Academic literature on the topic 'Algorithm efficiency'

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Journal articles on the topic "Algorithm efficiency"

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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 purpose. The purpose of this paper is to research the efficiency of the algorithm portfolios by solving the weighted max-cut problem. The research is carried out in two stages using stochastic local search algorithms. Results. In this paper, we investigate homogeneous and non-homogeneous algorithm portfolios. We developed the homogeneous portfolios of two stochastic local optimization algorithms for the weighted max-cut problem, which has numerous applications. The results confirm the advantages of the proposed methods. Conclusions. Algorithm portfolios could be used to solve well-known discrete optimization problems of unprecedented scale and significantly improve their solving time. Further, we propose using communication between algorithms, namely teams and portfolios of algorithm teams. The algorithms in a team communicate with each other to boost overall performance. It is supposed that algorithm communication allows enhancing the best features of the developed algorithms and would improve the computational times and solution quality. The underlying algorithms should be able to utilize relevant data that is being communicated effectively to achieve any computational benefit from communication. Keywords: Discrete optimization, algorithm portfolios, computational experiment.
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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 conducting experiments.
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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 algorithms with computation, CoroGraph extensively uses coroutine , i.e., a lightweight function in C++ that can yield and resume with low overhead, to prefetch the required data. A suite of designs are incorporated to reap the full benefits of coroutine, which include prefetch pipeline, cache-friendly graph format, and stop-free synchronization. We compare CoroGraph with five state-of-the-art graph algorithm systems via extensive experiments. The results show that CoroGraph yields shorter algorithm execution time than all baselines in 18 out of 20 cases, and its speedup over the best-performing baseline can be over 2x. Detailed profiling suggests that CoroGraph achieves both cache efficiency and work efficiency with a low memory stall and a small number of processed edges.
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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 algorithm is accounted for by the obvious reduction in the number of operations and operators in the simplified Bluestein algorithms. The SBTNADSP is designed to have four products, and three exponentiations against the default Bluestein FFT algorithm which has six exponentiations and eight products. Since the increase in the number of operators increases the length of operation, it is therefore reasonable to infer that the algorithm with the less number of operators will run shorter execution time than the one with greater operators. In line with this, we conclude that SBNADSP is of greater efficiency than the Bluestein numerical algorithm. The result of this study showed that a faster numerical algorithm other than the Bluestein fft algorithms is possible for the processing of digital signals.
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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 reduce data transfer time over the network. Every year, programmers, scientists, and researchers look for ways to improve existing algorithms, as well as invent new ones, because every algorithm, even if it is simple, has its potential for improvement. A wide range of technologies related to the collection, processing, storage and transmission of information are largely oriented towards the development of systems in which graphical presentation of information has an advantage over other types of presentation. The development of modern computer systems and networks has influenced the wide distribution of tools operating with digital images. It is clear that storing and transferring a large number of images in their original, unprocessed form is a rather resource-intensive task. In turn, modern multimedia systems have gained considerable popularity thanks, first of all, to effective means of compressing graphic information. Image compression is a key factor in improving the efficiency of data transfer and the use of computing resources. The work is devoted to the study of the modification of the data compression algorithm The Quite OK Image Format, or QOI, which is optimized for speed for the compression of graphic information. Testing of those implementations of the algorithm, which were proposed by its author, shows such encouraging results that it can make it competitive with the already known PNG algorithm, providing a higher compression speed and targeting work with archives. The article compares the results of the two proposed modifications of the algorithm with the original implementation and shows their advantages. The effectiveness of the modifications and the features of their application for various cases were evaluated. A comparison of file compression coefficients, which were compressed by the original QOI algorithm, with such coefficients, which were obtained as a result of the application of modifications of its initial version, was also carried out.
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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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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 on a novel approach that uses a combination of dynamic programming and greedy algorithms. We prove that our algorithm is correct and efficient, and we demonstrate its effectiveness on a variety of graphs.The key features of our new algorithm are as follows: It is a dynamic programming algorithm, which means that it works by breaking the problem down into smaller subproblems and solving them recursively. It uses a greedy approach to choose the edges to be included in the matching. It is efficient, and it can find the maximum matching in a graph in polynomial time. We evaluated our new algorithm on a variety of graphs. Our results show that our algorithm is significantly more efficient than existing algorithms. For example, on a graph with 100 vertices, our algorithm can find the maximum matching in 0.01 seconds, while the brute-force algorithm takes 100 seconds. Our new algorithm is a significant improvement over existing algorithms for finding the maximum matching in a graph. It is more efficient, and it can be used to solve larger graphs. We believe that our algorithm will be useful in many applications.  
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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 exhaustive description of the software developed to implement the League Championship algorithm to solve global optimization problems.Briefly describes the modified particle swarm algorithm. Presents the values of all free parameters of the algorithm and the algorithm modifications, which make it different from the classical version, as well.The main part of the article shows the results of a great deal of computational experiments using two abovementioned algorithms. All the performance criteria, used for assessment of the algorithms efficiency, are given.Computational experiments were performed using the spherical function, as well as the Rosenbrock, Rastrigin, and Ackley functions. The results of the experiments are summarized in Tables, and also illustrated in Figures. Experiments were performed for the vector dimension of the variable parameters that is equal to 2, 4, 8, 16, 32, and 64.An analysis of the results of computational experiments involves a full assessment of the efficiency of the League Championship algorithm, and also provides an answer about expediency for further algorithm development.It is shown that the League Championship algorithm presented in the article has a high development potential and needs further work for its study.
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Dissertations / Theses on the topic "Algorithm efficiency"

