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Journal articles on the topic 'Memory management (Computer science)'

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Author: Grafiati

Published: 4 June 2021

Last updated: 29 July 2024

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1

Tempel, Tobias, Claudia Niederée, Christian Jilek, Andrea Ceroni, Heiko Maus, Yannick Runge, and Christian Frings. "Temporarily Unavailable: Memory Inhibition in Cognitive and Computer Science." Interacting with Computers 31, no. 3 (May 1, 2019): 231–49. http://dx.doi.org/10.1093/iwc/iwz013.

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Abstract Inhibition is one of the core concepts in Cognitive Psychology. The idea of inhibitory mechanisms actively weakening representations in the human mind has inspired a great number of studies in various research domains. In contrast, Computer Science only recently has begun to consider concepts such as digital forgetting or suppression of irrelevant information to complement activation and highlighting of relevant information. Here, we review psychological research on inhibition in memory and link the gained insights with the current efforts and opportunities in Computer Science of incorporating inhibitory principles for reducing information overload and improving information retrieval in Personal Information Management. Four common aspects guide this review in both domains: (i) the purpose of inhibition to increase processing efficiency; (ii) its relation to activation; (iii) its links to contexts; (iv) its temporariness. In summary, the principle of suppressing information has been used by Computer Science for enhancing software in some ways already. Yet, we consider how novel methods for reducing information overload can be inspired by a more systematic involvement of the inhibition concept.

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2

Il’in, V. P. "Soviet experience in the management of applied and academic science: In memory of Academician G.I. Marchuk." Вестник Российской академии наук 93, no. 5 (May 1, 2023): 479–85. http://dx.doi.org/10.31857/s0869587323050043.

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Ten years ago, on March 24, 2013, Academician G.I. Marchuk died; his creative path includes outstanding results of basic and applied research in the field of computational mathematics and computer modeling, the creation of world-class scientific schools in atmospheric and ocean physics, nuclear reactor calculations, and mathematical immunology, as well as unique experience in managing industrial and mathematical science at the state level. The scientist’s behests, concentrated in his book The Science of Managing Science, indicate ways to reform the Russian Academy of Sciences, designed to ensure scientific and technological progress and sustainable development of society in our country.

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3

Aboubacar, Adamou Souleymane. "Kilobyte Virtual Machine Memory Management." International Review on Computers and Software (IRECOS) 15, no. 1 (June 30, 2020): 14. http://dx.doi.org/10.15866/irecos.v15i1.19314.

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4

Cheng, Jun. "Research on Data Management for China Railway Based on Computer Science." Applied Mechanics and Materials 631-632 (September 2014): 1304–7. http://dx.doi.org/10.4028/www.scientific.net/amm.631-632.1304.

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This article introduces content and utilization status of railway data management. In view of the characteristics of diversity, dispersion and mass memory, this paper puts forward an integration analysis method from three dimensions-time dimension, space dimension and category. This paper proposes a framework of data management of high-speed railway equipment, where cloud computing provides a feasible technical solution combined with MapReduce programming model based on Hadoop platform. These models are capable of considering the characteristics of data and processing demand in management of High-speed railway equipment. Finally, we summarize the challenges and opportunities with Big Data for application of China railway and point out there is more than enough that we can work on.

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5

Tofte, Mads, and Jean-Pierre Talpin. "Region-Based Memory Management." Information and Computation 132, no. 2 (February 1997): 109–76. http://dx.doi.org/10.1006/inco.1996.2613.

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6

JOHNSON, THEODORE, and TIMOTHY A. DAVIS. "PARALLEL BUDDY MEMORY MANAGEMENT." Parallel Processing Letters 02, no. 04 (December 1992): 391–98. http://dx.doi.org/10.1142/s0129626492000544.

