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Articoli di riviste sul tema "Algorithm efficiency"

Autore: Grafiati

Pubblicato: 31 agosto 2024

Ultima modifica: 19 luglio 2025

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1

Sergienko, Ivan, Vladimir Shylo, Valentyna Roshchyn, and Petro Shylo. "The Efficiency of Discrete Optimization Algorithm Portfolios." Cybernetics and Computer Technologies, no. 2 (June 30, 2021): 5–12. http://dx.doi.org/10.34229/2707-451x.21.2.1.

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Introduction. Solving large-scale discrete optimization problems requires the processing of large-scale data in a reasonable time. Efficient solving is only possible by using multiprocessor computer systems. However, it is a daunting challenge to adapt existing optimization algorithms to get all the benefits of these parallel computing systems. The available computational resources are ineffective without efficient and scalable parallel methods. In this connection, the algorithm unions (portfolios and teams) play a crucial role in the parallel processing of discrete optimization problems. The

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Zarembo, Imants, and Sergejs Kodors. "Pathfinding Algorithm Efficiency Analysis in 2D Grid." Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference 2 (August 8, 2015): 46. http://dx.doi.org/10.17770/etr2013vol2.868.

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The main goal of this paper is to collect information about pathfinding algorithms A*, BFS, Dijkstra's algorithm, HPA* and LPA*, and compare them on different criteria, including execution time and memory requirements. Work has two parts, the first being theoretical and the second practical. The theoretical part details the comparison of pathfinding algorithms. The practical part includes implementation of specific algorithms and series of experiments using algorithms implemented. Such factors as various size two dimensional grids and choice of heuristics were taken into account while conducti

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Zhi, Xiangyu, Xiao Yan, Bo Tang, Ziyao Yin, Yanchao Zhu, and Minqi Zhou. "CoroGraph: Bridging Cache Efficiency and Work Efficiency for Graph Algorithm Execution." Proceedings of the VLDB Endowment 17, no. 4 (2023): 891–903. http://dx.doi.org/10.14778/3636218.3636240.

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Many systems are designed to run graph algorithms efficiently in memory but they achieve only cache efficiency or work efficiency. We tackle this fundamental trade-off in existing systems by designing CoroGraph, a system that attains both cache efficiency and work efficiency for in-memory graph processing. CoroGraph adopts a novel hybrid execution model , which generates update messages at vertex granularity to prioritize promising vertices for work efficiency, and commits updates at partition granularity to share data access for cache efficiency. To overlap the random memory access of graph a

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Brandejsky, Tomas. "Function Set Structure Influence onto GPA Efficiency." MENDEL 23, no. 1 (2017): 29–32. http://dx.doi.org/10.13164/mendel.2017.1.029.

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The paper discusses the influence of function set structure onto efficiency of GPA (Genetic Programming Algorithms), and hierarchical algorithms like GPA-ES (GPA with Evolutionary Strategy to separate parameter optimization) algorithm efficiency. On the foreword, the discussed GPA algorithm is described. Then there is depicted function set and common requirements to its structure. On the end of this contribution, the test examples and environment as well as results of measurement of influence of superfluous functions presence in the used function set is discussed.

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Amannah, Constance Izuchukwu, and Francis Sunday Bakpo. "SIMPLIFIED BLUESTEIN NUMERICAL FAST FOURIER TRANSFORMS ALGORITHM FOR DSP AND ASP." International Journal of Research – Granthaalayah 3, no. 11 (2017): 153–63. https://doi.org/10.5281/zenodo.849031.

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This research was designed to develop a simplified Bluestein numerical FFT algorithm necessary for the processing of digital signals. The simplified numerical algorithm developed in this study is abbreviated with SBNADSP. The methodology adopted in this work was iterative and incremental development design. The major technology used in this work is the Bluestein numerical FFT algorithm. The study set the pace for its goal by re-indexing, decomposing, and simplifying the default Fast Fourier Transform Algorithms (the Bluestein FFT Algorithm). The improved efficiency of the Bluestein FFT algorit

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Xiao, Shi Song, Ao Lin Wang, and Hui Feng. "An Improved Algorithm Based on AC-BM Algorithm." Applied Mechanics and Materials 380-384 (August 2013): 1576–79. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.1576.

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The pattern matching algorithm is the mainstream technology in the instruction detection system, and therefore as a pattern-matching methods core string matching algorithm directly affect an intrusion detection system performance and efficiency. So based on the discussions of the most fashionable pattern matching algorithms at present, an improved algorithm of AC-BM is presented. From the experiments in the Snort ,it is concluded that the improved algorithm of the performance and efficiency is higher than AC-BM algorithm.