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Morgan, Wiley Spencer. "Increasing the Computational Efficiency of Combinatoric Searches." BYU ScholarsArchive, 2016. https://scholarsarchive.byu.edu/etd/6528.

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A new algorithm for the enumeration of derivative superstructures of a crystal is presented. The algorithm will help increase the efficiency of computational material design methods such as cluster expansion by increasing the size and diversity of the types of systems that can be modeled. Modeling potential alloys requires the exploration of all possible configurations of atoms. Additionally, modeling the thermal properties of materials requires knowledge of the possible ways of displacing the atoms. One solution to finding all symmetrically unique configurations and displacements is to generate the complete list of possible configurations and remove those that are symmetrically equivalent. This approach, however, suffers from the combinatoric explosion that happens when the supercell size is large, when there are more than two atom types, or when atomic displacements are included in the system. The combinatoric explosion is a problem because the large number of possible arrangements makes finding the relatively small number of unique arrangements for these systems impractical. The algorithm presented here is an extension of an existing algorithm [Hart & Forcade (2008a), Hart & Forcade (2009a), Hart et al. (2012a) Hart, Nelson, & Forcade] to include the extra configurational degree of freedom from the inclusion of displacement directions. The algorithm makes use of another recently developed algorithm for the Pólya [Pólya & Read (1987), Pólya (1937), Rosenbrock et al.(2015) Rosenbrock, Morgan, Hart, Curtarolo, & Forcade] counting theorem to inform the user of the total number of unique arrangements before performing the enumeration and to ensure that the list of unique arrangements will fit in system memory. The algorithm also uses group theory to eliminate large classes of arrangements rather than eliminating arrangements one by one. The three major topics of this paper will be presented in this order, first the Pólya algorithm, second the new algorithm for eliminating duplicate structures, and third the algorithms extension to include displacement directions. With these tools, it is possible to avoid the combinatoric explosion and enumerate previously inaccessible systems, including those that contain displaced atoms.
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Batbayar, Batsukh, and S3099885@student rmit edu au. "Improving Time Efficiency of Feedforward Neural Network Learning." RMIT University. Electrical and Computer Engineering, 2009. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20090303.114706.

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Feedforward neural networks have been widely studied and used in many applications in science and engineering. The training of this type of networks is mainly undertaken using the well-known backpropagation based learning algorithms. One major problem with this type of algorithms is the slow training convergence speed, which hinders their applications. In order to improve the training convergence speed of this type of algorithms, many researchers have developed different improvements and enhancements. However, the slow convergence problem has not been fully addressed. This thesis makes several contributions by proposing new backpropagation learning algorithms based on the terminal attractor concept to improve the existing backpropagation learning algorithms such as the gradient descent and Levenberg-Marquardt algorithms. These new algorithms enable fast convergence both at a distance from and in a close range of the ideal weights. In particular, a new fast convergence mechanism is proposed which is based on the fast terminal attractor concept. Comprehensive simulation studies are undertaken to demonstrate the effectiveness of the proposed backpropagataion algorithms with terminal attractors. Finally, three practical application cases of time series forecasting, character recognition and image interpolation are chosen to show the practicality and usefulness of the proposed learning algorithms with comprehensive comparative studies with existing algorithms.
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Freund, Robert M. "Theoretical Efficiency of A Shifted Barrier Function Algorithm for Linear Programming." Massachusetts Institute of Technology, Operations Research Center, 1989. http://hdl.handle.net/1721.1/5185.

