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Research on dynamic time warping algorithm and intelligent financial management system based on heterogeneous cellular network

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SOFT COMPUTING 2023年 1-11页

作者： Lu, Mengqiu Wuhan Huaxia Inst Technol Dept Finance & Accounting Wuhan 430223 Hubei Peoples R China

This article focuses on user-centered site collaboration strategies. The main site collaboration of the collaboration framework is to provide services to target users. First, the same cellular network is modeled according to the same Poisson point process model to indicate the target user's radius formula;the energy consumption and user level of the collaboration set are related to the collaboration radius, and a specific user level is created. Solve the optimization problem with the lowest energy consumption in a set of collaborative requirements. And based on the traditional dynamic time warping algorithm (DTW) that deals with unequal length vectors in one-dimensional samples, this article focuses on the similarity between spatial two-dimensional matrix samples, improves research from different perspectives, and expands the construction of the processing matrix. The new algorithm of sample DTW is used to solve the problem of distance measurement between matrix samples and unequal size matrix samples. Based on the traditional dynamic time warping algorithm, a line-by-line DTW smart finance is proposed. The algorithm uses the distance matrix to calculate the DTW distance by calculating the DTW distance between the rows of the matrix samples, introduces the intermediate distance matrix, and uses the distance matrix to calculate the DTW distance. The standardized DTW distance is used as the final matrix distance. Multiple DTW distance calculations significantly improve the matrix samples. Finally, perform functional realization and system testing on the designed system, and confirm the normal operation of the financial management system based on the test results. This paper is mainly based on the dynamic time warping algorithm for heterogeneous cellular networks and applies it to the research of intelligent financial management system to improve the efficiency of financial management.

关键词： Heterogeneous cellular network dynamic time warping algorithm Intelligent finance Management system

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Evaluating ecosystem stability based on the dynamic time warping algorithm: A case study in the Minjiang river Basin, China

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ECOLOGICAL INDICATORS 2023年第1期154卷

作者： Ding, Hao Yuan, Zhe Yin, Jun Shi, Xiaoliang Shi, Mengqi Xian Univ Sci & Technol Coll Geomatics Xian 710054 Peoples R China Changjiang River Sci Res Inst Changjiang Water Resources Commiss Minist Water Re Wuhan 430010 Peoples R China Hubei Key Lab Water Resources & Ecoenvironm Sci Wuhan 430010 Peoples R China Hubei Univ Fac Resources & Environm Sci Dept Geog Sci Wuhan 430062 Peoples R China

With the ongoing impacts of global climate change, the cumulative stress effects of external disturbances on ecosystems are gradually strengthening. Therefore, it is very important to scientifically evaluate the stability of ecosystems. In the terrestrial ecosystems, vegetation serves as a link between the water, energy, and carbon cycles, and is an important index which allows for the measurement of ecosystem stability. In this study, two vegetation indices (normalized difference vegetation index and enhanced vegetation index), along with solarinduced chlorophyll fluorescence data from 2001 to 2021, were used to determine the external disturbance events in the Minjiang river basin using a dynamic time warping (DTW) algorithm. Analyses of the disturbance characteristics during this period, and quantification of the vegetation resistance, resilience, and vegetation regime shift rate were conducted. The results indicated the following. (1) The disturbance results monitored by the DTW algorithm were highly consistent with typical events, and it was feasible to monitor the disturbance of the Minjiang river basin using the DTW algorithm. (2) Disturbance intensity in the river basin increased slightly, while in urban areas it decreased. (3) The resistance of different types of vegetation varied greatly, with the resistance strongest in forests, next in croplands, and weakest in grasslands. In contrast, resilience was the strongest in croplands, next in grasslands, and weakest in forests. (4) The vegetation growth state of the river basin was more significantly affected by external disturbance in 2001-2021, with 58.75% of forest, 54.37% of grassland, and 37.21% of cropland having regime shift rates < 1. Lastly, (5) the response of vegetation to external disturbance was diverse under different disturbance scenarios, with the vegetation recovery rate under gradual disturbance being greater than the rate under abrupt disturbance.

