, the Khmer script is the official letter of Cambodia, written from left to right without a space separator; it is complicated and requires more analysis studies. Without clear standard guidelines, a space separator in the Khmer language is used inconsistently and informally to separate words in sentences. Therefore, a segmented method should be discussed with the combination of the future Khmer natural language processing (NLP) to define the appropriate rule for Khmer sentences. The critical process in NLP with the capability of extensive data language analysis necessitates applying in this scenario. One of the essential components in Khmer language processing is how to split the word into a series of sentences and count the words used in the sentences. Currently, Microsoft Word cannot count Khmer words correctly. So, this study presents a systematic library to segment Khmer phrases using the bi-directional maximal matching (BiMM) method to address these problematic constraints. In the BiMM algorithm, the paper focuses on the Bidirectional implementation of forward maximal matching (FMM) and backward maximal matching (BMM) to improve word segmentation accuracy. A digital or prefix tree of data structure algorithm, also known as a trie, enhances the segmentation accuracy procedure by finding the children of each word parent node. The accuracy of BiMM is higher than using FMM or BMM independently; moreover, the proposed approach improves dictionary structures and reduces the number of errors. The result of this study can reduce the error by 8.57% compared to FMM and BFF algorithms with 94,807 Khmer words.

KCI등재SCOUPUS

저자 : Mingfeng Zhao

발행기관 : 한국정보처리학회 간행물 : JIPS(Journal of Information Processing Systems) 18권 4호 발행 연도 : 2022 페이지 : pp. 562-574 (13 pages)

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As traditional ways of evaluation prove to be ineffective in evaluating the effect of interactive multimedia physical education (PE) teaching, this study develops a new evaluation model based on the simulated annealing algorithm. After the evaluation subjects and the principle of the evaluation system are determined, different subjects are well chosen to constitute the evaluation system and given the weight. The backpropagation neural network has been improved through the simulated annealing algorithm, whose improvement indicates the completion of the evaluation model. Simulation results show that the evaluation model is highly efficient. Compared with traditional evaluation models, the proposed one enhances students' performance in PE classes by 50%.

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