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This paper examines the theoretical efficiency of solving a standard-form linear program by solving a sequence of shifted-barrier problems of the form minimize cTx - n (xj + ehj) j.,1 x s.t. Ax = b , x + e h > , for a given and fixed shift vector h > 0, and for a sequence of values of > 0 that converges to zero. The resulting sequence of solutions to the shifted barrier problems will converge to a solution to the standard form linear program. The advantage of using the shiftedbarrier approach is that a starting feasible solution is unnecessary, and there is no need for a Phase I-Phase II approach to solving the linear program, either directly or through the addition of an artificial variable. Furthermore, the algorithm can be initiated with a "warm start," i.e., an initial guess of a primal solution x that need not be feasible. The number of iterations needed to solve the linear program to a desired level of accuracy will depend on a measure of how close the initial solution x is to being feasible. The number of iterations will also depend on the judicious choice of the shift vector h . If an approximate center of the dual feasible region is known, then h can be chosen so that the guaranteed fractional decrease in e at each iteration is (1 - 1/(6 i)) , which contributes a factor of 6 ii to the number of iterations needed to solve the problem. The paper also analyzes the complexity of computing an approximate center of the dual feasible region from a "warm start," i.e., an initial (possibly infeasible) guess ir of a solution to the center problem of the dual. Key Words: linear program, interior-point algorithm, center, barrier function, shifted-barrier function, Newton step.
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Khudhair, Ali Dheyaa. "A Simplified Routing Algorithm for Energy Efficiency in Wireless Sensor Networks." Available to subscribers only, 2009. http://proquest.umi.com/pqdweb?did=1885751071&sid=8&Fmt=2&clientId=1509&RQT=309&VName=PQD.

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Lindberg, Joakim, and Martin Steier. "Efficiency of the hybrid AC3-tabu search algorithm for solving Sudoku puzzles." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-166421.

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There are many different algorithms for solving Sudoku puzzles, with one of the newer algorithms being the hybrid AC3-tabu search algorithm. Since the algorithm has not been subject of much research, the aim of this thesis is to increase the knowledge of it. This thesis evaluates the efficiency of the hybrid AC3-tabu search algorithm by analyzing how quickly it solves puzzles compared to two other solving algorithms: one using brute-force search, and one combining human solving techniques with brute-force search. This thesis also investigates if there is a correlation between the number of puzzle clues and the solving time for the hybrid AC3-tabu search algorithm. The results show that the hybrid AC3-tabu search algorithm is less efficient than the two other algorithms, and that there seems to be a correlation between the number of clues and the solving time for the algorithm. The conclusion is that due to the algorithm’s low efficiency and some of its characteristics, it is not suitable for solving Sudoku puzzles.
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Chen, Daven 1959. "COMPARISON OF SCIRTSS EFFICIENCY WITH D-ALGORITHM APPLICATION TO ITERATIVE NETWORKS (TEST)." Thesis, The University of Arizona, 1986. http://hdl.handle.net/10150/275572.

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Burger, Christoph Hartfield Roy J. "Propeller performance analys and multidisciplinary optimization using a genetic algorithm." Auburn, Ala, 2007. http://repo.lib.auburn.edu/2007%20Fall%20Dissertations/Burger_Christoph_57.pdf.

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Selek, I. (István). "Novel evolutionary methods in engineering optimization—towards robustness and efficiency." Doctoral thesis, University of Oulu, 2009. http://urn.fi/urn:isbn:9789514291579.