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Klyatchenko, Yaroslav, and Volodymyr Holub. "EFFICIENCY OF LOSSLESS DATA COMPRESSION ALGORITHM MODIFICATION." Bulletin of National Technical University "KhPI". Series: System Analysis, Control and Information Technologies, no. 2 (10) (December 19, 2023): 67–72. http://dx.doi.org/10.20998/2079-0023.2023.02.10.

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The current level of development of information technologies causes a rapid increase in the amount of information stored, transmitted and processed in computer systems. Ensuring the full and effective use of this information requires the use of the latest improved algorithms for compaction and optimization of its storage. The further growth of the technical level of hardware and software is closely related to the problems of lack of memory for storage, which also actualizes the task of effective data compression. Improved compression algorithms allow more efficient use of storage resources and

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Mrs., Pooja V. "Enhancing Scheduling Efficiency in Graph Theory: A Novel Approach to Maximum Matching." Journal of Scholastic Engineering Science and Management 3, no. 3 (2024): 1–13. https://doi.org/10.5281/zenodo.10907243.

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The maximum matching problem is a fundamental problem in graph theory. It asks for the maximum number of edges that can be selected in a graph so that no two selected edges share an endpoint. This problem has applications in many areas, such as scheduling, transportation, and telecommunications. Existing algorithms for finding the maximum matching in a graph are often inefficient. For example, the brute-force algorithm can take exponential time to find the maximum matching in a graph. In this paper, we present a new algorithm for finding the maximum matching in a graph. Our algorithm is based

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Wang, Chun Ye, and Xiao Feng Zhou. "The MapReduce Parallel Study of KNN Algorithm." Advanced Materials Research 989-994 (July 2014): 2123–27. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.2123.

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Although the parallelization KNN algorithm improves the classification efficiency of the algorithm, the calculation of the parallel algorithms increases with the increasing of the training sample data scale, affecting the classification efficiency of the algorithm. Aiming at this shortage, this paper will improve the original parallelization KNN algorithm in the MapReduce model, adding the text pretreatment process to improve the classification efficiency of the algorithm.

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Zaharov, D. O., and A. P. Karpenko. "Study of League Championship Algorithm Efficiency for Global Optimization Problem." Mathematics and Mathematical Modeling, no. 2 (June 9, 2020): 25–45. http://dx.doi.org/10.24108/mathm.0220.0000217.

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The article objective is to study a new League Championship Algorithm (LCA) algorithm efficiency by its comparing with the efficiency of the Particle Swarm optimization (PSO) algorithm.The article presents a brief description of the terms used in the League Championship algorithm, describes the basic rules of the algorithm, on the basis of which the iterative process for solving the global optimization problem is built.Gives a detailed description of the League Championship algorithm, which comprises a flowchart of the algorithm, as well as a formalization of all its main steps.Depicts an exha

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Yang, Wen Jun. "Efficient Pattern Matching Algorithm for Intrusion Detection Systems." Applied Mechanics and Materials 511-512 (February 2014): 1178–84. http://dx.doi.org/10.4028/www.scientific.net/amm.511-512.1178.

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To overcome the defects of low efficiency of pattern matching in intrusion detection systems (IDS), an efficient pattern matching algorithm is proposed. The proposed algorithm first preprocesses pattern to record pattern information, then it recursive compares the nodes to find the most common part of pattern to improve efficiency. The proposed algorithm also appends auxiliary structure of m nodes in pattern to reduce time and space complexity. Theoretical analysis shows that for the subject with n nodes, the time complexity of the proposed algorithm is, and space complexity is . Detailed expe

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Liao, Xiong, Junxiong Guo, Zhenghua Luo, Yanghui Xu, and Yingjun Chu. "Research and Implementation of High-Efficiency and Low-Complexity LDPC Coding Algorithm." Electronics 12, no. 17 (2023): 3696. http://dx.doi.org/10.3390/electronics12173696.

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In this work, we proposed a high-efficiency and low-complexity encoding algorithm and its corresponding implementation structure during the design and implementation process of an LDPC encoder and decoder. This proposal was derived from extensive research on and analysis of standard encoding algorithms and recursive iterative encoding algorithms, specifically targeting the problem of high computational complexity in encoding algorithms. Subsequently, we combined binary phase-shift keying modulation mode and additive white Gaussian noise channel transmission with the min-sum decoding algorithm

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Markić, Ivan, Maja Štula, Marija Zorić, and Darko Stipaničev. "Entropy-Based Approach in Selection Exact String-Matching Algorithms." Entropy 23, no. 1 (2020): 31. http://dx.doi.org/10.3390/e23010031.