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Shared memory multiprocessor systems need efficient dynamic storage allocators, both for system purposes and to support parallel programs. Memory managers are often based on the buddy system, which provides fast allocation and release. Previous parallel buddy memory managers made no attempt to coordinate the allocation, splitting and release of blocks, and as a result needlessly fragment memory. We present a fast and simple parallel buddy memory manager that is also as space efficient as a serial buddy memory manager. We test our algorithms using memory allocation/deallocation traces collected from a parallel sparse matrix algorithm.

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7

Arge, Lars, and Jeffrey Scott Vitter. "Optimal External Memory Interval Management." SIAM Journal on Computing 32, no. 6 (January 2003): 1488–508. http://dx.doi.org/10.1137/s009753970240481x.

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8

Kesselman, Alexander, and Yishay Mansour. "Harmonic buffer management policy for shared memory switches." Theoretical Computer Science 324, no. 2-3 (September 2004): 161–82. http://dx.doi.org/10.1016/j.tcs.2004.05.014.

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9

Salagnac, G., S. Yovine, and D. Garbervetsky. "Fast Escape Analysis for Region-based Memory Management." Electronic Notes in Theoretical Computer Science 131 (May 2005): 99–110. http://dx.doi.org/10.1016/j.entcs.2005.01.026.

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10

Turkan, Y. "An Efficient Memory Management Algorithm for Client-Server Database Management Systems." Computer Journal 39, no. 5 (May 1, 1996): 374–85. http://dx.doi.org/10.1093/comjnl/39.5.374.

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11

Souza, Renan, Vitor Silva, Alexandre A. B. Lima, Daniel de Oliveira, Patrick Valduriez, and Marta Mattoso. "Distributed in-memory data management for workflow executions." PeerJ Computer Science 7 (May 7, 2021): e527. http://dx.doi.org/10.7717/peerj-cs.527.

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Complex scientific experiments from various domains are typically modeled as workflows and executed on large-scale machines using a Parallel Workflow Management System (WMS). Since such executions usually last for hours or days, some WMSs provide user steering support, i.e., they allow users to run data analyses and, depending on the results, adapt the workflows at runtime. A challenge in the parallel execution control design is to manage workflow data for efficient executions while enabling user steering support. Data access for high scalability is typically transaction-oriented, while for data analysis, it is online analytical-oriented so that managing such hybrid workloads makes the challenge even harder. In this work, we present SchalaDB, an architecture with a set of design principles and techniques based on distributed in-memory data management for efficient workflow execution control and user steering. We propose a distributed data design for scalable workflow task scheduling and high availability driven by a parallel and distributed in-memory DBMS. To evaluate our proposal, we develop d-Chiron, a WMS designed according to SchalaDB’s principles. We carry out an extensive experimental evaluation on an HPC cluster with up to 960 computing cores. Among other analyses, we show that even when running data analyses for user steering, SchalaDB’s overhead is negligible for workloads composed of hundreds of concurrent tasks on shared data. Our results encourage workflow engine developers to follow a parallel and distributed data-oriented approach not only for scheduling and monitoring but also for user steering.

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12

Gaud, Fabien, Baptiste Lepers, Justin Funston, Mohammad Dashti, Alexandra Fedorova, Vivien Quéma, Renaud Lachaize, and Mark Roth. "Challenges of memory management on modern NUMA systems." Communications of the ACM 58, no. 12 (November 23, 2015): 59–66. http://dx.doi.org/10.1145/2814328.

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13

Cui, YanLiang, and Dechang Pi. "SQLmmdb: An Embedded Main Memory Database Management Systemcc." Information Technology Journal 6, no. 6 (August 1, 2007): 872–78. http://dx.doi.org/10.3923/itj.2007.872.878.

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14

Gaud, Fabien, Baptiste Lepers, Justin Funston, Mohammad Dashti, Alexandra Fedorova, Vivien Quéma, Renaud Lachaize, and Mark Roth. "Challenges of Memory Management on Modern NUMA System." Queue 13, no. 8 (September 2015): 70–85. http://dx.doi.org/10.1145/2838344.2852078.

