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1

Huang, Feifan. "The Research Progress of Path Planning Algorithms." Highlights in Science, Engineering and Technology 63 (August 8, 2023): 216–21. http://dx.doi.org/10.54097/hset.v63i.10879.

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At present, path-planning for mobile robots is a hot problem. In the previous scientific research, A*, Dijkstra, rapidly-exploring random tree (RRT) and many other algorithms have appeared. To provide a clearer understanding of these algorithms, this article organized the idea and development of Q-learning, A* algorithm, ant colony algorithm, RRT algorithm and Dijkstra algorithm. According to the time order, this article researched several applications of the five algorithms respectively. Besides, optimization of the five algorithms in the past few years were listed. There are also examples of
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Dan Liu, Dan Liu, Shu-Wen Yao Dan Liu, Hai-Long Zhao Shu-Wen Yao, et al. "Research on Mutual Information Feature Selection Algorithm Based on Genetic Algorithm." 電腦學刊 33, no. 6 (2022): 131–41. http://dx.doi.org/10.53106/199115992022123306011.

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<p>Feature selection is an important part of data preprocessing. Feature selection algorithms that use mutual information as evaluation can effectively handle different types of data, so it has been widely used. However, the potential relationship between relevance and redundancy in the evaluation criteria is often ignored, so that effective feature subsets cannot be selected. Optimize the evaluation criteria of the mutual information feature selection algorithm and propose a mutual information feature selection algorithm based on dynamic penalty factors (Dynamic Penalty Factor Mutual In
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Tan, Jun. "Weighted Association Rules Mining Algorithm Research." Applied Mechanics and Materials 241-244 (December 2012): 1598–601. http://dx.doi.org/10.4028/www.scientific.net/amm.241-244.1598.

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Aiming at the problem that most of weighted association rules mining algorithms have not the anti-monotonicity, this paper presents a weighted support-confidence framework which supports anti-monotonicity. On this basis, weighted boolean association rules mining algorithm and weighted fuzzy association rules mining algorithm are presented, which use pruning strategy of Apriori algorithm so that improve the efficiency of frequent itemsets generated. Experimental results show that both algorithms have good performance.
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Zhang, Qing-hui, Qi-ming Wang, and Shuying Qin. "Research on An Improved RFID Collision Algorithm." MATEC Web of Conferences 232 (2018): 03012. http://dx.doi.org/10.1051/matecconf/201823203012.

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Radio Frequency Identification (RFID) is a kind of information that using radio Identification technology. Anti-collision algorithm has always been a research topic for researchers. The anti-collision algorithm of labels is mainly divided into two major categories: ALOHA-Based Anti-Collision Algorithms and Anti-collision algorithm based on binary search. Both algorithms have their own advantages and disadvantages, Anti-collision algorithm that based on ALOHA is simple and fast, but it will lose labels. Binary-based anti-collision algorithm can be searched for every tag, and it is not easy to l
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Xue, Liqi. "Research on SGD Algorithm Using Momentum Strategy." Applied and Computational Engineering 2, no. 1 (2023): 141–50. http://dx.doi.org/10.54254/2755-2721/2/20220622.

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With the continuous development of stochastic gradient descent algorithms, many efficient momentum algorithms have appeared. Stochastic gradient descent(SGD) is one of the classic algorithms in optimization. Its accelerated version, the SGD algorithm with momentum strategy, has been a hot research topic in recent years. Therefore, this paper will analyze and summarize these series of algorithms, starting with the classical momentum algorithm, and introduce some improved versions of the momentum algorithm. Numerical experiments on real problems will also be done to evaluate the performance of t
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Zhang, Yi Fan, Yong Tao Qian, Tai Yu Liu, and Shu Yan Wu. "Data Mining Clustering Algorithm Research and Application." Advanced Materials Research 926-930 (May 2014): 3608–11. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.3608.

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In this paper, first introduce data mining knowledge then focuses on the clustering analysis algorithms, including classification clustering algorithm, and each classification typical cluster analysis algorithms, including the formal description of each algorithm as well as the advantages and disadvantages of each algorithm also has a more detailed description. Then carefully introduce data mining algorithm on the basis of cluster analysis. And using cohesion based clustering algorithm with DBSCAN algorithm and clustering in consumer spending in two-dimensional space, 2,000 data points for eac
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Yi, Jian Jun, Fei Luo, Shao Li Chen, Bai Yang Ji, and Hai Xu Yan. "Research on a Dynamic Binary Stack Anti-Collision Algorithm." Applied Mechanics and Materials 268-270 (December 2012): 1426–31. http://dx.doi.org/10.4028/www.scientific.net/amm.268-270.1426.