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The string-matching paradigm is applied in every computer science and science branch in general. The existence of a plethora of string-matching algorithms makes it hard to choose the best one for any particular case. Expressing, measuring, and testing algorithm efficiency is a challenging task with many potential pitfalls. Algorithm efficiency can be measured based on the usage of different resources. In software engineering, algorithmic productivity is a property of an algorithm execution identified with the computational resources the algorithm consumes. Resource usage in algorithm execution

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Gracios, Anita, and Prof Arun Jhapate. "An Effective Routing Algorithm to Enhance Efficiency with WSN." International Journal of Trend in Scientific Research and Development Volume-2, Issue-3 (2018): 301–4. http://dx.doi.org/10.31142/ijtsrd10879.

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Nurmana, Ayyub Hamdanu Budi, Mars Caroline Wibowo, and Sarwo Nugroho. "Enhancing Image Denoising Efficiency: Dynamic Transformations in BM3D Algorithm." Journal of Image and Graphics 12, no. 4 (2024): 332–44. http://dx.doi.org/10.18178/joig.12.4.332-344.

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This research aims to enhance the performance of image-denoising algorithms, particularly in the context of Block Matching 3D (BM3D) usage, focusing on improving image quality and retaining important information in noisy images. The novelty of this research lies in developing more effective and efficient image-denoising techniques by considering the characteristics of image blocks to improve denoising results. The method employed in this research involves the development of a new approach enabling the application of adaptive 2D and 3D transformations depending on the characteristics of the ima

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Seliverstov, E. Yu. "Structural Mapping of Global Optimization Algorithms to Graphics Processing Unit Architecture." Herald of the Bauman Moscow State Technical University. Series Instrument Engineering, no. 2 (139) (June 2022): 42–59. http://dx.doi.org/10.18698/0236-3933-2022-2-42-59.

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Graphics processing units (GPU) deliver a high execution efficiency for modern metaheuristic algorithms with a high computation complexity. It is crucial to have an optimal task mapping of the optimization algorithm to the parallel system architecture which strongly affects the efficiency of the optimization process. The paper proposes a novel task mapping algorithm of the parallel metaheuristic algorithm to the GPU architecture, describes problem statement for the mapping of algorithm graph model to the GPU model, and gives a formal definition of graph mapping and mapping restrictions. The al

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Ahmadi, Farrokh, Abbas Toloie Eshlaghi, and Reza Radfar. "Examining and Comparing the Efficiency of MLP and SimpleRNN Algorithms in Cryptocurrency Price Prediction." Management Strategies and Engineering Sciences 6, no. 3 (2024): 121–37. https://doi.org/10.61838/msesj.6.3.12.

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Cryptocurrencies have been widely identified and established as a new form of electronic currency exchange, carrying significant implications for emerging economies and the global economy. This research focused on the "examination and comparison of the efficiency of MLP and SimpleRNN algorithms in predicting cryptocurrency prices" using the Python programming language. Price predictions for Bitcoin, Ethereum, Binance Coin, Cardano, and Ripple were made using two deep learning algorithms (including the MLP algorithm and the SimpleRNN algorithm) over the period from 2017 to 2023. The results of

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Bhavani, Ch, and P. Madhavi. "Improving Efficiency of Apriori Algorithm." International Journal of Computer Trends and Technology 27, no. 2 (2015): 93–99. http://dx.doi.org/10.14445/22312803/ijctt-v27p116.

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Sadullaeva, Sh. "Analysis of the efficiency of SHA algorithms based on message length." Международный Журнал Теоретических и Прикладных Вопросов Цифровых Технологий 8, no. 1 (2025): 164–74. https://doi.org/10.62132/ijdt.v8i1.245.

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This study analyzes the efficiency of SHA (Secure Hash Algorithm) family algorithms depending on message length. The execution time of hashing processes for SHA-1 and SHA-2 (SHA-224, SHA-256, SHA-384, SHA-512) algorithms is compared across various message lengths. Python programming language is used for implementation, and the results are presented in graphical and tabular forms. The study examines the computational complexity and performance speed of these algorithms. The main objective is to determine the efficiency of each algorithm relative to message length and recommend an optimal option

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Moldovan, Dorin. "Plum Tree Algorithm and Weighted Aggregated Ensembles for Energy Efficiency Estimation." Algorithms 16, no. 3 (2023): 134. http://dx.doi.org/10.3390/a16030134.