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15

Furht and Milutinovic. "A Survey of Microprocessor Architectures for Memory Management." Computer 20, no. 3 (March 1987): 48–67. http://dx.doi.org/10.1109/mc.1987.1663508.

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16

Sha, Sai, Jing-Yuan Hu, Ying-Wei Luo, Xiao-Lin Wang, and Zhenlin Wang. "Huge Page Friendly Virtualized Memory Management." Journal of Computer Science and Technology 35, no. 2 (March 2020): 433–52. http://dx.doi.org/10.1007/s11390-020-9693-0.

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17

Lee, Soyoon, and Hyokyung Bahn. "Characterization of Android Memory References and Implication to Hybrid Memory Management." IEEE Access 9 (2021): 60997–1009. http://dx.doi.org/10.1109/access.2021.3074179.

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18

Higuera-Toledano, M. Teresa, and Val�rie Issarny. "Improving the memory management performance of RTSJ." Concurrency and Computation: Practice and Experience 17, no. 5-6 (2005): 715–37. http://dx.doi.org/10.1002/cpe.845.

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19

Anagnostopoulos, Iraklis, Sotirios Xydis, Alexandros Bartzas, Zhonghai Lu, Dimitrios Soudris, and Axel Jantsch. "Custom Microcoded Dynamic Memory Management for Distributed On-Chip Memory Organizations." IEEE Embedded Systems Letters 3, no. 2 (June 2011): 66–69. http://dx.doi.org/10.1109/les.2011.2146228.

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20

BYUN, SIWOO, MOONHAENG HUH, and HOYOUNG HWANG. "FLASH MEMORY LOCK MANAGEMENT FOR PORTABLE INFORMATION SYSTEMS." International Journal of Cooperative Information Systems 15, no. 03 (September 2006): 461–79. http://dx.doi.org/10.1142/s0218843006001438.

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Flash memory is becoming a major database storage in building embedded systems or portable devices because of its non-volatile, shock-resistant, power-economic nature, and fast access time for read operations. Flash memory, however, should be erased before it can be rewritten and the erase and write operations are very slow as compared to main memory. Due to this drawback, traditional database management schemes are not easy to apply directly to flash memory database for portable devices. Therefore, we improve the traditional schemes and propose a new scheme called Flash Two Phase Locking (F2PL) scheme for efficient transaction processing in a flash memory database environment. F2PL achieves high transaction performance by exploiting the notion of the Alternative Version Coordination which allows previous version reads and efficiently handles slow write/erase operations in lock management processes. We also propose a simulation model to show the performance of F2PL. Based on the results of the performance evaluation, we conclude that F2PL scheme outperforms the traditional schemes.

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21

Denning, Peter J. "Working Set Analytics." ACM Computing Surveys 53, no. 6 (February 2021): 1–36. http://dx.doi.org/10.1145/3399709.

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The working set model for program behavior was invented in 1965. It has stood the test of time in virtual memory management for over 50 years. It is considered the ideal for managing memory in operating systems and caches. Its superior performance was based on the principle of locality, which was discovered at the same time; locality is the observed tendency of programs to use distinct subsets of their pages over extended periods of time. This tutorial traces the development of working set theory from its origins to the present day. We will discuss the principle of locality and its experimental verification. We will show why working set memory management resists thrashing and generates near-optimal system throughput. We will present the powerful, linear-time algorithms for computing working set statistics and applying them to the design of memory systems. We will debunk several myths about locality and the performance of memory systems. We will conclude with a discussion of the application of the working set model in parallel systems, modern shared CPU caches, network edge caches, and inventory and logistics management.

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22

CHAUDHRY, G. M., and J. S. BEDI. "Multi-dimensional state-space model for memory management." International Journal of Systems Science 20, no. 1 (January 1989): 121–28. http://dx.doi.org/10.1080/00207728908910109.