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RFID anti-collision technology is one of a key technology in RFID application system. Anti-collision algorithms for RFID systems include tag anti-collision algorithms and reader anti-collision algorithms. This paper focused on the impoved binary algorithm and dynamic binary algorithm. An improved algorithm has been proposed, in which the collision bits was put into the stack and they were used as the reader’s request. Based on this mechanism, a novel binary stack algorithm has been proposed. Its simulation was given to analyze the performance of this algorithm. The simulation results showed th
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Zeng, Yi, Shiqun Yin, Jiangyue Liu, and Miao Zhang. "Research of Improved FP-Growth Algorithm in Association Rules Mining." Scientific Programming 2015 (2015): 1–6. http://dx.doi.org/10.1155/2015/910281.

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Association rules mining is an important technology in data mining. FP-Growth (frequent-pattern growth) algorithm is a classical algorithm in association rules mining. But the FP-Growth algorithm in mining needs two times to scan database, which reduces the efficiency of algorithm. Through the study of association rules mining and FP-Growth algorithm, we worked out improved algorithms of FP-Growth algorithm—Painting-Growth algorithm and N (not) Painting-Growth algorithm (removes the painting steps, and uses another way to achieve). We compared two kinds of improved algorithms with FP-Growth al
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Yu, Binyan, and Yuanzheng Zheng. "Research on algorithms of machine learning." Applied and Computational Engineering 39, no. 1 (2024): 277–81. http://dx.doi.org/10.54254/2755-2721/39/20230614.

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Machine learning has endless application possibilities, with many algorithms worth learning in depth. Different algorithms can be flexibly applied to a variety of vertical fields, such as the most common neural network algorithms for face recognition, garbage classification, picture classification, and other application scenarios image recognition and computer vision, the hottest recent natural language processing and recommendation algorithms for different applications are from it. In the field of financial analysis, the decision tree algorithm and its derivative algorithms such as random for
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10

Li, Xiao Bo. "Contrast Research of Two Kinds of Integrated Sorting Algorithms." Advanced Materials Research 433-440 (January 2012): 4025–31. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.4025.

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Boosting and Bagging are two kinds of important voting sorting algorithms. Boosting algorithm can generate multiple classifiers by serialization through adjustment of sample weight; Bagging can generate multiple classifiers by parallelization. Different algorithms are composed of different loss and different integration mode, through integration of Bagging and Boosting algorithm and naïve Bayes algorithm, the Bagging NB and AdaBoost NB algorithms are constructed. Through experiment contrast of UCI data set, the result shows Bagging NB algorithm is relatively stable, it can produce the sorting
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Zeng, Jin, Li Guang Wang, Meng Jun Ye, Chang Hui Hu, and Tian Feng Ye. "Research of Several PID Algorithms Based on MATLAB." Advanced Materials Research 760-762 (September 2013): 1075–79. http://dx.doi.org/10.4028/www.scientific.net/amr.760-762.1075.

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This paper introduces several PID control algorithms and their discretization expression. Compare the performance of positional PID algorithm with incremental PID algorithm, integration separate PID algorithm, incomplete differential PID algorithm and PID algorithm with dead zone. The experiment results show that different digital PID control algorithm could achieve different using.
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12

Tong, Lin, and Di Wu. "Research on Optimized Clustering Analysis Algorithm." Advanced Materials Research 811 (September 2013): 407–12. http://dx.doi.org/10.4028/www.scientific.net/amr.811.407.

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In this paper an improved clustering analysis algorithm is proposed on the basis of randomly selected data in the CURE algorithm and the cluster centers setting in the K-NN algorithm. The combination of the two algorithms conquers the poor clustering accuracy in the CURE algorithm and the clustering deficiency on large data set in the K-NN algorithm. This paper first introduces the concept of clustering analysis and its real-life applications, then proceeds to describe the method of clustering analysis, and then introduces optimized CURE_KNN algorithm described in pseudo-code, at last the adva
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Fu, Li Li, Yong Li Liu, and Li Jing Hao. "Research on Spectral Clustering." Applied Mechanics and Materials 687-691 (November 2014): 1350–53. http://dx.doi.org/10.4028/www.scientific.net/amm.687-691.1350.