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This article introduces a novel nature-inspired algorithm called the Plum Tree Algorithm (PTA), which has the biology of the plum trees as its main source of inspiration. The PTA was tested and validated using 24 benchmark objective functions, and it was further applied and compared to the following selection of representative state-of-the-art, nature-inspired algorithms: the Chicken Swarm Optimization (CSO) algorithm, the Particle Swarm Optimization (PSO) algorithm, the Grey Wolf Optimizer (GWO), the Cuckoo Search (CS) algorithm, the Crow Search Algorithm (CSA), and the Horse Optimization Alg

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Xiao, Qian Cai, Ming Qi Li, and Wen Qiang Guo. "Experimental Study of Dynamic Single-Source Shortest Path Algorithm." Applied Mechanics and Materials 58-60 (June 2011): 1493–98. http://dx.doi.org/10.4028/www.scientific.net/amm.58-60.1493.

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In this paper, software Inet 3.0 is applied to generate topology, which randomly generates dynamic topology nodes. Based on dynamic shortest path algorithms put forward by P.Narvaez, Xiaobin et al, we analyzed the time efficiency of dynamic and static shortest path algorithms, the different time efficiency inner dynamic shortest path algorithms, and the relationship of time efficiency between topology and dynamic shortest path algorithms. The result shows that Xiaobin algorithm is statistically better than Narvaez algorithm about 20-30 percent. Dynamic algorithms are not always better than sta

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Moayedi, A., R. A. Abbaspour, and A. Chehreghan. "A COMPARISON OF EFFICIENCY OF THE OPTIMIZATION APPROACH FOR CLUSTERING OF TRAJECTORIES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W18 (October 18, 2019): 737–40. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w18-737-2019.

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Abstract. Clustering is an unsupervised learning method that used to discover hidden patterns in large sets of data. Huge data volume and the multidimensionality of trajectories have made their clustering a more challenging task. K-means is a widely used clustering algorithm applied in the trajectory computation field. However, the critical issue with this algorithm is its dependency on the initial values and getting stuck in the local minimum. Meta-heuristic algorithms with the goal of minimizing the cost function of the K-means algorithm can be utilized to address this problem. In this paper

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Poddubnyi, Vadym, Oleksandr Sievierinov, and Dmytro Nepokrytov. "Research the efficiency of image processing algorithms in zero watermark schemes." INNOVATIVE TECHNOLOGIES AND SCIENTIFIC SOLUTIONS FOR INDUSTRIES, no. 1(31) (March 31, 2025): 102–14. https://doi.org/10.30837/2522-9818.2025.1.102.

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Subject matter: image transformation algorithms used in zero-watermarking techniques for development authentication algorithm. Objectives: identify effective image transformation algorithms for use in zero-watermarking schemes. The study addresses the following tasks: examining the range of existing image transformation algorithms, formulating informal requirements for image transformation algorithms to be used in zero-watermarking-based authentication schemes, and making assumptions about the feasibility of using each analyzed image transformation algorithm. To achieve these objectives, the f

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Chen, Jie. "AIRRT*: An improved fast path planning algorithm for manipulators." Journal of Physics: Conference Series 2390, no. 1 (2022): 012088. http://dx.doi.org/10.1088/1742-6596/2390/1/012088.

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Abstract Path planning algorithms based on sampling have been widely studied and applied in recent years, among which the Informed-RRT* algorithm is a typically progressive optimization algorithm. To overcome the weakness of low optimization efficiency of the Informed-RRT* algorithm, an improved algorithm AIRRT* (Adaptive Informed-RRT*) is proposed, which can greatly improve optimization efficiency and improve the quality of optimized paths. According to the node distribution of the initial path, the appropriate node construction areas are dynamically selected first in the process of direct lo

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Shen, Linbang, Zhigang Chu, Yongxiang Zhang, and Yang Yang. "A novel Fourier-based deconvolution algorithm with improved efficiency and convergence." Journal of Low Frequency Noise, Vibration and Active Control 39, no. 4 (2019): 866–78. http://dx.doi.org/10.1177/1461348419873471.

