两种不同场景下,如何预测合并 TTD 值?

ETH中文网Published on 2022-08-12Last updated on 2022-08-12

Abstract

为了设定合并的终结总难度值,我们可以先预测给定日期的 TTD 值,然后根据算力的变动进行调整。

为了设定合并的终结总难度值,我们可以先预测给定日期的 TTD 值,然后根据算力的变动进行调整。

合并 TTD 值

目标:确定 TTD 值,它会在 Bellatrix 主网升级之后以及九月底之前触达。如果算力大幅下降,那我们可以在 Bellatrix 升级之后,我们可以调用指令以覆盖 TTD。

预测 TTD 值的策略

为了设定合并的终结总难度值,我们可以先预测给定日期的 TTD 值,然后根据算力的变动进行调整。

为了确定 TTD 值触达的时间,可用多项式回归的方法创建一个具有合理精确度的估值。这些估值会基于前四周的数据并使用预测工具生成。但是,预测的精确度完全取决于未来算力的波动。如果算力大幅变动并且比预期的日期提前了足够长的时间,那么 TTD 的日期可能会推迟几天。

让我们来研究一下以太坊网络的算力以建立预期。

算力趋势

在过去的几个月里,算力平均值在 1PH/s 左右,并在 5 月达到峰值 1.126 PH/s。在 6 月急剧下降之后,算力逐渐恢复,并且现在保持在 900TH/s 左右(平均值、有效的算力)。上个月,算力在 950TH/s 和 780TH/s (峰值)之间振荡,其每日变化不大于 5%。

算力会基于挖矿收益率发生浮动,而挖矿的收益率与 ETH 价格相关。尽管算力变化不完全依赖于价格的波动,但是它确实会对此作出反应。以下是 1 月以来的 ETH 价格和算力投射到一个图表中:

因为算力表明了在一段时间内必须克服的挖矿难度,我们可以确定在特定时间,网络中达到 TTD 值所需的具体算力值。这个脚本计算并显示出在一段时间内 —— 9 月期间 —— 达到给定 TTD 值所需的算力值。

在下列可视化图表中,你可以从更大的时间框架上看清楚算力的趋势。它显示,在一段时间内(y 轴)达成示例的 TTD 值所需的算力值(x 轴)。曲线的红色部分代表 9 月,也就是合并可能发生的时间。

这个形状实际上显示出,9 月的前半段需要明显更大的算力。这为算力在前期的增长提供了更多「保护」,但随后必要的算力下降得更慢。如果算力大幅下跌,那么必要算力的缓慢降幅会让 TTD 更难达到。

由于 DAG 大小达到 5 GB 以及矿工可能会采取的消极应对,我们必须留出足够的空间来应对算力的下降。为此,下面预估的默认预测值会向下舍入。

场景 1 估值

场景 1,Bellatrix 主网升级将在 8 月 31 日发生。

预测将会在 UTC 时间的 9 月 15 日中午触达 TTD 值,介于 5877487756139069440 和 58834281007084994560000 之间。

为了取出更好且稍低的数字,我们可以将这个向下舍入为 58750000000000000000000。这个数字只需相差 10 个小时就可以达到。以下是在 9 月达到这个 TTD 值所需算力的可视化图表。

你可以看见达到这个 TTD 值的必需算力从 9 月 1 日的 1400TH/s 左右减少到 9 月底的 623TH/s 左右(比当前的算力下降了 29%)。红色虚线代表了当前的算力平均值,并在 9 月 15 日与蓝色曲线相交,这是 TTD 值的预估日期。

下一个图表绘制了与当前算力 ( 在 0 处用红色虚线标记 ) 相比的必要算力百分比变化。

这里的图表总结了这些估值并把它与 ATH(历史最高)算力和当前算力进行对比。

如果我们预估最大限度的算力跌幅为 30%,那么 TTD 值会在 9 月底达到。如果我们想为更大的跌幅做准备,就必须把 TTD 值设得更低。

以下图表列出了其他要考虑的 TTD,它们什么时候会触达、在 Bellatrix 升级中需要多少算力才能达到以及从当前算力来看,我们可以预计下降多少百分比。

场景 2 估值

在场景 2,Bellatrix 主网升级会在 9 月 6 日进行。

预测会在 UTC 时间的 9 月 20 日中午触达 TTD 值,介于 5915542925294436352 和 59227132692074332160000 之间。

将它向下舍入至 59100000000000000000000 ,大约会相差 16 小时。下一个图表绘制了要在 9 月 6 日至 7 日期间达到 TTD 值所需的算力。

达到这个 TTD 值的必要算力会从 9 月 6 日 Bellatrix 升级的 1290TH/s 下降至 9 月 30 日的 700TH/s (比当前算力下降了 20%)。红色虚线代表着当前算力的平均值,并在 9 月 19 日至 20 日与蓝色曲线相交。

这种情况下,我们在 Devcon 前达到 TTD 值得空间较小。但是我们有更多的时间基于一个潜在的 DAG 算力降幅来调整 TTD 值。以下是考虑到较低算力的其他 TTD 值:

