Abstract
In a heterogeneous computing environment, task scheduling has always been a central issue in high-performance computing. This paper proposes a scheduling algorithm based on priority queue division. The algorithm determines the number of priority queues according to the number of input nodes of the directed DAG task set of the acyclic graph and divides the task queue into communication overhead and computational overhead. With the development of the marine economy, the pressure on the marine ecological environment is increasing, and the complexity of protection and governance is also increasing. Therefore, on the basis of heterogeneous computer technology, this paper has carried out a systematic study on the characteristics of marine organisms and has carried out a systematic study on the characteristics of marine ecology. This article finds out the many reasons for the destruction of the marine environment and proposes appropriate countermeasures to establish a complete marine protection and management system. In view of the increasing importance of international and national criminal responsibility of maritime transport rights, the establishment of environmental legal issues has become very important, which is essential for combating and punishing crimes related to marine pollution and maintaining the marine environment. This paper studies domestic and foreign taxation policies and the legal system of coordinated management in the ecological environment and mainly studies how to build a legal system of fiscal and taxation policies for the coordinated governance of the ecological environment and optimize the fiscal and taxation policies of the ecological environment. Based on the research and analysis of taxation policy optimization environment, taxation law, taxation policy, and joint management law, this article puts forward practical suggestions.
Similar content being viewed by others
Change history
30 November 2021
This article has been retracted. Please see the Retraction Notice for more detail: https://doi.org/10.1007/s12517-021-09137-1
28 September 2021
An Editorial Expression of Concern to this paper has been published: https://doi.org/10.1007/s12517-021-08471-8
References
Ahmadi MA, Ahmadi MR, Hosseini SM, Ebadi M (2014) Connectionist model predicts the porosity and permeability of petroleum reservoirs by means of petro-physical logs: application of artificial intelligence. J Pet Sci Eng 123:183–200
Baxendell PB, Thomas R (1961) The calculation of pressure gradients in high-rate flowing wells. J Pet Technol 13(10):1–023
Coello CAC, Lamont GB, Van Veldhuizen DA (2007) Evolutionary algorithms for solving multi-objective problems, vol 5. Springer, New York, pp 79–104
Duns Jr H, Ros NCJ (1963) Vertical flow of gas and liquid mixtures in wells. In 6th world petroleum congress. World Petroleum Congress
Fancher Jr GH, Brown KE (1962) Prediction of pressure gradients for multiphase flow in tubing. In Fall Meeting of the Society of Petroleum Engineers of AIME. Society of Petroleum Engineers
Fayazi A, Arabloo M, Shokrollahi A, Zargari MH, Ghazanfari MH (2014) State-of-the-art least square support vector machine application for accurate determination of natural gas viscosity. Ind Eng Chem Res 53(2):945–958
Gharbi RB, Mansoori GA (2005) An introduction to artificial intelligence applications in petroleum exploration and production. J Pet Sci Eng 49(3-4):93–96
Hagedorn AR, Brown KE (1965) Experimental study of pressure gradients occurring during continuous two-phase flow in small-diameter vertical conduits. J Pet Technol 17(04):475–484
Hasan AR, Kabir CS (1992) Two-phase flow in vertical and inclined annuli. Int J Multiphase Flow 18(2):279–293
Jahanandish I, Salimifard B, Jalalifar H (2011) Predicting bottom-hole pressure in vertical multiphase flowing wells using artificial neural networks. J Pet Sci Eng 75(3-4):336–342
Khamehchi E, Zolfagharroshan M, Mahdiani MR (2020) A robust method for estimating the two-phase flow rate of oil and gas using wellhead data, Springer
Koza JR (1990) Genetic programming: a paradigm for genetically breeding populations of computer programs to solve problems, vol 34. Stanford University, Department of Computer Science, Stanford
Koza JR, Keane MA, Streeter MJ, Mydlowec W, Yu J, Lanza G (2006) Genetic programming IV: routine human-competitive machine intelligence (vol. 5). Springer Science & Business Media, Berlin
Malallah A, Nashawi IS (2005) Estimating the fracture gradient coefficient using neural networks for a field in the Middle East. J Pet Sci Eng 49(3-4):193–211
Mukherjee H, Brill JP (1985) Empirical equations to predict flow patterns in two-phase inclined flow. Int J Multiphase Flow 11(3):299–315
Naderi M, Khamehchi E (2018) Application of optimized least square support vector machine and genetic programming for accurate estimation of drilling rate of penetration. Int J Energy Optim Eng (IJEOE) 7(4):92–108
Payne GA, Palmer CM, Brill JP, Beggs HD (1979) Evaluation of inclined-pipe, two-phase liquid holdup and pressure-loss correlation using experimental data (includes associated paper 8782). J Pet Technol 31(09):1–198
Petalas N, Aziz K (2000) A mechanistic model for multiphase flow in pipes. J Can Pet Technol 39. https://doi.org/10.2118/00-06-04
Poettman FH, Carpenter PG (1952) The multiphase flow of gas, oil, and water through vertical flow strings with application to the design of gas-lift installations. In Drilling and production practice. American Petroleum Institute
Searson DP, Leahy DE, Willis MJ (2010) GPTIPS: an open source genetic programming toolbox for multigene symbolic regression. In Proceedings of the International multiconference of engineers and computer scientists (Vol. 1, pp. 77-80)
Shoham O (2006) Mechanistic modeling of gas-liquid two-phase flow in pipes. Richardson, TX: Society of Petroleum Engineers
Watson A (2016) Geothermal engineering. Springer-Verlag New York
Yuan X, Chen C, Yuan Y, Huang Y, Tan Q (2015) Short-term wind power prediction based on LSSVM–GSA model. Energy Convers Manag 101:393–401
Acknowledgements
The study was supported by “Research on the conflicts of interest and legal adjustments in the construction of modern environmental governance system (Grant No. 20BFX166).”
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no competing interests.
Additional information
Responsible Editor: Sheldon Williamson
This article is part of the Topical Collection on Environment and Low Carbon Transportation
This article has been retracted. Please see the retraction notice for more detail: https://doi.org/10.1007/s12517-021-09137-1
About this article
Cite this article
Jiang, M. RETRACTED ARTICLE: Marine biological characteristics and environmental legal policy optimization based on heterogeneous computing environment. Arab J Geosci 14, 1534 (2021). https://doi.org/10.1007/s12517-021-07949-9
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s12517-021-07949-9