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Various deconvolution algorithms for acoustic source are developed to improve spatial resolution and suppress sidelobe of the conventional beamforming. To improve the computational efficiency and solution convergence of deconvolution, this paper proposes a Fourier-based improved fast iterative shrinkage thresholding algorithm. Simulations and experiments show that Fourier-based improved fast iterative shrinkage thresholding algorithm can achieve excellent acoustic identification performance, with high computational efficiency and good convergence. For Fourier-based improved fast iterative shri

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Et. al., Siva Sankara Phani T. ,. "CGRA MODULO SCHEDULING FOR ACHIEVING BETTER PERFORMANCE AND INCREASED EFFICIENCY." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 4 (2021): 1400–1413. http://dx.doi.org/10.17762/turcomat.v12i4.1225.

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Coarse-Grained Reconfigurable Architectures (CGRA) is an effective solution for speeding up computer-intensive activities due to its high energy efficiency and flexibility sacrifices. The timely implementation of CGRA loops was one of the hardest problems in the analysis. Modulo scheduling (MS) was productive in order to implement loops on CGRAs. The problem remains with current MS algorithms, namely to map large and irregular circuits to CGRAs over a fair period of compilation with restricted computational and high-performance routing tools. This is mainly due to an absence of awareness of ma

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WANG, MONAN, SHAOYONG CHEN, and QIYOU YANG. "DESIGN AND APPLICATION OF BOUNDING VOLUME HIERARCHY COLLISION DETECTION ALGORITHM BASED ON VIRTUAL SPHERE." Journal of Mechanics in Medicine and Biology 19, no. 07 (2019): 1940044. http://dx.doi.org/10.1142/s021951941940044x.

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The result of collision detection is closely related to the further deformation or cutting action of soft tissue. In order to further improve the efficiency and stability of collision detection, in this paper, a collision detection algorithm of bounding volume hierarchy based on virtual sphere was proposed. The proposed algorithm was validated and the results show that the detection efficiency of the bounding volume hierarchy algorithm based on virtual sphere is higher than that of the serial hybrid bounding volume hierarchy algorithm and the parallel hybrid bounding volume hierarchy algorithm

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Guo, Xiaomin, Yongxing Cao, Jian Zhou, Yuanxian Huang, and Bijun Li. "HDM-RRT: A Fast HD-Map-Guided Motion Planning Algorithm for Autonomous Driving in the Campus Environment." Remote Sensing 15, no. 2 (2023): 487. http://dx.doi.org/10.3390/rs15020487.

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On campus, the complexity of the environment and the lack of regulatory constraints make it difficult to model the environment, resulting in less efficient motion planning algorithms. To solve this problem, HD-Map-guided sampling-based motion planning is a feasible research direction. We proposed a motion planning algorithm for autonomous vehicles on campus, called HD-Map-guided rapidly-exploring random tree (HDM-RRT). In our algorithm, A collision risk map (CR-Map) that quantifies the collision risk coefficient on the road is combined with the Gaussian distribution for sampling to improve the

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Harvey, Charles, and Edmund Green. "Record Linkage Algorithms: Efficiency, Selection and Relative Confidence." History and Computing 6, no. 3 (1994): 143–52. http://dx.doi.org/10.3366/hac.1994.6.3.143.

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Using the case material of the Westminster Historical Database, this article describes how 30 record linkage algorithms were evaluated to select the optimum algorithm for linking poll book data. It stresses the importance of relative confidence in linkage algorithms, and shows how more discriminating algorithms may increase both confidence in linked records and rates of record linkage.

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Sevin, Abdullah, and Ünal Çavuşoğlu. "Design and Performance Analysis of a SPECK-Based Lightweight Hash Function." Electronics 13, no. 23 (2024): 4767. https://doi.org/10.3390/electronics13234767.

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In recent years, hash algorithms have been used frequently in many areas, such as digital signature, blockchain, and IoT applications. Standard cryptographic hash functions, including traditional algorithms such as SHA-1 and MD5, are generally computationally intensive. A principal approach to improving the security and efficiency of hash algorithms is the integration of lightweight algorithms, which are designed to minimize computational overhead, into their architectural framework. This article proposes a new hash algorithm based on lightweight encryption. A new design for the lightweight ha

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Pujiono, Imam Prayogo, Eko Hari Rachmawanto, and Nurul Anisa Sri Winarsih. "Array Sorting Algorithm vs Traditional Sorting Algorithm: Memory and Time Efficiency Analysis." Jurnal Manajemen Informatika (JAMIKA) 15, no. 1 (2025): 47–59. https://doi.org/10.34010/jamika.v15i1.13230.