Trending Cryptos

Related Reads

A 380% Soar, Shenzhen’s 100-Billion-Yuan IPO Rings the Bell

HKC Holdings, a major Chinese display panel manufacturer, has successfully listed on the Shenzhen Stock Exchange's main board. The company's shares surged over 380% on its debut, pushing its market capitalization to around 350 billion yuan (formerly reaching 500 billion yuan). Founded by Wang Zhiyong in Shenzhen's Huaqiangbei electronics market nearly three decades ago, HKC evolved from assembling monitors to becoming a global top-tier supplier of semiconductor display panels for TVs, monitors, and smartphones. The IPO marks a significant milestone for HKC and its backers. The company's growth into the capital-intensive panel manufacturing sector was supported through partnerships with state-owned capital from regions like Chongqing, Mianyang, and Chuzhou. Its shareholder list also includes BOE Technology's investment arm. In recent years, HKC reported strong financials, with core panel business contributing over 70% of revenue and clients including Samsung, TCL, and Xiaomi. This listing is seen as part of a broader trend in Shenzhen's evolving tech landscape. Beyond established giants, the city is nurturing clusters of leading companies in specialized sectors like robotics—exemplified by the "Shenzhen Robot Valley"—and storage chips, where a group of firms dubbed the "Storage Five Tigers" has achieved a combined trillion-yuan market valuation. Shenzhen's strategic focus on emerging industries such as AI terminals, low-altitude economy, and humanoid robotics aims to build new industrial depth and foster the next generation of tech champions.

marsbit6m ago

A 380% Soar, Shenzhen’s 100-Billion-Yuan IPO Rings the Bell

marsbit6m ago

Domestic First Explosion-Proof Certification, World's First Fueling Brain Solution: How Did They Secure Two 'Firsts'?

China's embodied AI sector is booming, with over ¥37 billion in funding this year. The focus has shifted decisively to real-world application, particularly in hazardous, repetitive tasks humans should avoid. A key, often prohibitive, barrier to entry for robots in environments like gas stations and oil fields is obtaining explosion-proof certification, requiring meticulous hardware and circuit design from the ground up. The article explores three main application areas. At gas stations, the challenge lies in executing a long, precise sequence of actions (opening caps, handling the fuel nozzle) with millimeter accuracy across diverse car models. For facility inspections, robots need sustained autonomous patrols combined with real-time anomaly detection and response. Port scenarios introduce the complexity of multi-robot coordination. Addressing the core challenge of long-horizon tasks, the piece highlights a technical breakthrough: a "world model"-driven approach. This enables predictive planning, allowing the AI to visualize the desired end-state (e.g., nozzle returned, cap closed) and work backward to synthesize intermediate visual frames. This "imagination" of the task trajectory, as implemented in the H-GAR architecture, guides action generation, significantly reducing cumulative error in multi-step operations. The three-step H-GAR process involves generating a coarse action draft, synthesizing target-conditioned observation frames, and then refining actions based on visual context and a memory of past successful motions. The conclusion emphasizes that success in specialized, safety-critical fields requires long-term commitment and deep integration of the "embodied brain" (AI) with a purpose-built, certified physical "body." Mastering this brain-body-data闭环 (closed-loop) is positioned as a crucial competitive advantage for commercialization.

marsbit55m ago

Domestic First Explosion-Proof Certification, World's First Fueling Brain Solution: How Did They Secure Two 'Firsts'?

marsbit55m ago

Bitcoin Bear Market Triggers Crypto Layoffs, Yet Fuels Industry's Most Aggressive M&A Wave Ever

A prolonged Bitcoin downturn is forcing crypto companies to lay off employees and automate operations, but has simultaneously triggered the industry's most aggressive wave of mergers and acquisitions (M&A). In the first half of 2026, crypto M&A deal value reached $93.7 billion, 26 times higher than the same period last year. This activity is primarily driven by traditional financial institutions—banks, payment processors, and asset managers—who are acquiring compliant crypto infrastructure like custody solutions, payment rails, and regulatory licenses instead of building them internally. Examples include Mastercard's acquisition of stablecoin firm BVNK and Franklin Templeton's launch of a dedicated crypto division via acquisition. This consolidation contrasts sharply with a shrinking crypto labor market, where active job openings have plummeted. Companies like Coinbase are restructuring to become "AI-native," leading to a sharp increase in roles requiring AI skills, while engineering and compliance positions now dominate hiring. Financially pressured crypto firms, such as Messari which was acquired at a fraction of its prior valuation, are becoming prime targets. Capital remains available but is highly selective, flowing overwhelmingly into businesses that bridge digital assets with traditional finance, such as tokenization platforms and regulated trading venues. The trend indicates a market where capital is rewarding compliant, utility-focused infrastructure while weaker models consolidate or downsize.

marsbit55m ago

Bitcoin Bear Market Triggers Crypto Layoffs, Yet Fuels Industry's Most Aggressive M&A Wave Ever

marsbit55m ago

Trading

Spot
Futures

Hot Articles

Discussions

Welcome to the HTX Community. Here, you can stay informed about the latest platform developments and gain access to professional market insights. Users' opinions on the price of ETH (ETH) are presented below.

活动图片