

ランキング5340
Bottos (BTO) 価格ライブチャート
今日のBottos(BTO)価格は ¥0.02363で、24時間の取引量は¥12.94Mであり、Bottos(BTO)の時価総額は¥12.9Mであるため、0.0000047%の市場支配力を持っています。Bottos (BTO) の価格は過去24時間で+2.96%変動しました。
BTO 価格データ
- 24時間取引量¥12.94M
- 史上最高値(ATH)¥53.81
- 24時間高値¥0.02396
- 史上最低値(ATL)¥0.01621
- 24時間安値¥0.02277
BTO 時価総額情報
- 時価総額¥12.9M
- 完全希薄化評価¥23.63M
- 時価総額/FDV54.6%
- 市場センチメントポジティブ
BTO 供給
- 流通供給量545.99M BTO
- 総供給量1B BTO
- 最大供給量∞
Bottos(BTO)の価格予測は、2025年に平均 ¥0.02363となります、最低価格の¥0.02032と最高価格の ¥0.03332の間で変動する可能性があります。2035年までに、Bottos(BTO)価格は ¥0.1443に達し、今日の価格から潜在的な+384.00%収益を提供する可能性があります。
年 | 最低価格 | 最高取引額 | 平均価格 | 変更 |
---|---|---|---|---|
2025 | ¥0.02032 | ¥0.03332 | ¥0.02363 | -- |
2026 | ¥0.02449 | ¥0.03787 | ¥0.02847 | +20.00% |
2027 | ¥0.03019 | ¥0.0418 | ¥0.03317 | +40.00% |
2028 | ¥0.02474 | ¥0.05398 | ¥0.03749 | +58.00% |
2029 | ¥0.04391 | ¥0.04939 | ¥0.04573 | +93.00% |
2030 | ¥0.04281 | ¥0.06897 | ¥0.04756 | +101.00% |
2031 | ¥0.03263 | ¥0.08158 | ¥0.05827 | +146.00% |
2032 | ¥0.04545 | ¥0.102 | ¥0.06992 | +195.00% |
2033 | ¥0.0774 | ¥0.1195 | ¥0.086 | +263.00% |
2034 | ¥0.05858 | ¥0.1264 | ¥0.1027 | +334.00% |
2035 | ¥0.1031 | ¥0.1443 | ¥0.1146 | +384.00% |
Bottos(BTO) 価格は過去24時間で +2.96% 変動し、過去7日間で +7.76% 変動しました。Bottos(BTO) の価格は過去30日間で+6.65%であり、昨年より-75.79%です。
期間 | 数量変更 | 変動率 |
---|---|---|
1H | +¥0.00001417 | +0.06% |
24H | +¥0.0006794 | +2.96% |
7D | +¥0.001701 | +7.76% |
30D | +¥0.001473 | +6.65% |
1Y | -¥0.07398 | -75.79% |
Bottos (BTO) 信頼性指標
52.85
信頼性スコア
パーセンタイルBTM 25%
Bottos(BTO)について
エクスプローラー
explorer.chainbottos.com
ウェブサイト
bottos.org
Platinum chains (bottoms) is the world's largest data collection pool based on blockchain technology, which solves the pain point of difficult access to high-quality data in the artificial intelligence (AI) industry, creates an intelligent data shareholding contract, realizes personal data wealth sharing by data mining, and builds an Ethereum environment in the AI industry. The platinum chains have two main goals: to build the most efficient data exchange center in the world and to build an "Ethereum" ecosystem in artificial intelligence. The former can help AI geeks and companies generate better models because of the new scale of data, and also generate updated models because of the updated data. The latter can help any geek team and company easily establish AI algorithms / models, and then support the search for high-quality data, so as to train algorithms / models. At the same time, it can bring new economic incentives to those data providers, and also bring higher value to crowdsourcing intelligence and aggregated data.