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The development of information technology has changed various aspects of life, including the way we store and sort data. Data that used to be stored in filing cabinets is now stored in digital form on computers. However, digital data that is not well organised can make it difficult to search and verify. Therefore, data sorting has become very important, and various sorting algorithms have been developed to fulfil this need, such as the Array Sorting Algorithm (ASA), which is claimed to have efficient time complexity and is very competitive when compared to the time complexity of traditional al

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Shen, Lingli. "Implementation of CT Image Segmentation Based on an Image Segmentation Algorithm." Applied Bionics and Biomechanics 2022 (October 12, 2022): 1–11. http://dx.doi.org/10.1155/2022/2047537.

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With the increasingly important role of image segmentation in the field of computed tomography (CT) image segmentation, the requirements for image segmentation technology in related industries are constantly improving. When the hardware resources can fully meet the needs of the fast and high-precision image segmentation program system, the main means of how to improve the image segmentation effect is to improve the related algorithms. Therefore, this study has proposed a combination of genetic algorithm (GA) and Great Law (OTSU) algorithm to form an image segmentation algorithm-immune genetic

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Ma, Xiangbo. "The impact of AI on algorithm design innovations and practical applications." Edelweiss Applied Science and Technology 9, no. 3 (2025): 1121–27. https://doi.org/10.55214/25768484.v9i3.5436.

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Artificial intelligence (AI) has greatly influenced the innovation and practical application of algorithm design. With the rapid development of AI technology, the traditional algorithm design paradigm is undergoing profound changes. AI leverages machine and deep learning to automate algorithm optimization and adaptation for tasks and environments. This involves selecting suitable models and preparing specific datasets for training and validation. It also includes implementing complex algorithms for automatic optimization, allowing models to learn and improve over time with minimal manual inter

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Kim, Bong-seok, Youngseok Jin, Jonghun Lee, and Sangdong Kim. "High-Efficiency Super-Resolution FMCW Radar Algorithm Based on FFT Estimation." Sensors 21, no. 12 (2021): 4018. http://dx.doi.org/10.3390/s21124018.

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This paper proposes a high-efficiency super-resolution frequency-modulated continuous-wave (FMCW) radar algorithm based on estimation by fast Fourier transform (FFT). In FMCW radar systems, the maximum number of samples is generally determined by the maximum detectable distance. However, targets are often closer than the maximum detectable distance. In this case, even if the number of samples is reduced, the ranges of targets can be estimated without degrading the performance. Based on this property, the proposed algorithm adaptively selects the number of samples used as input to the super-res

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Yang, Ruohan, and Zijun Zhong. "Algorithm efficiency and hybrid applications of quantum computing." Theoretical and Natural Science 11, no. 1 (2023): 279–89. http://dx.doi.org/10.54254/2753-8818/11/20230419.

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With the development of science and technology, it is difficult for traditional computers to solve cutting-edge problems due to the lack of computing power, and the importance of quantum computers is increasing day by day. This article starts with the simple principle of quantum computing, introduces the most advanced quantum computing instruments and quantum computing algorithms, and points out the application prospects in medicine, chemistry and other fields. This paper explains the basic principles of quantum computing algorithms, their efficiency over traditional algorithms, and focuses on

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Loo, Chang Herng, M. Zulfahmi Toh, Ahmad Fakhri Ab. Nasir, Nur Shazwani Kamaruddin, and Nur Hafieza Ismail. "Efficiency and Accuracy of Scheduling Algorithms for Final Year Project Evaluation Management System." MEKATRONIKA 5, no. 2 (2023): 23–31. http://dx.doi.org/10.15282/mekatronika.v5i2.9973.

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Scheduling algorithms play a crucial role in optimizing the efficiency and precision of scheduling tasks, finding applications across various domains to enhance work productivity, reduce costs, and save time. This research paper conducts a comparative analysis of three algorithms: genetic algorithm, hill climbing algorithm, and particle swarm optimization algorithm, with a focus on evaluating their performance in scheduling presentations. The primary goal of this study is to assess the effectiveness of these algorithms and identify the most efficient one for handling presentation scheduling ta

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Naeem, Usman, and Muhammad Mateen Afzal Awan. "Maximizing off-grid solar photovoltaic system efficiency through cutting-edge performance optimization technique for incremental conductance algorithm." Mehran University Research Journal of Engineering and Technology 43, no. 3 (2024): 113. http://dx.doi.org/10.22581/muet1982.3135.