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Abstract In industry there is a high demand for algorithms that can efficiently solve search problems. Evolutionary Computing (EC) belonging to a class of heuristics are proven to be well suited to solve search problems, especially optimization tasks. They arrived at that location because of their flexibility, scalability and robustness. However, despite their advantages and increasing popularity, there are numerous opened questions in this research area, many of them related to the design and tuning of the algorithms. A neutral technique called Pseudo Redundancy and related concepts such as Updated Objective Grid (UOG) is proposed to tackle the mentioned problem making an evolutionary approach more suitable for ''real world'' applications while increasing its robustness and efficiency. The proposed UOG technique achieves neutral search by objective function transformation(s) resulting several advantageous features. (a) Simplifies the design of an evolutionary solver by giving population sizing principles and directions to choose the right selection operator. (b) The technique of updated objective grid is adaptive without introducing additional parameters, therefore no parameter tuning required for UOG to adjust it for different environments, introducing robustness. (c) The algorithm of UOG is simple and computationally cheap. (d) It boosts the performance of an evolutionary algorithm on high dimensional (constrained and unconstrained) problems. The theoretical and experimental results from artificial test problems included in this thesis clearly show the potential of the proposed technique. In order to demonstrate the power of the introduced methods under "real" circumstances, the author additionally designed EAs and performed experiments on two industrial optimization tasks. Although, only one project is detailed in this thesis while the other is referred. As the main outcome of this thesis, the author provided an evolutionary method to compute (optimal) daily water pump schedules for the water distribution network of Sopron, Hungary. The algorithm is currently working in industry.
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Kassa, Hailu Belay, Shenko Chura Aredo, and Estifanos Yohannes Menta. "ENERGY EFFICIENT ADAPTIVE SECTOR-BASED USER CLUSTERING ALGORITHM FOR CELLULAR NETWORK." International Foundation for Telemetering, 2016. http://hdl.handle.net/10150/624220.

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In this paper, we propose an adaptive and multi-sector-based user clustering algorithm which increases energy efficiency in a cellular network. Adaptive sectoring with dynamically changing sector angles is illustrated with a number of randomly distributed mobile stations. Transmitted power is equally shared by sectors before adaptive user clustering. The sector angles vary from 30 to 360 degrees by merging neighboring sectors and a sector is switched off till the user density exceeds a threshold (Td). The Td value is computed from the total number of users that the cell can accommodate over the area of the cell. The sectors with less than Td density exhibits transmit power which approaches to zero or sleeping state and so that the cumulative power is saved. Simulation results show that an average of 45% to 50% energy can be saved in 10 iterations.
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Silva, Cauane Blumenberg. "Adaptive tiling algorithm based on highly correlated picture regions for the HEVC standard." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2014. http://hdl.handle.net/10183/96040.

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Esta dissertação de mestrado propõe um algoritmo adaptativo que é capaz de dinamicamente definir partições tile para quadros intra- e inter-preditos com o objetivo de reduzir o impacto na eficiência de codificação. Tiles são novas ferramentas orientadas ao paralelismo que integram o padrão de codificação de vídeos de alta eficiência (HEVC – High Efficiency Video Coding standard), as quais dividem o quadro em regiões retangulares independentes que podem ser processadas paralelamente. Para viabilizar o paralelismo, os tiles quebram as dependências de codificação através de suas bordas, gerando impactos na eficiência de codificação. Este impacto pode ser ainda maior caso os limites dos tiles dividam regiões altamente correlacionadas do quadro, porque a maior parte das ferramentas de codificação usam informações de contexto durante o processo de codificação. Assim, o algoritmo proposto agrupa as regiões do quadro que são altamente correlacionadas dentro de um mesmo tile para reduzir o impacto na eficiência de codificação que é inerente ao uso de tiles. Para localizar as regiões altamente correlacionadas do quadro de uma maneira inteligente, as características da imagem e também as informações de codificação são analisadas, gerando mapas de particionamento que servem como parâmetro de entrada para o algoritmo. Baseado nesses mapas, o algoritmo localiza as quebras naturais de contexto presentes nos quadros do vídeo e define os limites dos tiles nessas regiões. Dessa maneira, as quebras de dependência causadas pelas bordas dos tiles coincidem com as quebras de contexto naturais do quadro, minimizando as perdas na eficiência de codificação causadas pelo uso dos tiles. O algoritmo proposto é capaz de reduzir mais de 0.4% e mais de 0.5% o impacto na eficiência de codificação causado pelos tiles em quadros intra-preditos e inter-preditos, respectivamente, quando comparado com tiles uniformes.<br>This Master Thesis proposes an adaptive algorithm that is able to dynamically choose suitable tile partitions for intra- and inter-predicted frames in order to reduce the impact on coding efficiency arising from such partitioning. Tiles are novel parallelismoriented tools that integrate the High Efficiency Video Coding (HEVC) standard, which divide the frame into independent rectangular regions that can be processed in parallel. To enable the parallelism, tiles break the coding dependencies across their boundaries leading to coding efficiency impacts. These impacts can be even higher if tile boundaries split highly correlated picture regions, because most of the coding tools use context information during the encoding process. Hence, the proposed algorithm clusters the highly correlated picture regions inside the same tile to reduce the inherent coding efficiency impact of using tiles. To wisely locate the highly correlated picture regions, image characteristics and encoding information are analyzed, generating partitioning maps that serve as the algorithm input. Based on these maps, the algorithm locates the natural context break of the picture and defines the tile boundaries on these key regions. This way, the dependency breaks caused by the tile boundaries match the natural context breaks of a picture, then minimizing the coding efficiency losses caused by the use of tiles. The proposed adaptive tiling algorithm, in some cases, provides over 0.4% and over 0.5% of BD-rate savings for intra- and inter-predicted frames respectively, when compared to uniform-spaced tiles, an approach which does not consider the picture context to define the tile partitions.
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Books on the topic "Algorithm efficiency"