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Spectral clustering algorithm is a kind of clustering algorithm based on spectral graph theory. As spectral clustering has deep theoretical foundation as well as the advantage in dealing with non-convex distribution, it has received much attention in machine learning and data mining areas. The algorithm is easy to implement, and outperforms traditional clustering algorithms such as K-means algorithm. This paper aims to give some intuitions on spectral clustering. We describe different graph partition criteria, the definition of spectral clustering, and clustering steps, etc. Finally, in order
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14

Li, Gang. "Research on Smartphone Trojan Detection Based on the Wireless Sensor Network." Security and Communication Networks 2022 (July 9, 2022): 1–7. http://dx.doi.org/10.1155/2022/2455102.

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In order to reduce false positives of Trojan horse detection algorithms in smartphones, a voting algorithm based on multiple machine learning algorithms in wireless sensor networks was proposed. Through setting up the experiment, the preliminary preparations of the experiment, including sample set selection, feature set extraction method, and algorithm effect evaluation criteria, were described first. The K-nearest neighbors algorithm, random forests algorithm, support vector machine, and voting algorithm were compared. The experimental results showed that SVM and KNN algorithms took the short
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15

Qiu, Dong Wei, and Shan Shan Wan. "Research on Algorithms Performance about JSP Scheduling." Advanced Materials Research 457-458 (January 2012): 20–25. http://dx.doi.org/10.4028/www.scientific.net/amr.457-458.20.

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Three typical intelligent evolutionary algorithms are applied on Job Shop scheduling problem which are Quantum algorithm, Genetic Algorithm and Population Based Incremental Learning algorithm. They three algorithms have some common features in computation, encoding strategy and probability application, but with the different problems and different scale sizes of the same problem they show different performance. In this paper we take JSP as example to test their performance difference and analyze their applicability. Two benchmark Job Shop problems are used to fulfill the comparison. The result
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16

Sun, Jingran, Yuyin Zhang, Fangjia Fu, Liyan Kang, and Junxu Ma. "Research and Prospect of Intelligent Workshop AGV Path Planning Algorithm." Journal of Engineering Research and Reports 26, no. 7 (2024): 71–80. http://dx.doi.org/10.9734/jerr/2024/v26i71195.

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Path planning algorithm is one of the core algorithms for automatic guided vehicle(AGV)to complete the autonomous task of intelligent workshop. The research status of grid method and Viewable method in environment modeling at home and abroad is described. The research results of traditional path search algorithms such as artificial potential field method, Dijstra algorithm and A* algorithm are analyzed and compared with intelligent algorithms such as particle swarm optimization algorithm, ant colony algorithm and genetic algorithm. The analysis finds that in the face of complex workshop enviro
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Bakhvalova, Ekaterina Alexandrovna, and Vladimir Anatolievich Sudakov. "Research of consensus algorithms for blockchain platforms." Keldysh Institute Preprints, no. 26 (2021): 1–16. http://dx.doi.org/10.20948/prepr-2021-26.

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In this paper, several consensus algorithms are investigated, a comparative analysis of these algorithms is made, the results of which are important in the context of the active growth of the cryptocurrency market. In addition, in the context of pandemics, the creation of blockchain technologies for the distributed storage of reliable medical data is relevant. The key properties of consensus algorithms are highlighted, and a detailed analysis of the algorithm of the promising Istanbul BFT algorithm is carried out. Using multi-criterion analysis of alternatives, it is shown how you can select t
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18

Wei, Xian Min. "Routing Lookup Algorithm Performance Analysis and Research." Advanced Materials Research 181-182 (January 2011): 109–12. http://dx.doi.org/10.4028/www.scientific.net/amr.181-182.109.

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This paper describes several current routing lookup algorithms, to study and analysize the complexity and operating practical performance of these routing lookup algorithms. The results show that although the binary search algorithm is not greatly improved in the searching performance, but in IPv6 environment, because searching performance of multi-branch Trie tree will decrease greatly, thus the superiority of binary search algorithm will be reflected better.
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19

Yan, Ruixia, Zhijie Xia, Yanxi Xie, Xiaoli Wang, and Zukang Song. "Research on Sentiment Classification Algorithms on Online Review." Complexity 2020 (September 8, 2020): 1–6. http://dx.doi.org/10.1155/2020/5093620.

