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YOLOv8 algorithm Improvement and Its Application in Small Target Detection

TRAITEMENT DU SIGNAL 2025年第2期42卷 985-994页

作者： Gao, Lu Zhao, Junwei Bohai Univ Coll Phys Sci & Technol Jinzhou 121000 Peoples R China North China Inst Sci & Technol Coll Comp Sci & Technol Langfang 065201 Peoples R China

In the trend of the continuous development of AI, the application range of small target detection (STD) is very wide. Improving the accuracy of small target detection is the focus of research, which has positive significance for the improvement of computer vision technology and multiple application scenarios. Based on the overall structure of YOLOv8 network, this paper introduces the deformable convolution and attention mechanism of DCNv4 to improve it. DCNv4 enhances the ability of the network to capture spatial structure, especially for objects of different scales or positions, so that the kernel can sample from any position in the input feature map, which can improve the performance of small target detection to a certain extent. The attention mechanism improves the ability of the network to focus on the key information in the detection task, and improves the efficiency and accuracy of the network detection. The experimental results show that the improved YOLOv8 algorithm significantly improves the detection performance of small targets, and achieves a good balance between detection accuracy and computational efficiency.

关键词： YOLOv8 small target detection (STD) improved algorithm DCNv4 deformable convolution attention mechanism

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An image layered scrambling encryption algorithm based on a novel discrete chaotic map

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IET IMAGE PROCESSING 2023年第2期17卷 518-532页

作者： Tang, Jianeng Zhang, Zezong Chen, Peiyang Zhang, Feng Ni, Hui Huang, Zhongming Huaqiao Univ Coll Engn Quanzhou Peoples R China Huaqiao Univ Coll Informat Sci & Engn Xiamen Peoples R China Fujian MM Elect Co Ltd Quanzhou Peoples R China

At present, the image encryption algorithm based on the bit-plane has the problem that the encryption speed and the encryption effect cannot be well balanced. To address the problem, an image layered scrambling encryption algorithm is proposed in this paper. First, a new one-dimensional Cosine Logistic compound chaotic map (1DCLC) is proposed. Several characteristics of the new chaotic map are analyzed by using various measures, such as bifurcation diagram, Lyapunov exponent, sample entropy etc. And the results show that the novel chaotic map has a better chaotic performance. Second, based on the chaotic map, an image encryption algorithm is proposed. The algorithm first performs an XOR encryption operation on the image. Second, the layered scrambling is applied to the XOR encrypted image. Then the layered and scrambled image is recombined for the second XOR encryption operation. In particular, in the layered scrambling, not only can the position of the pixel be changed but also the value of the pixel can be modified, which improves the security of the algorithm. In addition, in order to defend against various plaintext attacks and increase the security of the overall algorithm, the Hash function is introduced to update the key of the proposed algorithm. Finally, the original algorithm is improved and the improved algorithm's ability to resist differential attacks is analyzed. The experimental simulation and security test results show that the proposed encryption algorithm has a comparable encryption effect and a faster encryption speed.

关键词： XOR encryption operation improved algorithm Cryptography image layered scrambling novel chaotic map chaotic performance image encryption algorithm Optical, image and video signal processing faster encryption speed Computer vision and image processing techniques chaos image processing XOR encrypted image Data security entropy one-dimensional Cosine Logistic compound chaotic map novel discrete chaotic map comparable encryption effect bifurcation cryptography layered scrambled image

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Research on Security Situation Assessment and Prediction Model of Network System in Deep Learning Environment

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Journal of Mobile Multimedia 2024年第6期13卷 1263-1282页

作者： Xiao, Li Pan, TianHeng Wu, Xiaoling Zhu, YouKang School of computer science and technology Wuhan University of Bioengineering Hubei Wuhan 430010 China

With the development of the Internet, the network environment is increasingly complex, and the problem of network security is increasingly serious. Traditional passive network security technology has been unable to meet people’s current security needs, in this context, network security situation awareness arises at the historic moment. NSSA technology makes the traditional passive security into active security, from the analysis of unilateral elements to the analysis of the overall security. As key technology of situation perception, security situation assessment and prediction can evaluate and predict the network security situation at the overall level, help network security managers understand the overall network security changes and take protective measures in advance when predicting the dangerous state, which has important research significance. This paper mainly studies the situation assessment and prediction technology of network security, and puts forward the improved model and algorithm, which improves accuracy of situation assessment and prediction results. Prediction accuracy reaches 97.86%, and the efficiency of the situation assessment reaches 98.22%. © 2024 River Publishers.