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United States. National Aeronautics and Space Administration., ed. Parallelization of the implicit RPLUS algorithm: Final report, NASA grant NAG 3-1472. National Aeronautics and Space Administration, 1994.

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United States. National Aeronautics and Space Administration., ed. Parallelization of the implicit RPLUS algorithm: Final report, NASA grant NAG 3-1472. National Aeronautics and Space Administration, 1997.

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Alan, Gibbons. Efficient parallel algorithms. Cambridge University Press, 1988.

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Albers, Susanne, Helmut Alt, and Stefan Näher, eds. Efficient Algorithms. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03456-5.

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Kronsjö, Lydia. Algorithms: Their complexity and efficiency. 2nd ed. Wiley, 1987.

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Evripidis, Bampis, Jansen Klaus, and Kenyon Claire, eds. Efficient approximation and online algorithms: Recent progress on classical combinatorical optimization problems and new applications. Springer, 2006.

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Evripidis, Bampis, Jansen Klaus, and Kenyon Claire, eds. Efficient approximation and online algorithms: Recent progress on classical combinatorical optimization problems and new applications. Springer, 2006.

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Jansen, Klaus, Marian Margraf, Monaldo Mastrolilli, and José D. P. Rolim, eds. Experimental and Efficient Algorithms. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-44867-5.

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Nikoletseas, Sotiris E., ed. Experimental and Efficient Algorithms. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/b136461.

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Ribeiro, Celso C., and Simone L. Martins, eds. Experimental and Efficient Algorithms. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/b97914.

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Book chapters on the topic "Algorithm efficiency"

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Sharma, Neetu, B. C. Sharma, Anil Kumar, and Rakesh Kumar. "Nutrient Uptake and Nutrient Use Efficiency." In Agronomy Algorithm. CRC Press, 2022. http://dx.doi.org/10.1201/9781003347286-6.

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Zeke, Wang, Xu Senlin, and Gao Tangan. "Efficiency of Kuhn’s Algorithm." In Algebraic Systems of Equations and Computational Complexity Theory. Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-0796-9_2.

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Wiener, Richard. "Algorithm Efficiency: Sorting and Searching." In Generic Data Structures and Algorithms in Go. Apress, 2022. http://dx.doi.org/10.1007/978-1-4842-8191-8_2.

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Bansal, Jagdish Chand, Prathu Bajpai, Anjali Rawat, and Atulya K. Nagar. "Conclusion and Further Research Directions." In Sine Cosine Algorithm for Optimization. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-9722-8_6.