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The maximum power point tracking (MPPT) algorithms are required to deliver the optimal energy from solar photovoltaic cells/array (PV) under numerous weather conditions. Therefore, MPPT circuits driven by defined rules called algorithms are designed. These algorithms range from simple to complex in design and implementation and are selected based on the scenarios of the surroundings. However, the incremental conductance (InC) MPPT algorithm is one of the market's most simple, easy to implement, and demanding algorithms. The drawback associated with the InC algorithm is its tracking speed. To o

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Zhang, Wei, and Qian Xu. "Optimization of College English Classroom Teaching Efficiency by Deep Learning SDD Algorithm." Computational Intelligence and Neuroscience 2022 (January 21, 2022): 1–10. http://dx.doi.org/10.1155/2022/1014501.

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In order to improve the teaching efficiency of English teachers in classroom teaching, the target detection algorithm in deep learning and the monitoring information from teachers are used, the target detection algorithm of deep learning Single Shot MultiBox Detector (SSD) is optimized, and the optimized Mobilenet-Single Shot MultiBox Detector (Mobilenet-SSD) is designed. After analyzing the Mobilenet-SSD algorithm, it is recognized that the algorithm has the shortcomings of large amount of basic network parameters and poor small target detection. The deficiencies are optimized in the followin

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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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Ali, Abdulrazzak, Nurul Akmar Emran, Safiza Suhana Kamal Baharin, et al. "Improving the efficiency of clustering algorithm for duplicates detection." Indonesian Journal of Electrical Engineering and Computer Science 30, no. 3 (2023): 1586. http://dx.doi.org/10.11591/ijeecs.v30.i3.pp1586-1595.

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Clustering method is a technique used for comparisons reduction between the candidates records in the duplicate detection process. The process of clustering records is affected by the quality of data. The more error-free the data, the more efficient the clustering algorithm, as data errors cause data to be placed in incorrect groups. Window algorithms suffer from the window size. The larger the window, the greater the number of unnecessary comparisons, and the smaller the window size may prevent the detection of duplicates that are supposed to be within the window. In this paper, we propose a

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Abdulrazzak, Ali, Akmar Emran Nurul, Suhana Kamal Baharin Safiza, et al. "Improving the efficiency of clustering algorithm for duplicates detection." Improving the efficiency of clustering algorithm for duplicates detection 30, no. 3 (2023): 1586–95. https://doi.org/10.11591/ijeecs.v30.i3.pp1586-1595.

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Abstract (sommario):

Clustering method is a technique used for comparisons reduction between the candidates records in the duplicate detection process. The process of clustering records is affected by the quality of data. The more error-free the data, the more efficient the clustering algorithm, as data errors cause data to be placed in incorrect groups. Window algorithms suffer from the window size. The larger the window, the greater the number of unnecessary comparisons, and the smaller the window size may prevent the detection of duplicates that are supposed to be within the window. In this paper, we propose a

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Parfenov, V. I., and V. D. Le. "DISTRIBUTED DETECTION BASED ON USING SOFT DECISION DECODING IN A FUSION CENTER." Telecommunications, no. 1 (2022): 2–9. http://dx.doi.org/10.31044/1684-2588-2022-0-1-2-9.

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In this work, distributed detection by data from many sensors in the wireless sensor system is considered. A decision-making algorithm based on using soft-decision decoding in a fusion center is synthesized. Its gain in efficiency compared to efficiency of the algorithm based on hard-decision scheme is shown. It is noted that this algorithm is a generalization of earlier developed algorithms.

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G B, Suba Santhosi. "A Light Weight Optimal Resource Scheduling Algorithm for Energy Efficient and Real Time Cloud Services." International Journal for Research in Applied Science and Engineering Technology 11, no. 5 (2023): 1953–62. http://dx.doi.org/10.22214/ijraset.2023.51985.

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Abstract: Cloud computing has become an essential technology for providing various services to customers. Energy consumption and response time are critical factors in cloud computing systems. Therefore, scheduling algorithms play a vital role in optimizing resource usage and improving energy efficiency. In this paper, we propose a lightweight optimal scheduling algorithm for energy-efficient and real-time cloud services. Our algorithm considers the trade-off between energy consumption and response time and provides a solution that optimizes both factors. We evaluate our algorithm on a cloud co

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Wang, Huanwei, Xuyan Qi, Shangjie Lou, Jing Jing, Hongqi He, and Wei Liu. "An Efficient and Robust Improved A* Algorithm for Path Planning." Symmetry 13, no. 11 (2021): 2213. http://dx.doi.org/10.3390/sym13112213.