关键词： Ecological system stability dynamic time warping algorithm Minjiang river basin Gradual disturbance Abrupt disturbance

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Application of image optical detection based on dynamic time warping algorithm in dance teaching

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OPTICAL AND QUANTUM ELECTRONICS 2024年第3期56卷 287-287页

作者： Huang, Hailing Zhu, Hongwen YuZhang Normal Univ Nanchang 330000 Jiangxi Peoples R China

With the continuous development of computer technology and the deepening of mathematical theory research, the combination of mathematics and computer pattern recognition technology has penetrated into various fields of scientific research and social production. In order to accurately detect and analyze students' movements in dance teaching, a new optical detection method is proposed in this study, which uses dynamic time distortion algorithm to accurately identify and analyze dance movements. The dynamic time warping algorithm is used to compare two time series and is applied to the detection of dance movements to realize the accurate identification and analysis of students' movements. The dance video data is collected and pre-processed into time series data, and then each time series is compared and analyzed using a dynamic time warping algorithm, and key movement features are extracted. Finally, the machine learning model is trained to classify and evaluate the students' movements. The experimental results show that the optical detection method based on dynamic time distortion algorithm can achieve high accuracy and precision in dance teaching. When applied to dance teaching, it has high accuracy and precision in detecting dance movements, which is expected to provide effective tools and support for dance teaching.

关键词： dynamic time warping algorithm Image optical detection Dance teaching Practical application

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Application of dynamic time warping optimization algorithm in speech recognition of machine translation

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HELIYON 2023年第11期9卷 e21625页

作者： Jiang, Shaohua Chen, Zheng Fujian Univ Technol Sch Humanities Fuzhou 350118 Peoples R China Krirk Univ Bangkok 10220 Thailand Fujian Normal Univ Concord Univ Coll Fuzhou Fujian Peoples R China

Speech recognition is the foundation of human-computer interaction technology and an important aspect of speech signal processing, with broad application prospects. Therefore, it is very necessary to recognize speech. At present, speech recognition has problems such as low recognition rate, slow recognition speed, and severe interference from other factors. This paper studied speech recognition based on dynamic time warping (DTW) algorithm. By introducing speech recognition, the specific steps of speech recognition were understood. Before performing speech recognition, the speech that needs to be recognized needs to be converted into a speech sequence using an acoustic model. Then, the DTW algorithm was used to preprocess speech recognition, mainly by sampling and windowing the speech. After preprocessing, speech feature extraction was carried out. After feature extraction was completed, speech recognition was carried out. Through experiments, it can be found that the recognition rate of speech recognition on the basis of DTW algorithm was very high. In a quiet environment, the recognition rate was above 93.85 %, and the average recognition rate of the 10 selected testers was 95.8 %. In a noisy environment, the recognition rate was above 91.4 %, and the average recognition rate of the 10 selected testers was 93 %. In addition to high recognition rate, DTW based speech recognition also had a very fast speed for vocabulary recognition. Based on the DTW algorithm, speech recognition not only has a high recognition rate, but also has a faster recognition speed.

关键词： Speech recognition dynamic time warping algorithm Feature extraction Deep learning algorithm

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Capacity Estimation of Serial Lithium-ion Battery Pack Using dynamic time warping algorithm

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IEEE ACCESS 2019年 7卷 174687-174698页

作者： Liu, Yang Zhang, Caiping Jiang, Jiuchun Jiang, Yan Zhang, Linjing Zhang, Weige Beijing Jiaotong Univ Natl Act Distribut Network Technol Res Ctr Beijing 100044 Peoples R China Shenzhen Precise Testing Technol Co Ltd Shenzhen 518108 Peoples R China

The existence of the consistency degradation of the battery pack hinders the accurate estimation of pack capacity and cell capacity in the battery pack. The paper focuses on the capacity estimation of cells in the serial battery pack. The shape invariance of the charging voltage curve is discussed and used as the theoretical foundation of cell capacity difference identification. The matching relationship between two voltage curves is obtained based on the dynamic time warping algorithm. Then the capacity difference identification algorithm to calculate the capacity difference between the two cells is proposed. Based on the algorithm, a three-step capacity estimation method is established. The proposed method can only use the previous charging curve of one cell in the pack and the current charging data of the battery pack to rapidly estimate the capacity of each cell in the battery pack. A 16 serial LiFePO4 battery pack is employed to verify the method. The result shows the estimation error of cell capacities is less than 3% rated capacity. With this method, the cell capacities in the pack can be rapidly and accurately estimated, providing a foundation for the consistency analysis and equalization of the battery pack.