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23

Chen, Kaimeng, Peiquan Jin, and Lihua Yue. "A Survey on Phase Change Memory-Aware Cache Management." International Journal of Multimedia and Ubiquitous Engineering 11, no. 1 (January 31, 2016): 293–310. http://dx.doi.org/10.14257/ijmue.2016.11.1.28.

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24

Johnson, Theodore. "Parallel-access memory management using fast-fits." International Journal of Parallel Programming 22, no. 6 (December 1994): 617–44. http://dx.doi.org/10.1007/bf02577871.

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25

Snyder, Charles A., Denise Johnson McManus, and Larry Todd Wilson. "Corporate memory management: a knowledge management process model." International Journal of Technology Management 20, no. 5/6/7/8 (2000): 752. http://dx.doi.org/10.1504/ijtm.2000.002894.

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26

Levary, Reuven R., and William D. Edwards. "Planning computer memory allocation: A simulation case study." Computers & Operations Research 12, no. 1 (January 1985): 107–15. http://dx.doi.org/10.1016/0305-0548(85)90012-7.

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27

Purnomo, Rakhmat, and Tri Dharma Putra. "Theoretical Analysis of Standard Selection Sort Algorithm." SinkrOn 8, no. 2 (April 4, 2023): 666–73. http://dx.doi.org/10.33395/sinkron.v8i2.12153.

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Sorting algorithms plays an important role in the computer science field. Many applications use sorting algorithm. There are several sorting algorithms proposed by experts, namely bubble sort, exchange short, insertion short, heap sort, quick short, merge sort, standard selection sort. One well-known algorithm of sorting is selection sort. In this journal, discussion about standard selection sort is given with thorough analysis. Sorting is very important data structure concepts that has an important role in memory management, file management, in computer science in general, and in many real-life applications. Different sorting algorithms have differences in terms of time complexity, memory use, efficiency, and other factors. There are many sorting algorithms exist right now in the computer science field. Each algorithm has its benefits and limitations where a trade-off exists between execution time and the nature of the complexity of the algorithm itself. The method is theoretical analysis. Three theoretical analyses are given with deep explanation and analysis. Each with six index arrays, namely with six data on it. The numbers are sorted in ascending order. Pseudo code is also given, to understand this algorithm more thoroughly. It is concluded that this theoretical analysis explained the algorithm more clearly, by using process iteration by hand.

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28

Vuckovic, Vladan, and Djordje Vidanovic. "An algorithm for the detection of move repetition without the use of hash-keys." Yugoslav Journal of Operations Research 17, no. 2 (2007): 257–74. http://dx.doi.org/10.2298/yjor0702257v.

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This paper addresses the theoretical and practical aspects of an important problem in computer chess programming - the problem of draw detection in cases of position repetition. The standard approach used in the majority of computer chess programs is hash-oriented. This method is sufficient in most cases, as the Zobrist keys are already present due to the systemic positional hashing, so that they need not be computed anew for the purpose of draw detection. The new type of the algorithm that we have developed solves the problem of draw detection in cases when Zobrist keys are not used in the program, i.e. in cases when the memory is not hashed.

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29

Korpała, Grzegorz. "Data management in CUDA Programming for High Bandwidth Memory in GPU Accelerators." Computer Methods in Material Science 16, no. 3 (2016): 121–26. http://dx.doi.org/10.7494/cmms.2016.3.0580.

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The number of applications that use GPU accelerated calculations always grows. The software conversion to such calculation type is although complex but gives enormous energy efficiency and performance. In the publication is presented a method of the data sets, in which a temporary storage is occurred in the shared memory of GPU. The loading of values to shared memory via massive data access makes it possible to exploit the full power of the High Bandwidth Memory. It is demonstrated by CUDA codes for Cellular Automaton application and corresponding indexing of the data in global and shared memory. The real and the theoretical Speed-Up are described and shown in this publication.