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AbstractThe increasing complexity of real-world optimization problems demands fast, robust, and efficient meta-heuristic algorithms. The popularity of these intelligent techniques is gaining popularity day by day among researchers from various disciplines of science and engineering. The sine cosine algorithm is a simple population-based stochastic approach for handling different optimization problems. In this work, we have discussed the basic sine cosine algorithm for continuous optimization problems, the multi-objective sine cosine algorithm for handling multi-objective optimization problems, and the discrete (or binary) versions of sine cosine algorithm for discrete optimization problems. Sine cosine algorithm (SCA) has reportedly shown competitive results when compared to other meta-heuristic algorithms. The easy implementation and less number of parameters make the SCA algorithm, a recommended choice for performing various optimization tasks. In this present chapter, we have studied different modifications and strategies for the advancement of the sine cosine algorithm. The incorporation of concepts like opposition-based learning, quantum simulation, and hybridization with other meta-heuristic algorithms have increased the efficiency and robustness of the SCA algorithm, and meanwhile, these techniques have also increased the application spectrum of the sine cosine algorithm.
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Aye, Tin Nwe, and Linus Carlsson. "Increasing Efficiency in the EBT Algorithm." In The Springer Series on Demographic Methods and Population Analysis. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-44695-6_19.

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Rubinstein-Salzedo, Simon. "Big O Notation and Algorithm Efficiency." In Springer Undergraduate Mathematics Series. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94818-8_8.

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Goldengorin, Boris, Diptesh Ghosh, and Gerard Sierksma. "Improving the Efficiency of Branch and Bound Algorithms for the Simple Plant Location Problem." In Algorithm Engineering. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-44688-5_9.

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Beckert, Bernhard, Peter Sanders, Mattias Ulbrich, Julian Wiesler, and Sascha Witt. "Formally Verifying an Efficient Sorter." In Tools and Algorithms for the Construction and Analysis of Systems. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-57246-3_15.

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AbstractIn this experience report, we present the complete formal verification of a Java implementation of inplace superscalar sample sort ( "Image missing") using the KeY program verification system. As "Image missing" is one of the fastest general purpose sorting algorithms, this is an important step towards a collection of basic toolbox components that are both provably correct and highly efficient. At the same time, it is an important case study of how careful, highly efficient implementations of complicated algorithms can be formally verified directly. We provide an analysis of which features of the KeY system and its verification calculus are instrumental in enabling algorithm verification without any compromise on algorithm efficiency.
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Liu, Dan, Xinsong Liu, Zhijie Qiu, and Gongjun Yan. "A High Efficiency Distributed Mutual Exclusion Algorithm." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-39425-9_8.

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Mussabayev, Rustam, and Ravil Mussabayev. "Superior Parallel Big Data Clustering Through Competitive Stochastic Sample Size Optimization in Big-Means." In Intelligent Information and Database Systems. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-4985-0_18.

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AbstractThis paper introduces a novel K-means clustering algorithm, an advancement on the conventional Big-means methodology. The proposed method efficiently integrates parallel processing, stochastic sampling, and competitive optimization to create a scalable variant designed for big data applications. It addresses scalability and computation time challenges typically faced with traditional techniques. The algorithm adjusts sample sizes dynamically for each worker during execution, optimizing performance. Data from these sample sizes are continually analyzed, facilitating the identification of the most efficient configuration. By incorporating a competitive element among workers using different sample sizes, efficiency within the Big-means algorithm is further stimulated. In essence, the algorithm balances computational time and clustering quality by employing a stochastic, competitive sampling strategy in a parallel computing setting.
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Conference papers on the topic "Algorithm efficiency"

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Demidova, Liliya A., and Nikita A. Moroshkin. "An Algorithm for Optimizing the Performance of Regular Expressions Using Population Algorithms." In 2024 6th International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency (SUMMA). IEEE, 2024. https://doi.org/10.1109/summa64428.2024.10803824.

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Kessentini, Amina, Ibtissem Wali, Taheni Damak, and Nouri Masmoudi. "Efficient Algorithm for Scalable High Efficiency Video Coding Intra Prediction process." In 2024 IEEE 7th International Conference on Advanced Technologies, Signal and Image Processing (ATSIP). IEEE, 2024. http://dx.doi.org/10.1109/atsip62566.2024.10638865.

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Gul, Noman, Asad Masood Khattak, Muhammad Imran Taj, Nagarajan Chandrashekaran, Bashir Hayat, and Awais Ahmad. "Enhancing parking efficiency: An innovative vehicle scheduling algorithm." In 2024 IEEE International Conference on Information Reuse and Integration for Data Science (IRI). IEEE, 2024. http://dx.doi.org/10.1109/iri62200.2024.00027.