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The product online review text contains a large number of opinions and emotions. In order to identify the public’s emotional and tendentious information, we present reinforcement learning models in which sentiment classification algorithms of product online review corpus are discussed in this paper. In order to explore the classification effect of different sentiment classification algorithms, we conducted a research on Naive Bayesian algorithm, support vector machine algorithm, and neural network algorithm and carried out some comparison using a concrete example. The evaluation indexes and th
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20

He, Chunlin, Jiaye Wu, and Yujie Yang. "Research on Image Stitching Technology for Road Surface Cracks." International Journal of Computer Science and Information Technology 2, no. 1 (2024): 368–77. http://dx.doi.org/10.62051/ijcsit.v2n1.38.

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Image stitching refers to the combination of multiple images with a certain over lappingarea rate acquired by the image acquisition device into one image, which has a full picture of each image. Image stitching technology is an important part in the field of digital image processing. With the increasing requirements for image quality and the limited resolution of ordinary cameras, it is impossible to obtain large angle of view and clear image at the same time. In this paper, the key technologies involved in pavement crack image stitching are intensively studied, including image feature point d
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21

Zhang, Xueyi. "Research progress of path planning algorithm for mobile robot navigation." Highlights in Science, Engineering and Technology 119 (December 11, 2024): 366–73. https://doi.org/10.54097/psehyq71.

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The main research contents of mobile robot technology include: navigation and positioning, path planning and motion control. Path planning is an important branch of mobile robot research. Its task is to find an optimal path in its workspace according to some optimization criteria. Many different path planning algorithms have been developed to solve the corresponding problems, such as improving the safety of the path, enhancing the working ability of the robot and improving the efficiency of path planning. However, a single original path planning algorithm often has different advantages and dis
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22

USHAKOV, K. D., and O. N. KANEVA. "SPATIAL IMAGE REGISTRATION METHOD RESEARCH AND DEVELOPMENT." Applied Mathematics and Fundamental Informatics 11, no. 1 (2024): 37–44. http://dx.doi.org/10.25206/2311-4908-2024-11-1-37-44.

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The paper develops algorithms for fusion images by machine learning. Machine learning algorithms and static algorithms are compared. Static algorithms are easy to implement, but retain fewer details. Fusion algorithms based on machine learning give a clearer and sharper image while preserving more details. To train the algorithm, pairs of images with different blurred areas or with different colors are used. A trained algorithm works better than a static one. The comparison of the developed algorithms by quality metrics is carried out.
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23

Zhang, Xiaobo, and Jinguo Liu. "Research on Collision Detection Algorithm for Human-SRL Collaborative Motion Planning." Journal of Physics: Conference Series 2402, no. 1 (2022): 012021. http://dx.doi.org/10.1088/1742-6596/2402/1/012021.

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Abstract The existing collision detection algorithms are commonly based on triangle patch models, which leads to complex detection logic. Aiming at this problem, this paper proposes a new collision detection algorithm. It has simple detection logic and fast detection speed, and it is mainly used for human-SRL cooperative motion planning. The algorithm is based on a human-SRL skeleton model and a multi-sphere envelope method and includes four sub-algorithms, namely, a multi-sphere envelope sub-algorithm, an SRL collision detection sub-algorithm, a collision detection sub-algorithm between SRL a
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Andreev, Alexander A., and Marina S. Shapovalova. "SOUND RESEARCH. NOISE REMOVAL." RSUH/RGGU Bulletin. Series Information Science. Information Security. Mathematics, no. 1 (2022): 35–45. http://dx.doi.org/10.28995/2686-679x-2022-1-35-45.

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The article presents algorithms for removing extraneous noise from an audio track. It considers the features of various types of noise that occur during sound recording. The article takes into account the features of the Conv-TasNet architecture, which is based on the imposition of convolutions on a pure signal without frequency separation. There is an analysis of the DEMUC algorithm, which directly generates sources from the original signal, bypassing the intermediate prediction of masks; the architecture for segmentation of images U-Net is partially borrowed. Also the authors consider the Hi
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Wang, Han, and Yan Piao. "Research on Optimal Path Finding Algorithm." Applied Mechanics and Materials 427-429 (September 2013): 1883–87. http://dx.doi.org/10.4028/www.scientific.net/amm.427-429.1883.

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Optimal path finding algorithm is a very important research direction in computer science. It is a node search method based on graph theory. This paper focus on the fundamental researches of the optimal path finding algorithm. By comparing various path finding algorithms, this paper implement the A* algorithm and present a variant strategy of A* which is named Turning Point A*(TPA*). The experiment shows that searching with TPA* can speed up A* by an order of magnitude and more and report significant improvement.
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Hao, Shangqing, Xuewen Wang, Jiacheng Xie, and Zhaojian Yang. "Rigid framework section parameter optimization and optimization algorithm research." Transactions of the Canadian Society for Mechanical Engineering 43, no. 3 (2019): 398–404. http://dx.doi.org/10.1139/tcsme-2018-0085.