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30

Denning, Peter, and Roland Ibbett. "The Atlas milestone." Communications of the ACM 65, no. 9 (September 2022): 26–29. http://dx.doi.org/10.1145/3548781.

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31

Beckingsale, D. A., M. J. McFadden, J. P. S. Dahm, R. Pankajakshan, and R. D. Hornung. "Umpire: Application-focused management and coordination of complex hierarchical memory." IBM Journal of Research and Development 64, no. 3/4 (May 1, 2020): 00:1–00:10. http://dx.doi.org/10.1147/jrd.2019.2954403.

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32

Edneral, Victor F. "In Memory of Vladimir Gerdt." Discrete and Continuous Models and Applied Computational Science 29, no. 4 (December 15, 2021): 306–36. http://dx.doi.org/10.22363/2658-4670-2021-29-4-306-336.

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Center for Computational Methods in Applied Mathematics of RUDN, Professor V.P. Gerdt, whose passing was a great loss to the scientific center and the computer algebra community. The article provides biographical information about V.P. Gerdt, talks about his contribution to the development of computer algebra in Russia and the world. At the end there are the authors personal memories of V.P. Gerdt.

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33

Kamel, Ibrahim, and Beizhong Chen. "A novel memory management scheme for residential gateways." Information Systems Frontiers 11, no. 5 (June 26, 2008): 491–500. http://dx.doi.org/10.1007/s10796-008-9123-2.

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34

Lin, Yi-Bing. "Memory management algorithms for optimistic parallel simulation." Information Sciences 77, no. 1-2 (March 1994): 119–40. http://dx.doi.org/10.1016/0020-0255(94)90051-5.

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35

Chen, Xiao-Bing, Hao Qi, Shao-Hui Peng, Yi-Min Zhuang, Tian Zhi, and Yun-Ji Chen. "Tetris: A Heuristic Static Memory Management Framework for Uniform Memory Multicore Neural Network Accelerators." Journal of Computer Science and Technology 37, no. 6 (November 30, 2022): 1255–70. http://dx.doi.org/10.1007/s11390-021-1213-3.

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36

Kee, Yang-Suk, Jin-Soo Kim, and Soonhoi Ha. "Memory management for multi-threaded software DSM systems." Parallel Computing 30, no. 1 (January 2004): 121–38. http://dx.doi.org/10.1016/j.parco.2003.09.001.

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37

Liang, Jingjing, and Pianpian Ma. "Design of computer aided translation system for English communication language based on grey clustering evaluation." Journal of Computational Methods in Sciences and Engineering 21, no. 6 (December 7, 2021): 2023–33. http://dx.doi.org/10.3233/jcm-215564.

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In order to facilitate communication and communication, this paper studies the optimization of the current computer-aided translation system, and proposed a design method of English communication language computer-aided translation system based on grey clustering evaluation. By optimizing the hardware configuration and algorithm function keys of the system, the English translation mechanism of multilanguage interaction, the design idea of editing and modifying after English translation and knowledge database management are realized, and the system function framework was constructed, including the system transceiver unit, automatic translation unit, manual correction unit, task management unit and memory management unit, the performance of task management unit and memory management unit is analyzed. On this basis, the specific work flow of the design system mainly includes the English translation service flow integrating multilanguage interaction and the project-based multilanguage interaction English translation service flow design, which realizes the English translation online assistance under the multilanguage interaction environment. The experimental results show that the design system has the advantages of high online translation speed, pronunciation success rate and multilanguage translation success rate.

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38

Alahmadi, Yasser Ali, Mokhtar Alsorori, and Saleh Noman Alassali. "Reduce the Memory Used in Key Management for Security Systems." International Journal of Computer Networks and Applications 8, no. 4 (August 31, 2021): 412. http://dx.doi.org/10.22247/ijcna/2021/209707.

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39

Renton, Alastair, and Ann Macintosh. "Computer-Supported Argument Maps as a Policy Memory." Information Society 23, no. 2 (March 23, 2007): 125–33. http://dx.doi.org/10.1080/01972240701209300.