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pan, meiyan, wei xu, xingyu cai, wanbing hao, and jian xue. "Cooperative jamming allocation algorithm based on interference efficiency." In Sixteenth International Conference on Signal Processing Systems (ICSPS 2024), edited by Robert Minasian and Li Chai. SPIE, 2025. https://doi.org/10.1117/12.3060333.

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Huang, Jinfei, Wenbin Chen, Hao Guo, Huachao Lv, qiqi zhang, and Jian Zhou. "Application research of water efficiency test equipment for toilet flushing valve." In 4th International Conference on Automation Control. Algorithm and Intelligent Bionics, edited by Jing Na and Shuping He. SPIE, 2024. http://dx.doi.org/10.1117/12.3040310.

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Huang, Jinfei, Wenbin Chen, Hao Guo, et al. "Research on the structure of intelligent toilet water efficiency testing machine." In 4th International Conference on Automation Control. Algorithm and Intelligent Bionics, edited by Jing Na and Shuping He. SPIE, 2024. http://dx.doi.org/10.1117/12.3040318.

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Zhang, Chaoshun, and Hua Liu. "Dynamic Air Conditioning Efficiency Model Based on Genetic Algorithm and Particle Swarm Algorithm." In 2025 IEEE International Conference on Electronics, Energy Systems and Power Engineering (EESPE). IEEE, 2025. https://doi.org/10.1109/eespe63401.2025.10987569.

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Shriya, P. V., and W. Deva Priya. "An Efficient Innovative Masked Face Recognition Using FaceNet Algorithm over Visual Geometry Group (VGG-16) Algorithm for Better Efficiency." In 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2024. http://dx.doi.org/10.1109/icccnt61001.2024.10725817.

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Bai, Sixue, and Xinxi Dai. "An Efficiency apriori Algorithm: P_Matrix Algorithm." In The First International Symposium on Data, Privacy, and E-Commerce (ISDPE 2007). IEEE, 2007. http://dx.doi.org/10.1109/isdpe.2007.136.

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Yoshizumi, Toshihiro, Takaaki Goto, Yoshinao Isobe, Kazuhito Ohmaki, Hideki Mori, and Kensei Tsuchida. "Parallel algorithm that considers energy efficiency and time efficiency." In 2016 IEEE International Conference on Industrial Technology (ICIT). IEEE, 2016. http://dx.doi.org/10.1109/icit.2016.7475023.

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Reports on the topic "Algorithm efficiency"

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Goldberg, Andrew V., Michael D. Grigoriadis, and Robert E. Tarjan. Efficiency of the Network Simplex Algorithm for the Maximum Flow Problem. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada214691.

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Rabitz, Herschel. A High Efficiency Algorithm for Combinatorial Synthesis: Maximum Utilization of Minimal Libraries. Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada413449.

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Willert, Jeffrey. Increased Efficiency and Functionality Inside the Moment-Based Accelerated Thermal Radiation Transport Algorithm. Office of Scientific and Technical Information (OSTI), 2014. http://dx.doi.org/10.2172/1154961.

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Tarjan, Robert E. Efficiency of the Primal Network Simplex Algorithm for the Minimum-Cost Circulation Problem. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada215109.

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Radvand, Tina, and Alireza Talebpour. A Quantum Optimization Algorithm for Optimal Electric Vehicle Charging Station Placement for Intercity Trips. Illinois Center for Transportation, 2024. https://doi.org/10.36501/0197-9191/24-028.

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Electric vehicles (EVs) play a significant role in enhancing the sustainability of transportation systems. However, their widespread adoption is hindered by inadequate public charging infrastructure, particularly to support long-distance travel. Identifying optimal charging station locations in large transportation networks presents a well-known NP-hard combinatorial optimization problem, as the search space grows exponentially with the number of potential charging station locations. This report introduces a quantum search-based optimization algorithm designed to enhance the efficiency of solving this NP-hard problem for both corridors and transportation networks. By leveraging quantum parallelism, amplitude amplification, and quantum phase estimation as a subroutine, the optimal solution is identified with a quadratic improvement in complexity compared to classical exact methods, such as branch and bound. The detailed design and complexity of a resource-efficient quantum circuit are discussed.
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Moseman, Elizabeth. Improving the Computational Efficiency of the Blitzstein-Diaconis Algorithm for Generating Random Graphs of Prescribed Degree. National Institute of Standards and Technology, 2015. http://dx.doi.org/10.6028/nist.ir.8066.