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This article compares the optimization algorithms included with ANSYS Software for optimizing the dimensions of a large steel framework to minimize weight while maintaining stiffness. A finite element model of the structure was prepared, and the section parameters were optimized using the sub-problem and first-order algorithms. These reduce the weight of the structure by 33.8%. The sub-problem algorithm and the first-order algorithm are explained from the rationale, iteration method, and convergence criterion. According to the optimized result, these two algorithms were compared. The results s
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Lu, Pei Xin. "Research on BP Neural Network Algorithm Based on Quasi-Newton Method." Applied Mechanics and Materials 686 (October 2014): 388–94. http://dx.doi.org/10.4028/www.scientific.net/amm.686.388.

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With more and more researches about improving BP algorithm, there are more improvement methods. The paper researches two improvement algorithms based on quasi-Newton method, DFP algorithm and L-BFGS algorithm. After fully analyzing the features of quasi-Newton methods, the paper improves BP neural network algorithm. And the adjustment is made for the problems in the improvement process. The paper makes empirical analysis and proves the effectiveness of BP neural network algorithm based on quasi-Newton method. The improved algorithms are compared with the traditional BP algorithm, which indicat
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Chen, Tianhao, and Guanhong Jiang. "Research on robot path planning methods." Applied and Computational Engineering 15, no. 1 (2023): 30–37. http://dx.doi.org/10.54254/2755-2721/15/20230807.

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Mobile robots are used extensively across a variety of industries and fields. How to discover a start-to-end path without colliding has become a hot topic in recent years due to the complexity and uncertainty of the workplace. In various environments, a path planning technique should demonstrate high efficiency and speed. And this can reduce the energy consumption of the robots and greatly increase their working efficiency. This paper will conclude the presently popular path planning algorithm. Based on the different features of these algorithms, they are divided into three types: traditional
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Li, Cheng Yang. "Research and comparison of algorithms based on multi-modal fusion." Journal of Physics: Conference Series 2807, no. 1 (2024): 012038. http://dx.doi.org/10.1088/1742-6596/2807/1/012038.

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Abstract A multi-modal fusion algorithm is an important method for information fusion on multi-modal data provided by different sensors. It can make full use of the advantages of multiple sensors and improve the accuracy and robustness of data processing and decision-making. This paper aims to study the performance difference between the extended Kalman filter (EKF) algorithm and other algorithms in multi-modal fusion and explore a method to fuse multiple algorithms further to improve the accuracy of fusion results. The author uses the classic test set data set for experiments to evaluate the
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Fugui, Luo, Qin Yunchu, and Li Mingzhen. "Research and Implementation of Medical Image Edge Detection Algorithm." Tobacco Regulatory Science 7, no. 5 (2021): 3866–77. http://dx.doi.org/10.18001/trs.7.5.1.159.

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Medical imaging has become an important reference for the diagnosis of various diseases, and the role of medical imaging will become more and more important in the future. The interpretation of medical images is of paramount importance. With the continuous development of medical imaging technology, image interpretation has become more and more important. At present, it is directly inferred by doctors that in order to solve problems more effectively and deal with fuzzy data, it is necessary to research and implement an algorithm-based medical image edge detection assistant system. The current m
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Wang, Yaoying, Shudong Sun, and Zhiqiang Cai. "The Research of Short-term Electric Load Forecasting based on Machine Learning Algorithm." Advances in Engineering Technology Research 4, no. 1 (2023): 334. http://dx.doi.org/10.56028/aetr.4.1.334.2023.

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The ability of electric load forecasting become the key to measuring electric planning and dispatching, and improving the accuracy of electric load forecasting has become one hot spot topic of scholars in recent years. The traditional electric load forecasting algorithm mainly include statistical learning algorithm. The electric load forecasting algorithm based on traditional forecasting algorithm, machine learning algorithm and neural network algorithm greatly improve the convergence approximation effect and accuracy. In recent years, the electric load forecasting algorithms based on the deep
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32

Yu, Guoxiang, and Shoubo Wang. "Research on Lifting Path Planning Algorithms for Intelligent Cranes." Journal of Engineering Research and Reports 26, no. 7 (2024): 57–63. http://dx.doi.org/10.9734/jerr/2024/v26i71193.