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40

Dolev, Shlomi, and Reuven Yagel. "Memory Management for Self-Stabilizing Operating Systems." Journal of Aerospace Computing, Information, and Communication 3, no. 6 (June 2006): 260–80. http://dx.doi.org/10.2514/1.19946.

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41

Courts, Robert. "Improving locality of reference in a garbage-collecting memory management system." Communications of the ACM 31, no. 9 (September 1988): 1128–38. http://dx.doi.org/10.1145/48529.48536.

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42

Tskhakaya, D., and R. Schneider. "Optimization of PIC codes by improved memory management." Journal of Computational Physics 225, no. 1 (July 2007): 829–39. http://dx.doi.org/10.1016/j.jcp.2007.01.002.

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43

Sonobe, Tomohiro. "An Efficient Monte Carlo Approach to Compute PageRank for Large Graphs on a Single PC." Foundations of Computing and Decision Sciences 41, no. 1 (March 1, 2016): 29–43. http://dx.doi.org/10.1515/fcds-2016-0002.

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AbstractThis paper describes a novel Monte Carlo based random walk to compute PageRanks of nodes in a large graph on a single PC. The target graphs of this paper are ones whose size is larger than the physical memory. In such an environment, memory management is a difficult task for simulating the random walk among the nodes. We propose a novel method that partitions the graph into subgraphs in order to make them fit into the physical memory, and conducts the random walk for each subgraph. By evaluating the walks lazily, we can conduct the walks only in a subgraph and approximate the random walk by rotating the subgraphs. In computational experiments, the proposed method exhibits good performance for existing large graphs with several passes of the graph data.

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44

Grachev, Vladimir I. "In Memory of Alexander Sergeevich Ilyushin." Radioelectronics. Nanosystems. Information Technologies. 13, no. 2 (June 12, 2021): 221–24. http://dx.doi.org/10.17725/rensit.2021.13.221.

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Provides information about the deceased Alexander Sergeevich Ilyushin - Doctor of Physical and Mathematical Sciences, professor, Head of the Chair of Solid State Physics, Faculty of Physics, Lomonosov Moscow State University, Honored Professor of Lomonosov MSU, a full member of the Russian Academy of Natural Sciences, a well-known specialist in the field of structural solid state physics: basic biographical data, training at the Physics Faculty of Lomonosov MSU, postgraduate studies and work at the Solid State Physics Chair of Moscow State University, defense of candidate and doctoral dissertations, authorship of hundreds of scientific works, dozens of monographs and textbooks, pedagogical activity, leadership of the Solid State Physics Chair of MSU, membership in the academic councils of the Physics Faculty, participation and organization of Russian and international conferences, editorial scientific journals, creation and management of the Museum of History of the Physics Faculty of MSU, membership in the Russian Academy of Natural Sciences, management of its Division, creation and management of the Union of Philatelists of Russia, participation and organization of Russian and international philatelic exhibitions and conferences.

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45

Igaeva, Ksenia V. "THREE TYPES OF NOSTALGIA IN COMPUTER GAMES." Sovremennye issledovaniya sotsialnykh problem 15, no. 2 (June 30, 2023): 64–75. http://dx.doi.org/10.12731/2077-1770-2023-15-2-64-75.

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The article is devoted to the problems of representation of nostalgia in computer games and offers a distinction between its three interrelated forms: retrotopic, aestheticizing, nostalgia for childhood and lost parental home. These forms are featured in the series of games «Fallout», «Second Life», and «World of Warships». The relevance of the study is associated with a wide controversy about nostalgia in the framework of modern memory studies. Further, it is proved that the communicative nature of media memory subordinates the cultural component (in its interpretation by J. Assman). Nostalgia in computer games differs significantly from nostalgia in cinema, which also actively uses repetition and emotional identification – it is less reflective and more oriented to affect. On the other hand, the temporal dimension of nostalgia in computer games seems to be more complex, not leading to presentism, but expanding the contingency or complex interweaving of past, present and future.