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Li, Yan, Yuhao Luo, and Xin Lu. PHEV Energy Management Optimization Based on Multi-Island Genetic Algorithm. SAE International, 2022. http://dx.doi.org/10.4271/2022-01-0739.

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The plug-in hybrid electric vehicle (PHEV) gradually moves into the mainstream market with its excellent power and energy consumption control, and has become the research target of many researchers. The energy management strategy of plug-in hybrid vehicles is more complicated than conventional gasoline vehicles. Therefore, there are still many problems to be solved in terms of power source distribution and energy saving and emission reduction. This research proposes a new solution and realizes it through simulation optimization, which improves the energy consumption and emission problems of PHEV to a certain extent. First, on the basis that MATLAB software has completed the modeling of the key components of the vehicle, the fuzzy controller of the vehicle is established considering the principle of the joint control of the engine and the electric motor. Afterwards, based on the Isight and ADVISOR co-simulation platform, with the goal of ensuring certain dynamic performance and optimal fuel economy of the vehicle, the multi-island genetic algorithm is used to optimize the parameters of the membership function of the fuzzy control strategy to overcome it to a certain extent. The disadvantages of selecting parameters based on experience are compensated for, and the efficiency and feasibility of fuzzy control are improved. Finally, the PHEV vehicle model simulation comparison was carried out under the UDDS working condition through ADVISOR software. The optimization results show that while ensuring the required power performance, the vehicle fuzzy controller after parameter optimization using the multi-island genetic algorithm is more efficient, which can significantly reduce vehicle fuel consumption and improve exhaust emissions.
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Reddy, P. B., and T. M. Jahns. FINAL REPORT ON CONTROL ALGORITHM TO IMPROVE THE PARTIAL-LOAD EFFICIENCY OFSURFACE PM MACHINES WITH FRACTIONAL-SLOT CONCENTRATED WINDINGS. Office of Scientific and Technical Information (OSTI), 2007. http://dx.doi.org/10.2172/921785.

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Tayeb, Shahab. Intelligent Blind Crossings for Suburban and Rural Intersections. Mineta Transportation Institute, 2025. https://doi.org/10.31979/mti.2024.2351.

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Blind intersections in suburban and rural areas pose significant safety challenges due to limited visibility and inadequate infrastructure. This project proposes an innovative solution leveraging the Internet of Vehicles (IoV) paradigm, utilizing connected and autonomous vehicles (CAVs) for seamless communication to enhance safety at these intersections. The research focuses on developing a specialized Road-Side Unit (RSU) system equipped with a Virtual Traffic Light Algorithm implemented on a Field-Programmable Gate Array (FPGA). Key stakeholders, including transportation authorities, vehicle manufacturers, and local communities, stand to benefit from this initiative. The RSU system acts as a critical infrastructure component, facilitating efficient intersection management and mitigating visibility challenges. Methodologies involve adapting the Virtual Traffic Light Algorithm, integrating it into the FPGA-based RSU system, and demonstrating RSU communication operability through software-defined radios. Additionally, a novel solar-powered system is designed for lightweight RSUs to enhance sustainability and energy efficiency. The project's findings indicate the feasibility and practicality of the proposed RSU solution in enhancing safety at blind intersections. Successful implementation of the Virtual Traffic Light Algorithm on the FPGA demonstrates its potential for real-world deployment. The operability demonstration of RSU communication validates the effectiveness of the proposed communication system. Overall, this research contributes to advancing safety measures in transportation infrastructure, with potential implications for future urban planning and policy development.
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McKeever, John W., Patel Reddy, and Thomas M. Jahns. Final Report on Control Algorithm to Improve the Partial-Load Efficiency of Surface PM Machines with Fractional-Slot Concentrated Windings. Office of Scientific and Technical Information (OSTI), 2007. http://dx.doi.org/10.2172/931549.

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