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Path planning algorithm is one of the key technologies in the study of intelligent cranes, and a good path planning algorithm can quickly plan a safe and collision-free path. The current research status of path planning technology in the field of crane lifting path planning is reviewed. The implementation principles of various types of algorithms are analysed, and the current research status of mainstream path planning algorithms is summarized. According to the characteristics of crane path planning algorithms, crane path planning algorithms are classified into traditional path planning algori
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Zeng, Sha, and Kang Liu. "Research Status and Development Trend of UAV Path Planning Algorithms." Journal of Physics: Conference Series 2283, no. 1 (2022): 012004. http://dx.doi.org/10.1088/1742-6596/2283/1/012004.

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Abstract This paper introduces the basic concepts of UAV track planning, the relationship between track planning and algorithms, and focuses on the analysis and induction of several commonly used algorithms at home and abroad in recent years. The advantages and disadvantages of current path planning algorithms in different application scenarios are summarized. Finally, the future development trend of UAV path planning algorithm is prospected, and it is pointed out that real-time online path planning algorithm research, multi-UAV swarm planning algorithm, perfect path planning problem model and
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Zhang, Qize. "Research on fast matrix multiplication algorithm." Applied and Computational Engineering 31, no. 1 (2024): 229–34. http://dx.doi.org/10.54254/2755-2721/31/20230154.

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This research mainly focuses on fast matrix multiplication algorithms. Fast matrix multiplication is one of the most fundamental problems in computer science. The fast matrix multiplication algorithm differs from conventional matrix multiplication in that it offers a faster computational approach that can perform the operation in less than O(n3) time complexity. This algorithm provides a more efficient method for multiplying matrices, significantly reducing the computational requirements. The Laser method, developed by Coppersmith and Winograd, is an algorithm for matrix multiplication that do
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Wei, Feng. "Research on Knight Covering Based on Breadth First Search Algorithm." Applied Mechanics and Materials 686 (October 2014): 377–80. http://dx.doi.org/10.4028/www.scientific.net/amm.686.377.

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This paper introduces the general process of the search algorithm Structure through the knight problem. According to the characteristics of the problem, we detailed discuss the DFS(Depth First Search) algorithm and BFS(Breadth First Search) algorithm, and combine the two algorithms together to solve the knights coverage problem. This article has a good reference for the mixed-use scenarios which requires a variety of search algorithms.Algorithms is always the core of Computer programming modeling. Computer algorithm algorithms describes in detail how a computer will enter into the process of o
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Han, Ai Li. "Complexity Research on B Algorithm." Applied Mechanics and Materials 20-23 (January 2010): 173–77. http://dx.doi.org/10.4028/www.scientific.net/amm.20-23.173.

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The time complexity of B algorithm, one of the intelligent search algorithms, is discussed. By anatomizing some instances, it is pointed out that the cost of calculating the value of heuristic function should be included in the range of time complexity analysis for B algorithm. And then, an algorithm of calculating the value of heuristic function is presented. By analyzing the cost of calculating the value of heuristic function, it is pointed out that the number of recursions in B algorithm is O(n!) in the worst case. Therefore, the time complexity of B algorithm is exponential instead of O(n2
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Zhang, Zeshun. "Research on algorithms based on object detection." Applied and Computational Engineering 19, no. 1 (2023): 146–51. http://dx.doi.org/10.54254/2755-2721/19/20231024.

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Object detection technology is a hot research direction in computer vision field technology, which is broadly used in face recognition, vehicle navigation, aviation and other important fields, with broad development prospects. In recent years, object detection algorithms based on deep learning have also appeared as computer science technology has advanced quickly. Comparing modern object detecting algorithms to conventional ones, this algorithm has gradually highlighted the advantages of high precision and good real-time performance. This article reviews traditional object detection algorithms
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Zhang, Jian Hua, Fan Tao Kong, Jian Zhai Wu, Meng Shuai Zhu, Pu Zhao, and Sheng Wei Wang. "Research on Blurred Image Restoration Quality Evaluation Method." Advanced Materials Research 1049-1050 (October 2014): 1698–702. http://dx.doi.org/10.4028/www.scientific.net/amr.1049-1050.1698.