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46

Lee, Kwangjin, Hwajung Kim, and Heon Y. Yeom. "Validity Tracking Based Log Management for In-Memory Databases." IEEE Access 9 (2021): 111493–504. http://dx.doi.org/10.1109/access.2021.3103862.

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47

Turgay, Safiye. "Blockchain Management and Federated Learning Adaptation on Healthcare Management System." International Journal of Intelligent Systems and Applications 14, no. 5 (October 8, 2022): 1–13. http://dx.doi.org/10.5815/ijisa.2022.05.01.

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Recently, health management systems have some troubles such as insufficient sharing of medical data, security problems of shared information, tampering and leaking of private data with data modeling probes and developing technology. Local learning is performed together with federated learning and differential entropy method to prevent the leakage of medical confidential information, so blockchain-based learning is preferred to completely eliminate the possibility of leakage while in global learning. Qualitative and quantitative analysis of information can be made with information entropy technology for the effective and maximum use of medical data in the local learning process. The blockchain is used the distributed network structure and inherent security features, at the same time information is treated as a whole, not as islands of data. All the way through this work, data sharing between medical systems can be encouraged, access records tampered with, and better support medical research and definitive medical treatment. The M/M/1 queue for the memory pool and M/M/C queue to combine integrated blockchains with a unified learning structure. With the proposed model, the number of transactions per block, mining of each block, learning time, index operations per second, number of memory pools, waiting time in the memory pool, number of unconfirmed transactions in the whole system, total number of transactions were examined. Thanks to this study, the protection of the medical privacy information of the user during the service process and the autonomous management of the patient’s own medical data will benefit the protection of privacy within the scope of medical data sharing. Motivated by this, proposed a blockchain and federated learning-based data management system able to develop in next studies.

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48

Gu, Ning, Zongkai Lin, and Yuchai Guo. "On model, memory management and interface in EDBMS/3." Journal of Computer Science and Technology 13, no. 4 (July 1998): 337–47. http://dx.doi.org/10.1007/bf02946623.

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49

Lei, Tengfei, Rita Yi Man Li, Nuttapong Jotikastira, Haiyan Fu, and Cong Wang. "Prediction for the Inventory Management Chaotic Complexity System Based on the Deep Neural Network Algorithm." Complexity 2023 (May 12, 2023): 1–11. http://dx.doi.org/10.1155/2023/9369888.

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Precise inventory prediction is the key to goods inventory and safety management. Accurate inventory prediction improves enterprises’ production efficiency. It is also essential to control costs and optimize the supply chain’s performance. Nevertheless, the complex inventory data are often chaotic and nonlinear; high data complexity raises the accuracy prediction difficulty. This study simulated inventory records by using the dynamics inventory management system. Four deep neural network models trained the data: short-term memory neural network (LSTM), convolutional neural network-long short-term memory (CNN-LSTM), bidirectional long short-term memory neural network (Bi-LSTM), and deep long-short-term memory neural network (DLSTM). Evaluating the models’ performance based on RMSE, MSE, and MAE, bi-LSTM achieved the highest prediction accuracy with the least square error of 0.14%. The results concluded that the complexity of the model was not directly related to the prediction performance. By contrasting several methods of chaotic nonlinear inventory data and neural network dynamics prediction, this study contributed to the academia. The research results provided useful advice for companies’ planned production and inventory officers when they plan for product inventory and minimize the risk of mishaps brought on by excess inventories in warehouses.

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Hsieh, Jen-Wei, Yi-Lin Tsai, Tei-Wei Kuo, and Tzao-Lin Lee. "Configurable Flash-Memory Management: Performance versus Overheads." IEEE Transactions on Computers 57, no. 11 (November 2008): 1571–83. http://dx.doi.org/10.1109/tc.2008.61.

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