关键词： Charging voltage curve dynamic time warping algorithm capacity estimation lithium-ion battery pack

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An automatic landmarking algorithm for leaf morphology based on conformal mapping

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COMPUTERS AND ELECTRONICS IN AGRICULTURE 2025年 234卷

作者： Zhong, Peige Liu, Xiaojun Ye, Yulu Zhang, Rui Zhou, Hu Guo, Yan Li, Baoguo Zhu, Jinyu Ma, Yuntao Chinese Acad Agr Sci Inst Vegetables & Flowers Beijing 100081 Peoples R China China Agr Univ Coll Land Sci & Technol Beijing 100091 Peoples R China China Agr Univ Coll Sci Beijing 100091 Peoples R China Chinese Acad Agr Sci Biotechnol Res Inst Beijing 100081 Peoples R China

Leaf shape is of great significance in plant phenotype research. Landmarks method is a widely used morphometric approach, which can comprehensively describe the morphological differences among leaves. However, the selection of landmarks is time-consuming and laborious. An automatic landmarking algorithm is proposed here. Based on conformal mapping, the leaf outline can be transformed into a monotonically increasing function curve, referred to as the 'fingerprint function'. The dynamic time warping (DTW) algorithm was introduced to match landmarks between different leaves. Two leaf datasets were used to validate the algorithm separately in different species and developmental stages. Dataset1 is a public dataset which covers 26 different types of leaves. The average positional difference between automatic and manual landmarks for dataset1 was only 2.95%. Dataset2 consists of cotton leaves collected in the field at various growth stages, and the positional difference for this dataset was all below 5%. These results validate that our algorithm is applicable to a wide range of leaf types and capable of identifying and locating novel features that emerge during leaf growth. The automatic landmarking algorithm can simulate manual landmarking to a great extent. It provides a new approach for automated acquisition of plant leaf shape homology tailored to the research needs of botanists.

关键词： Morphometric Conformal mapping dynamic time warping algorithm Leaf phenotyping Biological homology

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Measurement of micro-harmonic vibration frequency from the modulated self-mixed interferometric signal using dynamic time warping method

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MECHANICAL SYSTEMS AND SIGNAL PROCESSING 2022年 168卷 108712-108712页

作者： Bhardwaj, Vibhor Kumar Maini, Surita St Longowal Inst Engn & Technol Dept Elect & Instrumentat Engn Longowal 148106 Punjab India Bhagwant Inst Technol Dept Elect & Commun Engn Muzaffarnagar 251315 Uttar Pradesh India

The vibration frequency is one of the key factors that contains vital information about the subjects/machines and offers major analytical support. The contactless measurement of vibration frequency is the crucial requirement of many industrial, scientific, and biomedical applications like predictive maintenance, non-destructive testing, and reverse engineering, chest vibration, etc. The paper presents a self-mixed optical feedback interferometry (SM-OFI) sensor to measure the vibration frequency of the micro-harmonic vibrating surface. The method employs a dynamic time warping algorithm (DTW) to compute the Euclidian distance between the locally generated reference signal and the SM interferometric signal obtained from a vibrating target. The method is tested experimentally on a customized SM-OFI emitting a wavelength of 650 nm under weak feedback conditions. The proposed method was able to measure the unknown frequency with 98% accuracy in all sets of experiments. The method also exhibits an R-squared value of 0.99 with a relative error of less than unity. The comprehensive analysis of the experimental results concludes that the proposed method provides an accurate and precise vibration frequency measurement scheme for the low bandwidth range. This low bandwidth range measurement promises a non-contact measurement in industries and biomedical applications during the COVID-19 scenario.

关键词： Self-mixed effect Optical feedback dynamic time warping algorithm Vibration frequency measurement Euclidian distance

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Human Animation Model Generation in Traffic Accident Restoration: Human Action Recognition Based on Improved DTW algorithm

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IEEE ACCESS 2024年 12卷 107570-107582页

作者： Fang, Xiao Guo, Yuzhen Qingdao Agr Univ Sch Animat & Media Qingdao 266109 Peoples R China Liaocheng Univ Sch Media & Technol Liaocheng 252000 Shandong Peoples R China