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Accurate evaluation of image quality is always being a problem. With blurry cotton images as samples, using variance methods, average gradient method, gray prediction error statistics method and information entropy method, this research evaluated restoration quality of 4 kinds of images from the perspective of grayscale contrast, sharpness, contrast and ambiguity. The results show that the 4 image restoration algorithms all improved image quality, and Wiener algorithm improved image quality best comparing with other 3 algorithms, Reg second, Blind algorithm and K-L algorithm were worse.
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Wu, Wenkang. "Research Process of Path Planning based on RRT Algorithm and Its Improvements." Transactions on Computer Science and Intelligent Systems Research 5 (August 12, 2024): 685–92. http://dx.doi.org/10.62051/236c5w06.

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At present, path-planning algorithms in the field of robotics is a problem of research value. Especially in the field of robotics, it has great significance. A good algorithm can improve the efficiency of the robot and ensure the safety of the robot in complex environments. In addition, the path planning algorithm can improve the autonomy and intelligence of the robot, help the robot to realize autonomous navigation and decision-making, and through different algorithms, the robot can also play different roles in different fields. In the past few years, many relatively perfect algorithms have b
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Fang, Yuchen. "A research on different digital signature schemes." Applied and Computational Engineering 16, no. 1 (2023): 27–35. http://dx.doi.org/10.54254/2755-2721/16/20230855.

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In the past years, digital signature development has rapidly with new products combined with blockchain, named distribute networks, and quantum computers, while there plays a vitally important role in file authorization and verification. In combination with various new technologies, digital signatures present a vigorous vitality, and new algorithms are widely used in varieties of scenarios including banking, financial services, and insurance (BFSI), education, E-government, healthcare, and the military. In this case, there is no paper illustrating a summary of those new digital signature appli
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Zhu, Kai Feng, Xue Wang, and Gui Hua Cai. "Research of Distribution Network Reconfiguration Based on SFLGA." Advanced Materials Research 960-961 (June 2014): 1058–61. http://dx.doi.org/10.4028/www.scientific.net/amr.960-961.1058.

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The article studies on the application of the shuffled frog leaping algorithm (SFLA) in power distribution network reconfiguration, taking the minimum loss and voltage quality of distribution network as a multi-objective function. The article improves the initial solution generation strategy of traditional genetic algorithm, which ensures the initial solution is feasible solution. Shuffled frog leaping algorithm and genetic algorithms are combined and proposed as shuffled frog leaping genetic algorithm (SFLGA). The algorithm uses the efficient coding strategy based on the basic loop and initia
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Xu, Hong Sheng, and Ting Zhong Wang. "The Research of Constructing Rough Concept Lattices Model." Applied Mechanics and Materials 63-64 (June 2011): 664–67. http://dx.doi.org/10.4028/www.scientific.net/amm.63-64.664.

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Formal concept lattices and rough set theory are two kinds of complementary mathematical tools for data analysis and data processing. The algorithm of concept lattice reduction based on variable precision rough set is proposed by combining the algorithms of β-upper and lower distribution reduction in variable precision rough set. The traditional algorithms aboutβvalue select algorithm, attribute reduction based on discernibility matrix and extraction rule in VPRS are discussed, there are defects in these traditional algorithms which are improved. Finally, the generation system of concept latti
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Wang, Hong. "Research on the Realization of LRU Algorithm." Applied Mechanics and Materials 530-531 (February 2014): 891–94. http://dx.doi.org/10.4028/www.scientific.net/amm.530-531.891.

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This paper analyzes LRU page-replacement algorithms, and points out that LRU is closest to OPT among all possible page-replacement algorithms. It studies the four possible methods for LRU algorithm: measurement of time, count of number, use of registers, and use of stack. Data structures and implementation methods are proposed; approximation algorithms are discussed. This paper also analyzes the performances and reliability of different LRU page-replacement algorithms, providing some basic information for us to choose them in different systems.
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Xiao, BoXue. "Research on High Resolution Image Processing System Based on FPGA Technology." Journal of Physics: Conference Series 2303, no. 1 (2022): 012087. http://dx.doi.org/10.1088/1742-6596/2303/1/012087.

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Abstract A This paper is the focus of the dissertation and focuses on some commonly used image filtering algorithms. The commonly used image filters are median filter, Gaussian filter and edge detection algorithm. In this chapter, the FPGA implementation of grayscale processing module is studied first, then median filtering and Gaussian filtering are studied, and a fast median filtering algorithm and displacement-optimized Gaussian filtering algorithm are proposed, and the feasibility of the algorithms is demonstrated by simulation experiments. Then the edge detection algorithm is studied and
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Fei, Teng, Hongjun Wang, Lanxue Liu, Liyi Zhang, Kangle Wu, and Jianing Guo. "Research on multi-strategy improved sparrow search optimization algorithm." Mathematical Biosciences and Engineering 20, no. 9 (2023): 17220–41. http://dx.doi.org/10.3934/mbe.2023767.

