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  3. 大规模非对称不定带宽线性代数方程组求解算法赛
OpenAtomGeneral MLAdvancedRegistration unverified

大规模非对称不定带宽线性代数方程组求解算法赛

A advanced general ml competition requiring roughly 25–70 hours for an end-to-end practice run.

Difficulty
Advanced
Estimated effort
25–70 hours
Registration deadline
To be confirmed
Compute
CPU only
OverviewPreparationSource

Overview

Who this competition fits

Advanced practitioners with experience in general machine learning. Requires strong technical foundations and comfort with complex ML pipelines.

Read the original official blurb
本赛题致力于实现适用于船舶流体CFD软件的先进迭代算法。船舶水动力学CFD计算中,流场精细结构捕捉对船舶阻力、噪声及线型优化等都十分重要,大规模稀疏矩阵方程的稳定、高效、快速求解是对流场精细结构捕捉的有力支撑。船舶水动力学CFD软件主要采用任意多面体非结构网格,这使得基于有限体积法离散后的线性方程组系数矩阵具有不定带宽的特性,同时由于非线性对流的影响,使得上述系数矩阵具有非对称的性质。 Official category: 实战竞技赛. Organizers: 中国船舶科学研究中心. Participants: 199.

Preparation

From registration to a first submission

  1. 01

    Python

  2. 02

    scikit-learn or similar ML library

  3. 03

    data analysis with pandas

Before you commit: Requires solid machine learning fundamentals and good experimental methodology. The competitive landscape is strong, with many experienced teams.

Source

How this page was assembled

Competition information is structured from the official page. Scores are platform estimates for decision support; official rules take precedence.

Official competition page
OpenAtom
Last checked
Sep 5, 2023

Entry assessment

est.
20

Prepare before joining

Overall fit estimate

Beginner fit20/100
Learning value66/100

Confirm eligibility and time commitment before moving into formal preparation.

Entry eligibility needs official confirmation

Open official pageSign in to saveOpen guide

Data and review state

Separate what is confirmed from what still needs review. Official rules and deadlines win.

View data stateClose
Source page verifiedMetric confirmedReviewed
Source published
Sep 5, 2023
Source created
Sep 5, 2023
Published on this site
Aug 1, 2026

Official metric is not published on the OpenAtom competition listing; verify scoring on the competition page.

reward_value_usd is a rough CNY→USD estimate (×0.14) for ranking only; use reward_summary for the official prize text.