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Path planning plays an essential role in mobile robot navigation, and the A* algorithm is one of the best-known path planning algorithms. However, the conventional A* algorithm and the subsequent improved algorithms still have some limitations in terms of robustness and efficiency. These limitations include slow algorithm efficiency, weak robustness, and collisions when robots are traversing. In this paper, we propose an improved A*-based algorithm called EBHSA* algorithm. The EBHSA* algorithm introduces the expansion distance, bidirectional search, heuristic function optimization and smoothin

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Qiu, Liqing, Shuang Zhang, Chunmei Gu, and Xiangbo Tian. "Scalable Influence Maximization Meets Efficiency and Effectiveness in Large-Scale Social Networks." International Journal of Software Engineering and Knowledge Engineering 30, no. 08 (2020): 1079–96. http://dx.doi.org/10.1142/s0218194020400161.

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Influence maximization is a problem that aims to select top [Formula: see text] influential nodes to maximize the spread of influence in social networks. The classical greedy-based algorithms and their improvements are relatively slow or not scalable. The efficiency of heuristic algorithms is fast but their accuracy is unacceptable. Some algorithms improve the accuracy and efficiency by consuming a large amount of memory usage. To overcome the above shortcoming, this paper proposes a fast and scalable algorithm for influence maximization, called K-paths, which utilizes the influence tree to es

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Mramba, Lazarus, and Salvador Gezan. "Evaluating Algorithm Efficiency for Optimizing Experimental Designs with Correlated Data." Algorithms 11, no. 12 (2018): 212. http://dx.doi.org/10.3390/a11120212.

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The search for efficient methods and procedures to optimize experimental designs is a vital process in field trials that is often challenged by computational bottlenecks. Most existing methods ignore the presence of some form of correlations in the data to simplify the optimization process at the design stage. This study explores several algorithms for improving field experimental designs using a linear mixed models statistical framework adjusting for both spatial and genetic correlations based on A- and D-optimality criteria. Relative design efficiencies are estimated for an array of algorith

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Dai, Cai, and Xiujuan Lei. "A Multiobjective Brain Storm Optimization Algorithm Based on Decomposition." Complexity 2019 (January 22, 2019): 1–11. http://dx.doi.org/10.1155/2019/5301284.

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Brain storm optimization (BSO) algorithm is a simple and effective evolutionary algorithm. Some multiobjective brain storm optimization algorithms have low search efficiency. This paper combines the decomposition technology and multiobjective brain storm optimization algorithm (MBSO/D) to improve the search efficiency. Given weight vectors transform a multiobjective optimization problem into a series of subproblems. The decomposition technology determines the neighboring clusters of each cluster. Solutions of adjacent clusters generate new solutions to update population. An adaptive selection

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Anita, Mahato* Kailash Patidar. "A REVIWE ARTICLE OF COMPARITIVELY ANALYSIS OF DEEC PROTOCOL." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 6, no. 6 (2017): 113–17. https://doi.org/10.5281/zenodo.805385.

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Energy Management can be improved by proficient clustering algorithms in heterogeneous wireless sensor networks. Coordination through cluster head selection provides efficient data aggregation that reduces communication overhead in the network. In this paper, we propose a fuzzy logic approach based DDEEC clustering algorithm which aims to prolong the lifetime of nodes in heterogeneous WSNs. We compare this algorithm with the PSO based DDEEC algorithm and original DDEEC algorithm according to the parameters of first node dies at different rounds and energy-efficiency metrics. The efficiency of

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Zhang, Bai, Haofang Liu, and Feng Gao. "Research on an Improved Sliding Extracting Algorithm of Composite Deviation for Wind Turbine Gear." Journal of Physics: Conference Series 2218, no. 1 (2022): 012046. http://dx.doi.org/10.1088/1742-6596/2218/1/012046.

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Abstract One tooth radial composite deviation and one tooth tangential composite deviation are important parameters of wind turbine gears whose operation life cycle can be influenced. An improved sliding extracting algorithm of composite deviation is proposed. It just only calculates those parts that need to be recalculated, avoids a large number of invalid searching calculations, and greatly improves the efficiency. The experimental results show that the improved sliding extracting algorithm of composite deviation has the same results as the traditional extracting algorithm, and the efficienc

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PAN, Guan-hua, and Xing-zhong ZHANG. "Study on efficiency of Sunday algorithm." Journal of Computer Applications 32, no. 11 (2013): 3082–84. http://dx.doi.org/10.3724/sp.j.1087.2012.03082.

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