关键词： improved algorithm prediction model Situation assessment situation prediction

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Research on robot path planning based on sparrow search algorithm integrating multiple strategies 5

Research on robot path planning based on sparrow search algo...

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5th International Conference on Computer Engineering and Application (ICCEA)

作者： Bian, Jinxin Li, Siyang Zheng, Xiaojun Liu, Congjian Dalian Jiaotong Univ Sch Mech Engn Dalian Peoples R China

ISBN: (纸本)9798350386783;9798350386776

The sparrow search algorithm (SSA) has some problems in the research of robot obstacle avoidance. It is difficult to jump out of the local optimum in advance, the initial population distribution is not wide enough, and the search accuracy is low. An improved sparrow search algorithm (Sparrow Search algorithm Combining Butterfly Search and Triangle Walk,BTSSA) is proposed by introducing a cubic chaotic map to obtain the initial population, introducing a butterfly algorithm and a triangular step strategy to update the individual position, and using a cubic spline curve method to smooth the path.

关键词： Sparrow search algorithm Path planning Mobile robot improved algorithm

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The Research on Analyzing Risk Factors of Type 2 Diabetes Mellitus Based on improved Apriori algorithm

The Research on Analyzing Risk Factors of Type 2 Diabetes Me...

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2015 4th International Conference on Computer, Mechatronics, Control and Electronic Engineering (ICCMCEE 2015)

作者： Wang yuzhen Jiang donghong Wei Zhe Ye Guangjian Lanzhou General Hospital Lanzhou Military Area Command School of Electrical Engineering and Information Engineering Lanzhou University of Technology

ISBN: (纸本)9781510813465

Purpose: We do it to improve the efficiency of analyzing risk factors of Type 2 Diabetes. Method: We use the patients' data from the information department of one tertiary referral hospital in Lanzhou which include course note of disease and their health record form January 2009 to March *** find out one improved algorithm applies to analyze risk factors of Type 2 Diabetes based on original Apriori algorithm and it's requirement. And we analyze the efficiency by programming both of the algorithms with C#. Result: We can analyze the chart of frequent item and support degree, time and number of records, time and support degree. Conclusion: This new improved Apriori algorithm has a high efficiency in analyzing risk factors of Type 2 Diabetes.

关键词： data mining Apriori algorithm association rules improved algorithm

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Utilizing complex networks and multi-scale analysis for spatial coordination and regional integration: Insight from the Pearl River Delta, China

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HABITAT INTERNATIONAL 2025年 161卷

作者： Fang, Chenyu Chen, Ran Zhou, Lin Liu, Xing Ge, Shidong Chinese Univ Hong Kong Inst Space & Earth Informat Sci Hong Kong Peoples R China Tech Univ Munich Dept Aerosp & Geodesy Professorship Big Geospatial Data Management D-85521 Munich Germany Northwest A&F Univ Coll Landscape Architecture & Arts Yangling 712100 Peoples R China Univ Massachusetts Amherst Sch Publ Policy Amherst MA 01003 USA Univ Massachusetts Amherst Dept Environm Conservat Amherst MA 01003 USA China Acad Urban Planning & Design Shenzhen Shenzhen 518055 Guangdong Peoples R China Henan Agr Univ Coll Landscape Architecture & Art Zhengzhou 450002 Peoples R China

The megaregion significantly influences spatial coordination and regional integration through complex interactions among cities;however, gaps persist in determining the roles of various administrative levels and in harnessing these interactions to facilitate regional integration. By integrating high-resolution mobile phone signaling data within a novel macro-meso-micro analytical framework, the study incorporates Degree Centrality, an improved Louvain algorithm modified to address the Matthew Effect (iLAME), and a Weighted and Normalized Gould-Fernandez (WNGF) to assess the influential roles, spatial structure, and brokerage interactions within the PRD. The result at the macro-level highlights regional imbalances within the PRD, notably the spatial mismatch between job opportunities and residential locations. At the meso-level, the community grouping result reveals discrepancies between administrative boundaries and actual community structures, suggesting that urban development has transcended traditional administrative limits. At the micro-level, the analysis accentuates the importance of brokerage roles played by multi-level administrative units. This comprehensive analysis underscores the necessity of constructing efficient transportation networks and reducing institutional distances to foster regional integration within the PRD.