Traffic accidents are a serious issue in modern society, causing significant personal and property damage. To better understand and prevent these accidents, traffic accident restoration technology has been developed. This study employs a multidimensional approach that includes improved dynamic time warping (DTW) algorithms, dynamic query sets, and Kinect technology. These methods focus on human animation model generation, deformation process design, and human motion recognition. The results demonstrated that the improved DTW algorithm outperformed traditional hidden Markov models, with an average accuracy of 0.92 after 1,000 iterations compared to 0.71. Additionally, the dynamic query set model excelled in computational complexity and time efficiency. The system's average thigh movement error ranged from 1.6 to 4.0 degrees, with a maximum error of 3.9 to 6.7 degrees and a median error of 1.8 to 3.9 degrees. The improved DTW algorithm maintained better integrity of joint point data in complex motion capture scenarios. The Alpha and Bravo data sets achieved 94.2% and 93.7% accuracy, respectively, significantly higher than the traditional DTW's 78.8% and 82.3%. The study of human animation model generation in the context of traffic accident restoration has the potential to have a significant impact across a range of fields, enhancing the scientific rigour and practical applicability of traffic accident restoration.

关键词： Accidents Heuristic algorithms Hidden Markov models Animation dynamics Human activity recognition Image restoration Traffic accidents human animation dynamic time warping algorithm human motion recognition dynamic query set

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Multi-Sensor Data Fusion Analysis for Tai Chi Action Recognition

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INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2024年第11期15卷 1054-1064页

作者： Ouyang, Jingying Zhang, Jisheng Zhao, Yuxin Yang, Changhuo Hunan Normal Univ Coll Phys Educ Changsha 410012 Peoples R China Hunan Univ Sch Business Changsha 410082 Peoples R China Cent South Univ Sch Comp Sci & Engn Changsha 410083 Peoples R China

The continuous development of action recognition technology can capture the decomposition data of Tai Chi movements, provide precise assistance for learners to correct erroneous movements and enhance their interest in practicing Tai Chi. Inertial sensors and human skeletal models are used to collect motion data. Combined with visual sensors, the motion and trajectory of Tai Chi are processed to obtain the relevant coordinate system of the movement trajectory. Then, the inertial sensor and visual sensor are fused for data processing to standardize the human skeleton model, remove noise interference from the collected information, and improve the smoothness performance of movement trajectories, thereby segmenting and clustering Tai Chi movement trajectories. Finally, the support vector machine and dynamic time-warping algorithm are combined to identify and verify the trajectory of Tai Chi movements. According to the results, in the 25%, 50%, and 75% training sample proportions, the lowest recognition accuracy of the Qi Shi movements was 90.87%, 93.53%, and 98.08%, respectively. The optimal recognition accuracy and standard deviation of single nodes in binary classification were 98.48% and 0.47%, respectively. The best recognition accuracy and standard deviation for multi-joint points in binary classification were 99.77% and 0.16%, respectively. This proves the recognition advantages of binary classification and the superiority of data fusion analysis based on multiple sensors, providing a theoretical basis and technical reference for action recognition technology.

关键词： Inertial sensor visual sensors segmentation clustering support vector machine dynamic time warping algorithm

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Coupling time and Non-time Series Models to Simulate the Flood Depth at Urban Flooded Area

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WATER RESOURCES MANAGEMENT 2023年第3期37卷 1275-1295页

作者： Wang, Hongfa Guan, Xinjian Meng, Yu Wu, Zening Wang, Kun Wang, Huiliang Zhengzhou Univ Coll Water Conservancy Engn Zhengzhou 450001 Henan Peoples R China China Inst Water Resources & Hydropower Res Dept Water Resources Beijing 100038 Peoples R China

The flood produced by short duration heavy rainfall events in cities will still exist after raining and continues to cause harm and impact. To accurately predict the depth and duration of the flood, a coupled model of the extreme gradient boosting and long short-term memory algorithms was proposed. A practical application of three representative flooded points in the Zhengzhou city, China, the results showed the coupled model could fit and forecast the flood. The average of Mean relative error, Nash-Sutcliffe efficiency coefficient and Qualified rate of validation data were 9.13%, 0.96 and 90.3% respectively, which verified the superiority of the method in the flood prediction. And the flood processes at the flooded points caused by design rainfall under different return periods were predicted by the coupled model. The growth rates of the flood duration and peak flood depth were all the highest during the return periods 1a-2a. This study proves that the coupled model has great potential in predictions of flood and could provide scientific basis guidance for disaster reduction.

关键词： Flood process XGBoost model dynamic time warping algorithm LSTM model Multiple rainfall scenarios

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