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<abstract> <p>To address the issues with inadequate search space, sluggish convergence and easy fall into local optimality during iteration of the sparrow search algorithm (SSA), a multi-strategy improved sparrow search algorithm (ISSA), is developed. First, the population dynamic adjustment strategy is carried out to restrict the amount of sparrow population discoverers and joiners. Second, the update strategy in the mining phase of the honeypot optimization algorithm (HBA) is combined to change the update formula of the joiner's position to enhance the global exploration ability
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Yun, Xiao Yan. "Research on Traveling Salesman Problem Algorithm." Advanced Materials Research 694-697 (May 2013): 2901–4. http://dx.doi.org/10.4028/www.scientific.net/amr.694-697.2901.

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The traveling salesman problem (TSP) has been an important problem in the field of distribution and logistics and it is clearlyNP-hard combinatorial optimization problem and difficult to solve. This paper gives a review of achievements of different types of Algorithms for the traveling sales man problem and outlines these advantages and limitation for these algorithms, including dynamic program, brand and bound, genetic algorithm and estimation of distribution algorithms. In addition, some of the most powerful efficiency enhancement techniques applied to TSP is discussed and quite a few common
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Li, Yifan, Bin Wang, Zixing Zhou, Aimin Yang, and Yunjie Bai. "Research Progress of Intelligent Ore Blending Model." Metals 13, no. 2 (2023): 379. http://dx.doi.org/10.3390/met13020379.

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The iron and steel industry has made an important contribution to China’s economic development, and sinter accounts for 70–80% of the blast furnace feed charge. However, the average grade of domestic iron ore is low, and imported iron ore is easily affected by transportation and price. The intelligent ore blending model with an intelligent algorithm as the core is studied. It has a decisive influence on the development of China’s steel industry. This paper first analyzes the current situation of iron ore resources, the theory of sintering ore blending, and the difficulties faced by sintering o
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Guoyan, Wang, A. V. Fomichev, and Dy Yiran. "Research on Improved Gaussian Smoothing Filters for SLAM Application." Mekhatronika, Avtomatizatsiya, Upravlenie 20, no. 12 (2019): 756–64. http://dx.doi.org/10.17587/mau.20.756-764.

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To address the navigation issues of the planetary rover and construct a map for the unknown environment as well as the surface of the planets in our solar system, the simultaneous localization and mapping can be seen as an alternative method. In terms of the navigation with the laser sensor, the Kalman filter and its improving algorithms, such as EKF and UKF are widely used in the the process of processing information. Nevertheless, these filter algorithms suffer from low accuracy and significant computation expensive. The EKF algorithm has a linearization process, the UKF algorithm is better
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Zhao, Jiafan, Xin Zhao, Quanhu Li, and Jingyu Zhang. "Research on ultra-tight integrated navigation method based on CKF filtering algorithm." Journal of Physics: Conference Series 2221, no. 1 (2022): 012048. http://dx.doi.org/10.1088/1742-6596/2221/1/012048.

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Abstract This paper takes the SINS/BDS ultra-tight integrated navigation system as the background of research. Based on the existing integrated navigation nonlinear filtering algorithm, an ultra-tight integrated navigation method based on CKF filtering algorithm is proposed. Compared with the EKF and UKF algorithms, the CKF algorithm reduces the errors caused by intercepting higher order terms in the EKF, overcomes the problem of difficult to determine adjustable parameters in the UKF in practical applications, and greatly reduces the computational effort. Because of the above advantages nowad
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Gong, Qianru. "Application Research of Data Encryption Algorithm in Computer Security Management." Wireless Communications and Mobile Computing 2022 (July 14, 2022): 1–7. http://dx.doi.org/10.1155/2022/1463724.

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In order to promote the research process of information security in the whole society, improve the safety factor of computer data communication, strengthen computer security management, the author proposes a computer data encryption strategy that combines the strong security of the 3DES encryption algorithm and the asymmetric encryption advantages of the RSA algorithm. Through the detailed analysis of DES encryption algorithm and 3DES encryption, creatively uses the RSA encryption algorithm to improve the single 3DES algorithm, consolidates the performance of the 3DES encryption algorithm to e
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