关键词： Multi-scale analysis Pearl River Delta improved algorithm Big data Megaregional network

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Credit system of smart logistics public information platform based on improved neural network

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NEURAL COMPUTING & APPLICATIONS 2021年第9期33卷 3987-4000页

作者： Zhang, Huifeng Jin, Yanfeng Shijiazhuang Posts & Telecommun Tech Coll Shijiazhuang 050021 Hebei Peoples R China

In-depth discussion and research on the credit issues of the logistics industry are not only of vital significance to the in-depth development of the logistics industry, but also have a significant impact on the sustainable development of the entire logistics industry and even the Chinese economy. This paper combines machine learning algorithms to improve the neural network and builds a credit system for the smart logistics public information platform. When studying the credit evaluation index system of logistics enterprises, the majority of logistics consumers are used as the evaluation subject, and the logistics users are surveyed, and the initial index system established is scored. Then, the method of factor analysis is used to sort and analyze the results of the questionnaire and determine the final evaluation index. In addition, according to the development of logistics enterprises themselves, this paper uses the analytic hierarchy process to evaluate the credit ratings of logistics enterprises from the perspectives of logistics enterprise customers and managers. This will be more authentic and convincing for the evaluation results.

关键词： Neural network improved algorithm Smart logistics Public information platform Credit system

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Research on business English autonomous learning based on artificial intelligence and improved BP network model

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2021年第4期40卷 7159-7170页

作者： Chen, Zijuan Lian, Ying Lin, Zhipeng Fujian Forestry Vocat Tech Coll Dept Art & Media Fujian Forestry Nanping Fujian Peoples R China Fujian Forestry Vocat Tech Coll Dept Automat Engn Nanping Fujian Peoples R China

Due to various factors, the learning process of business English is mostly autonomous learning. However, the traditional autonomous learning model is difficult to effectively improve the learning effect of business English. In order to improve the business English learning model, based on artificial intelligence and improved BP network model, this paper builds a business intelligence autonomous learning system with certain intelligence. Moreover, this paper designs functional modules for the characteristics of business English learners, and combines the self-learning needs to facilitate the processing of structural functions, so that students can complete the operation independently. The system sets up multiple functional modules, conducts guided recommendation learning according to the characteristics of the self-learning process, and combines the feedback system to correct the shortcomings in students' autonomous learning. Through this system, teachers can perform a variety of operations offline and eliminate restrictions on location and teaching time. In addition, in order to verify the performance of the model, the experimental study was conducted by setting up a control group and an experimental group. The research results show that the model constructed in this paper has good performance.

关键词： Artificial intelligence improved algorithm BP neural network business English

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Model of corporate bond spread based on improved neural network

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2021年第4期40卷 6605-6615页

作者： Luo, Qiaoshun Liu, Xinping Xinjiang Agr Univ Management Sch Urumqi Xinjiang Peoples R China

The reasons for credit spreads can be divided into enterprise-specific non-systematic risks and widespread macroeconomic systemic risks. The previous traditional research mainly focused on the perspective of unsystematic risk. However, at present, more and more scholars are beginning to focus on systemic risks. Based on the neural network algorithm, this paper constructs an improved neural network-based corporate bond spread model to explore the impact of macro systemic risks on credit spreads. Based on the multi-factor no-arbitrage model, the linear relationship between the credit spread and the risk premium of each factor is obtained. At the same time, based on previous research results and observations of the current market reality, this paper identifies five important macroeconomic factors: actual economic output factors, inflation factors, stock market volatility factors, stock market return factors and inter-bank funding factors. The research results show that the model constructed in this paper has excellent performance.

关键词： Neural network improved algorithm corporate bond spread model model simulation

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Fault diagnosis of new energy vehicles based on improved machine learning

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SOFT COMPUTING 2021年第18期25卷 12091-12106页

作者： Liu, Haichao Song, Xiaona Zhang, Fagui North China Univ Water Resource & Elect Power Sch Mech Engn Zhengzhou Peoples R China Ningbo Geely Royal Engine Components Co Ltd Engine Proc Dept Ningbo Zhejiang Peoples R China

The new energy vehicle system is in the initial stage of application, so the probability of fault is greater. Therefore, its reliability urgently needs to be improved. In order to improve the fault diagnosis effect of new energy vehicles, this paper proposes a fault diagnosis system of new energy vehicle electric drive system based on improved machine learning and also proposes several typical fault detection and diagnosis methods. Through the study of the operating characteristics and structural characteristics of the electric drive system and the analysis of the fault mechanism, this paper classifies the main faults of the electric drive system according to the self-test requirements of the electric drive system and the online diagnosis requirements and presents the self-test fault tree and online diagnosis fault tree of the electric drive system. In addition, this paper designs experiments to verify the performance of the system proposed by this paper, simulates the current common system fault conditions, and uses the system constructed in this paper to perform system fault diagnosis. The research results show that the performance of the fault diagnosis system for drive energy vehicles constructed in this paper is reliable.

关键词： Machine learning improved algorithm New energy vehicle Fault diagnosis

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